+
+
+ );
+ }
+}
diff --git a/src/components/activity-completion/completion-page-content.scss b/src/components/activity-completion/completion-page-content.scss
index 64050ac4..e8055051 100644
--- a/src/components/activity-completion/completion-page-content.scss
+++ b/src/components/activity-completion/completion-page-content.scss
@@ -68,6 +68,11 @@
margin: 0;
padding: 0;
+ &.with-backup-options {
+ margin-right: 30px;
+ width: 570px;
+ }
+
button {
align-items: center;
display: flex;
@@ -79,6 +84,13 @@
fill: $cc-orange-dark1;
margin-right: 5px;
}
+ &.disabled {
+ cursor: default;
+ opacity: 0.4;
+ &:hover{
+ background-color: $cc-orange-light1;
+ }
+ }
}
h1 {
flex-basis: 100%;
diff --git a/src/components/activity-completion/completion-page-content.test.tsx b/src/components/activity-completion/completion-page-content.test.tsx
index 5231969e..e090848e 100644
--- a/src/components/activity-completion/completion-page-content.test.tsx
+++ b/src/components/activity-completion/completion-page-content.test.tsx
@@ -15,7 +15,8 @@ describe("Completion Page Content component", () => {
Save My Work
+
+
@@ -158,17 +164,35 @@ export const CompletionPageContent: React.FC = (props) => {
}
-
+
);
};
diff --git a/src/components/activity-completion/completion-report-my-work.scss b/src/components/activity-completion/completion-report-my-work.scss
new file mode 100644
index 00000000..9892044a
--- /dev/null
+++ b/src/components/activity-completion/completion-report-my-work.scss
@@ -0,0 +1,18 @@
+@import "../vars.scss";
+
+.completion-report-my-work{
+ button {
+ width: 260px;
+ height: 44px;
+ margin: 10px 21px 10px 0;
+ padding: 9px 40px 10px;
+ border-radius: 4px;
+ border: solid 1.5px $cc-charcoal-light1;
+ background-color: $cc-orange;
+
+ &.disabled {
+ opacity: 0.35;
+ border-radius: 4px;
+ }
+ }
+}
\ No newline at end of file
diff --git a/src/components/activity-completion/completion-report-my-work.tsx b/src/components/activity-completion/completion-report-my-work.tsx
new file mode 100644
index 00000000..76a63b1c
--- /dev/null
+++ b/src/components/activity-completion/completion-report-my-work.tsx
@@ -0,0 +1,44 @@
+import React from "react";
+import { getStorage } from "../../storage/storage-facade";
+
+import "./completion-report-my-work.scss";
+
+interface IProps { }
+interface IState { }
+
+export class CompletionReportMyWork extends React.PureComponentSummary of Work: {activityTitle}
or
}
+
+
+ );
+ }
+}
diff --git a/src/components/activity-completion/report-backup-options.scss b/src/components/activity-completion/report-backup-options.scss
new file mode 100644
index 00000000..3ad71e14
--- /dev/null
+++ b/src/components/activity-completion/report-backup-options.scss
@@ -0,0 +1,85 @@
+@import "../vars.scss";
+
+.report-backup-options {
+ border: solid 1.5px $cc-charcoal-light2;
+ border-radius: 10px;
+ display: flex;
+ flex-wrap: wrap;
+ height: fit-content;
+ padding: 20px;
+ width: 260px;
+
+ .report-backup-option {
+ display: flex;
+ flex-wrap: wrap;
+ height: fit-content;
+ margin-bottom: 30px;
+
+ &.disabled {
+ opacity: 0.35;
+ }
+ &:last-child {
+ margin-bottom: 0;
+ }
+ }
+
+ a.button, button {
+ align-items: center;
+ display: flex;
+ justify-content: center;
+ margin-bottom: 8px;
+ padding: 0;
+ text-decoration: none;
+ width: 100%;
+
+ svg {
+ fill: $cc-orange-dark1;
+ margin-right: 5px;
+ height: 24px;
+ width: 24px;
+ &.complete {
+ margin-left: 5px;
+ }
+ &.incomplete {
+ margin-left: 5px;
+ }
+ }
+ }
+
+ .sending-text {
+ font-size: large;
+ font-weight: bold;
+ }
+ .sending-icon {
+ width: 100%;
+ padding: 30%;
+ svg {
+ &.progress {
+ stroke: $cc-orange-dark1;
+ stroke-width: 10;
+ fill: none;
+ stroke-linecap: round;
+ stroke-miterlimit: 10;
+ }
+ }
+ }
+ h2 {
+ border-bottom: solid 1px $cc-charcoal-light2;
+ margin: 0 0 10px;
+ padding: 0 0 14px;
+ width: 100%;
+ }
+ p {
+ font-size: 14px;
+ margin: 0;
+ padding: 0;
+ width: 226px;
+
+ &:last-child {
+ margin-bottom: 0;
+ }
+ }
+ svg {
+ margin-right: 5px;
+ }
+}
\ No newline at end of file
diff --git a/src/components/activity-completion/report-backup-options.tsx b/src/components/activity-completion/report-backup-options.tsx
new file mode 100644
index 00000000..e11f7155
--- /dev/null
+++ b/src/components/activity-completion/report-backup-options.tsx
@@ -0,0 +1,92 @@
+import React from "react";
+import IconFileDownload from "../../assets/svg-icons/icon-file-download.svg";
+import IconFileUpload from "../../assets/svg-icons/icon-file-upload.svg";
+import IconHelp from "../../assets/svg-icons/icon-help.svg";
+import { getStorage } from "../../storage/storage-facade";
+import IconComplete from "../../assets/svg-icons/icon-check-circle.svg";
+import IconIncomplete from "../../assets/svg-icons/icon-unfinished-check-circle.svg";
+import IconSpin from "../../assets/svg-icons/icon-clock-spin.svg";
+
+import "./report-backup-options.scss";
+
+interface IProps {}
+
+interface IState {
+ activityJSON: string,
+ filename: string,
+ sending: boolean,
+ lastSend: null| true | false;
+}
+
+export class ReportBackupOptions extends React.PureComponent
+ {this.ReportHelpText}
+
+ Sending ...
+
+
+
+ Share any work you have done in this activity with your teacher. You will have to be connected to the internet.
+
+
+
+ );
+ }
+
+ render(){
+ const { sending } = this.state;
+ return (
+ Back up your answers to create a desktop file that you can send to your teacher by email.
+
+
+ );
+ }
+}
diff --git a/src/components/activity-header/account-owner.tsx b/src/components/activity-header/account-owner.tsx
index def219bc..7473e4ea 100644
--- a/src/components/activity-header/account-owner.tsx
+++ b/src/components/activity-header/account-owner.tsx
@@ -5,11 +5,13 @@ import "./account-owner.scss";
interface IProps {
userName: string;
+ onClick?: () => void;
}
export class AccountOwner extends React.PureComponent Reporting/Backing Up My Work
+ { sending + ? this.renderProgress() + : this.renderButtons() + } +
+
{
render() {
const ccLogoLink = "https://concord.org/";
- const { fullWidth, projectId, userName, showSequence, onShowSequence } = this.props;
+ const { fullWidth, projectId, userName, showSequence, onShowSequence, onClickUsername } = this.props;
const projectType = ProjectTypes.find(pt => pt.id === projectId);
const logo = projectType?.headerLogo;
const projectURL = projectType?.url || ccLogoLink;
@@ -36,7 +38,7 @@ export class Header extends React.PureComponent {
{this.props.userName}
-
@@ -44,10 +46,11 @@ export class Header extends React.PureComponent
- {`${showSequence ? "Sequence:" : "Activity:"} ${contentName}`}
+ {`${titlePrefix}${contentName}`}
);
}
diff --git a/src/components/activity-introduction/introduction-import-answers.scss b/src/components/activity-introduction/introduction-import-answers.scss
new file mode 100644
index 00000000..0f0a327f
--- /dev/null
+++ b/src/components/activity-introduction/introduction-import-answers.scss
@@ -0,0 +1,18 @@
+.activity-import-upload{
+ display: flex;
+ padding: 5px;
+ height: 30px;
+ background-color: #eee;
+ border-radius: 4px;
+ margin: 4px 0 4px 0;
+
+ .instructions{
+ font-size: 0.9em;
+ display: flex;
+ margin-right: 10px;
+ }
+ input{
+ display: flex;
+ padding-top: 2px;
+ }
+}
\ No newline at end of file
diff --git a/src/components/activity-introduction/introduction-import-answers.tsx b/src/components/activity-introduction/introduction-import-answers.tsx
new file mode 100644
index 00000000..ff1df698
--- /dev/null
+++ b/src/components/activity-introduction/introduction-import-answers.tsx
@@ -0,0 +1,43 @@
+import React, { ChangeEvent } from "react";
+import { getStorage } from "../../storage/storage-facade";
+
+import "./introduction-import-answers.scss";
+
+export class ImportAnswers extends React.PureComponent {
+
+ private handleImportFile(event: ChangeEvent
+
+ );
+ }
+}
diff --git a/src/components/activity-page/activity-page-content.test.tsx b/src/components/activity-page/activity-page-content.test.tsx
index e6b5db10..b88a8bc7 100644
--- a/src/components/activity-page/activity-page-content.test.tsx
+++ b/src/components/activity-page/activity-page-content.test.tsx
@@ -17,6 +17,7 @@ describe("Activity Page Content component", () => {
totalPreviousQuestions={5}
setNavigation={stubFunction}
pluginsLoaded={true}
+ offlineMode={false}
/>);
expect(getByTestId("page-content")).toBeDefined();
expect(getByText("Hide")).toBeEnabled();
diff --git a/src/components/activity-page/activity-page-content.tsx b/src/components/activity-page/activity-page-content.tsx
index c8b44fbc..f997ff9b 100644
--- a/src/components/activity-page/activity-page-content.tsx
+++ b/src/components/activity-page/activity-page-content.tsx
@@ -24,6 +24,7 @@ interface IProps {
totalPreviousQuestions: number;
setNavigation: (refId: string, options: INavigationOptions) => void;
pluginsLoaded: boolean;
+ offlineMode: boolean;
}
interface IState {
@@ -132,6 +133,7 @@ export class ActivityPageContent extends React.PureComponent Import Work From File
+
+
{ this.state.showWarning && {this.setShowModal(false);}}
@@ -210,15 +442,55 @@ export class App extends React.PureComponent {
);
}
+ private renderContent = () => {
+ const {showSequenceIntro, sequence,
+ username, offlineMode, activity,
+ serviceWorkerStatus} = this.state;
+ if (offlineMode && serviceWorkerStatus !== "controlling") {
+ return ;
+ } else if (offlineMode) {
+ return activity ? this.renderActivity() :
+ {
contentName={sequence ? sequence.display_title || sequence.title || "" : activity.name}
showSequence={sequence !== undefined}
onShowSequence={sequence !== undefined ? this.handleShowSequenceIntro : undefined}
+ onClickUsername={openStudentInfoModal}
/>
{
- idle && !errorType &&
- {
teacherEditionMode={teacherEditionMode}
pluginsLoaded={pluginsLoaded}
glossaryPlugin={glossaryEmbeddable !== null}
+ offlineMode={offlineMode}
/>
}
{ glossaryEmbeddable && (activity.layout === ActivityLayouts.SinglePage || !isCompletionPage) &&
-
);
}
private renderActivityContent = (activity: Activity, currentPage: number, totalPreviousQuestions: number, fullWidth: boolean) => {
+ const {offlineMode} = this.state;
return (
<>
{ this.state.sequence && this.renderSequenceNav(fullWidth) }
@@ -288,6 +563,7 @@ export class App extends React.PureComponent {
setNavigation={this.handleSetNavigation}
key={`page-${currentPage}`}
pluginsLoaded={this.state.pluginsLoaded}
+ offlineMode={offlineMode}
/>
}
{ (activity.layout !== ActivityLayouts.SinglePage || this.state.sequence) &&
@@ -322,11 +598,13 @@ export class App extends React.PureComponent {
}
private renderSinglePageContent = (activity: Activity) => {
+ const {offlineMode} = this.state;
return (
{
}
private renderCompletionContent = (activity: Activity) => {
+ const showReportBackupOptions = this.state.offlineMode || queryValueBoolean("__forceOfflineData");
return (
{
Logger.log({ event: LogEventName.go_back_to_portal });
window.location.href = this.portalUrl;
}
-
+
private handleChangePage = (page: number) => {
const { currentPage, incompleteQuestions, activity } = this.state;
if (page > currentPage && incompleteQuestions.length > 0) {
@@ -455,4 +735,40 @@ export class App extends React.PureComponent {
this.setState({ pluginsLoaded: true });
}
+ private addActivityToOfflineManifest = async (offlineManifestAuthoringId: string, activity: Activity,
+ resourceUrl: string, contentUrl: string) => {
+ if (offlineManifestAuthoringId && isNotSampleActivityUrl(contentUrl)) {
+ const urls = await getAllUrlsInActivity(activity);
+
+ this.setState(prevState => {
+ let {offlineManifestAuthoringActivities} = prevState;
+ const {offlineManifestAuthoringCacheList} = prevState;
+
+ urls.forEach(urlInActivity => {
+ if (offlineManifestAuthoringCacheList.indexOf(urlInActivity) === -1) {
+ offlineManifestAuthoringCacheList.push(urlInActivity);
+ }
+ });
+
+ if (!prevState.offlineManifestAuthoringActivities.find(a => a.resourceUrl === resourceUrl)) {
+ offlineManifestAuthoringActivities =
+ offlineManifestAuthoringActivities.concat({ name: activity.name, resourceUrl, contentUrl });
+ setOfflineManifestAuthoringData(offlineManifestAuthoringId, {
+ activities: offlineManifestAuthoringActivities,
+ cacheList: offlineManifestAuthoringCacheList
+ });
+ }
+
+ return {offlineManifestAuthoringActivities, offlineManifestAuthoringCacheList};
+ });
+ }
+ }
+
+ private handleShowOfflineActivities = () => this.setState({ activity: undefined });
+
+ private trackOfflineResourceUrl(resourceUrl: string) {
+ TrackOfflineResourceUrl(resourceUrl);
+ Logger.setActivity(resourceUrl);
+ }
+
}
diff --git a/src/components/error/error.test.tsx b/src/components/error/error.test.tsx
index 11a3c7ed..0468940b 100644
--- a/src/components/error/error.test.tsx
+++ b/src/components/error/error.test.tsx
@@ -8,13 +8,18 @@ describe("Error component", () => {
expect(wrapper.find('[data-cy="error"]').length).toBe(1);
expect(wrapper.text()).toContain(errorMsg.auth);
});
-
- it("renders network error message", () => {
+
+ it("renders network error message when not in offline mode", () => {
const wrapper = shallow();
expect(wrapper.find('[data-cy="error"]').length).toBe(1);
expect(wrapper.text()).toContain(errorMsg.network);
});
-
+
+ it("does not render network error message when in offline mode", () => {
+ const wrapper = shallow();
+ expect(wrapper.find('[data-cy="error"]').length).toBe(0);
+ });
+
it("renders session timeout error message", () => {
const wrapper = shallow();
expect(wrapper.find('[data-cy="error"]').length).toBe(1);
diff --git a/src/components/error/error.tsx b/src/components/error/error.tsx
index 298d6bde..2873c98a 100644
--- a/src/components/error/error.tsx
+++ b/src/components/error/error.tsx
@@ -5,6 +5,7 @@ import "./error.scss";
interface IProps {
type: ErrorType;
onExit: () => void;
+ offlineMode?: boolean;
}
export const errorMsg: Record = {
@@ -13,8 +14,12 @@ export const errorMsg: Record = {
timeout: "Your session has expired."
};
+export const Error: React.FC = ({ type, onExit, offlineMode }) => {
+ // do not show network errors when in offline mode
+ if (offlineMode && (type === "network")) {
+ return null;
+ }
-export const Error: React.FC = ({ type, onExit }) => {
return (
= (props) => {
- const { activity, page, pageNumber, teacherEditionMode, pluginsLoaded, glossaryPlugin } = props;
+ const { activity, page, pageNumber, teacherEditionMode, pluginsLoaded, glossaryPlugin, offlineMode } = props;
const sideTips = pluginsLoaded && page ? getPageSideTipEmbeddables(activity, page) : [];
const verticalOffset = kExpandableContentTop + (sideTips.length + (glossaryPlugin ? 1 : 0)) * (kExpandableItemHeight + kExpandableContentMargin);
const sidebars = page && getPageSideBars(activity, page);
return (
{(window as any).__appVersionInfo || "(No Version Info)"}
+
+ Application: {__VERSION_INFO__}
+ {serviceWorkerVersionInfo && ` | Service Worker: ${serviceWorkerVersionInfo}`}
+
Loading
);
+ const { activity, idle, errorType, currentPage, username, pluginsLoaded, teacherEditionMode, sequence, portalData, showEditUserName, offlineMode } = this.state;
+ if (!activity) return (Loading activity ...
);
const totalPreviousQuestions = numQuestionsOnPreviousPages(currentPage, activity);
const fullWidth = (currentPage !== 0) && (activity.pages[currentPage - 1].layout === PageLayouts.Responsive);
const glossaryEmbeddable: IEmbeddablePlugin | undefined = getGlossaryEmbeddable(activity);
const isCompletionPage = currentPage > 0 && activity.pages[currentPage - 1].is_completion;
+
+ const closeStudentModal = (newUsername?: string) => {
+ if (newUsername) {
+ this.setState({
+ username: newUsername,
+ showEditUserName: false
+ });
+ } else {
+ this.setState({
+ showEditUserName: false
+ });
+ }
+ };
+
+ const openStudentInfoModal = () => {
+ if(this.studentInfo.canChangeName()) {
+ this.setState({showEditUserName: true});
+ }
+ };
+
return (
Hmm... we're having trouble connecting.
diff --git a/src/components/expandable-content/expandable-container.test.tsx b/src/components/expandable-content/expandable-container.test.tsx index 6e3a3214..e7706b67 100644 --- a/src/components/expandable-content/expandable-container.test.tsx +++ b/src/components/expandable-content/expandable-container.test.tsx @@ -10,11 +10,11 @@ const activityPlugins = _activityPlugins as Activity; describe("Expandable container component", () => { it("renders component", () => { - const wrapper = shallow(
{ teacherEditionMode && sideTips.map((sideTip: any) =>
- // Technically, the EmbeddablePluginSideTip won't be rendered if the plugins aren't loaded yet,
+ // Technically, the EmbeddablePluginSideTip won't be rendered if the plugins aren't loaded yet,
// but passing pluginLoaded into it makes it more consistent with the other plugins components
{
+ private wb: Workbox;
+ private startedInstalling = false;
+
+ public constructor(props: IProps) {
+ super(props);
+
+ if (!isOfflineHost() || !("serviceWorker" in navigator)) {
+ // Don't setup workbox
+ this.state = {
+ loadingOfflineManifest: false,
+ installedApplicationUrls: [],
+ installedContentUrls: [],
+ shouldStartInstalling: false
+ };
+ // TODO: show some useful message incase some one loads this page from a
+ // non offline host, or in a browser without service worker support
+ return;
+ }
+
+ const offlineManifestId = queryValue("offlineManifest");
+ const loadingOfflineManifest = !!offlineManifestId;
+
+ this.state = {
+ serviceWorkerVersionInfo: "Starting...",
+ loadingOfflineManifest,
+ offlineManifestId,
+ installedApplicationUrls: [],
+ installedContentUrls: [],
+ shouldStartInstalling: false
+ };
+
+ this.wb = new Workbox("service-worker.js");
+
+ this.wb.addEventListener("waiting", (event) => {
+ // TODO: in future work we should show a dialog using this recipe:
+ // https://developers.google.com/web/tools/workbox/guides/advanced-recipes#offer_a_page_reload_for_users
+ // For now just send a message to skip waiting so we don't have to do it manually in the devtools
+ // This will trigger a 'controlling' event which we are listening for below and reload the page when
+ // we get it
+ this.wb.messageSkipWaiting();
+ });
+
+ this.wb.addEventListener("activated", (event) => {
+ // Notes on when this fires:
+ // 1. On Page Load: this only fires if there isn't an active service worker.
+ // So it will only fire the first time a user visits the page.
+ // 2. On SW Update: This will also fire when the page is already loaded and
+ // a new version of the service worker becomes active. In this case
+ // Workbox is supposed to tell us with `event.isUpdate`
+ if (event.isUpdate) {
+ console.log("Workbox found an updated service worker has activated.");
+ if (!event.sw) {
+ // This should not happen
+ console.error("Worbox activated event without sw.", event);
+ this.setState({serviceWorkerVersionInfo: "Unknown worker activated..."});
+ } else {
+ this.getSWVersionInfoAndUpdateState(event.sw);
+ }
+ } else {
+ console.log("Workbox found the initial service worker has activated.");
+ }
+ });
+
+ navigator.serviceWorker.ready.then(registration => {
+ console.log("Browser says service worker is ready.");
+
+ // This promise should resolve on every page load once the service
+ // work becomes active. If the page is loaded in a way without a SW then
+ // it would never resolve.
+
+ // The registration.active is supposed to be set based on the docs for the ready
+ // promise: https://developer.mozilla.org/en-US/docs/Web/API/ServiceWorkerContainer/ready
+ if (registration.active) {
+ this.getSWVersionInfoAndUpdateState(registration.active);
+ } else {
+ console.error("browser did not provide the active service worker");
+ }
+ });
+
+ this.wb.register().then((_registration) => {
+ console.log("Workbox register() promise resolved", _registration);
+ });
+ }
+
+ async getSWVersionInfoAndUpdateState(sw: ServiceWorker) {
+ this.setState({serviceWorkerVersionInfo: "Checking..."});
+
+ const serviceWorkerVersionInfo = await this.getSWVersionInfo(sw);
+ this.setState({serviceWorkerVersionInfo});
+ if (serviceWorkerVersionInfo === __VERSION_INFO__) {
+ this.setState({shouldStartInstalling: true});
+ }
+ }
+
+ async getSWVersionInfo(sw: ServiceWorker): Promise {
+ try {
+ const versionInfo = await messageSW(sw, {type: "GET_VERSION_INFO"});
+ console.log("got service worker version info", versionInfo);
+ if (typeof versionInfo === "string") {
+ return versionInfo as string;
+ } else {
+ return "Invalid response!";
+ }
+ } catch (error) {
+ return "No response!";
+ }
+ }
+
+ addInstalledApplicationUrl(success:boolean, url:string) {
+ this.setState((prevState) => {
+ const updatedUrls = prevState.installedApplicationUrls.concat([{success, url}]);
+ return {installedApplicationUrls: updatedUrls};
+ });
+ }
+
+ addInstalledContentUrl(success:boolean, url:string) {
+ this.setState((prevState) => {
+ const updatedUrls = prevState.installedContentUrls.concat([{success, url}]);
+ return {installedContentUrls: updatedUrls};
+ });
+ }
+
+ async cacheApplication() {
+ // double check we haven't already started
+ if (this.startedInstalling) {
+ return;
+ }
+
+ this.startedInstalling = true;
+ const wbManifest = (window as any).__wbManifest;
+
+ // FIXME: this caching is going to happen after the initial page load
+ // that means that the manifest.json and index.html will be requested by
+ // Chrome before they are cached. The manifest.json is referened by
+ // install.html so the user can add the app to their computer from the
+ // install.html page. The manifest.json references index.html in its
+ // start_url field.
+ // The index.html request comes from Chrome's new installable detection that
+ // makes an offline request to the start_url:
+ // https://goo.gle/improved-pwa-offline-detection
+ // The best solution to this would be to somehow indicate to Chrome that
+ // we aren't ready to be used offline until the app has been cached.
+ // The only way I can find to do that is the block the service worker in the
+ // installing state. If the service worker is not active, then Chrome will
+ // not try to make the offline start_url request.
+ // But I don't think we can do that, because we need to block it while we
+ // send it the manifest from the page. I don't think the page can talk
+ // to the service worker while it is installing. We should test that.
+ //
+ // Alternative we could have the service worker respond with a fake index.html
+ // so Chrome will be happy, but really the app won't be installed at this
+ // point. So the page would have to say something to that effect.
+ //
+ //
+ // There is this event:
+ // https://developer.mozilla.org/en-US/docs/Web/API/BeforeInstallPromptEvent
+ // which is sent when Chrome determines the PWA can be installed. But it
+ // isn't possible to reject it or tell Chrome we aren't ready yet.
+ //
+ // We don't have to worry about this immediately because it isn't enforced
+ // until Chrome 93 which is due August 2021. It is just annoying to see the
+ // errors in the network log.
+ const appUrls = wbManifest.map((entry: {revision: null | string; url: string}) => {
+ // Add Worbox's standard __WB_REVISION__ to the files. The service worker
+ // strips this out from the key used in cache storage, but it is used when
+ // fetching the asset. This prevents some caching problems when the url
+ // is fetched. The service worker does use `cache: "no-store"` so the
+ // browser disk cache should not be used during the install of the assets
+ // but cloudfront could still be caching them, so having these revisions
+ // should help avoid caching issues from CloudFront
+ if (entry.revision) {
+ const parsedUrl = queryString.parseUrl(entry.url);
+ parsedUrl.query.__WB_REVISION__ = entry.revision;
+ return queryString.stringifyUrl(parsedUrl);
+ } else {
+ return entry.url;
+ }
+ });
+
+ // It is not clear why, but it seems like the service worker only handles one
+ // CACHE_URLS_WITH_PROGRESS at time. The next message seems to get queued
+ // until the first is complete. Perhaps because it calls event.waitUntil
+ // We are starting the request for caching the offline manifest after this
+ // caching of the application files. But we aren't doing an await or promise
+ // so in theory they might start synchronously. But it seems like the
+ // service worker is serializing the messages
+ //
+ // TODO: show something in the UI while the application files are caching
+ cacheUrlsWithProgress({
+ workbox: this.wb,
+ urls: appUrls,
+ onCachingStarted: (urls) => {
+ console.log("started caching application");
+ },
+ onUrlCached: (url) => {
+ console.log(`cached url ${url}`);
+ this.addInstalledApplicationUrl(true, url);
+ },
+ onUrlCacheFailed: (url, err) => {
+ console.error(`failed to cache ${url}`, err);
+ this.addInstalledApplicationUrl(false, url);
+ },
+ onCachingFinished: () => {
+ console.log("finished caching application");
+ },
+ });
+
+ const {offlineManifestId} = this.state;
+ if (offlineManifestId) {
+ // The offline manifest is the list of files for the activities needed
+ // offline. Currently this offline manifest file itself is not put into cache
+ // storage by the service worker. The saveOfflineManifestToOfflineActivities
+ // adds information about the manifest to local storage.
+ // The setting of the offlineManifest in the state triggers the loading
+ // of the OfflineManifestLoadingModal which then triggers a call
+ // similiar to cacheUrlsWithProgress but with the urls from the offline manifest
+ getOfflineManifest(offlineManifestId)
+ .then(async (offlineManifest) => {
+ console.log("got offlineManifest", offlineManifest);
+ if (offlineManifest) {
+ await saveOfflineManifestToOfflineActivities(offlineManifest);
+ this.setState({offlineManifest});
+ }
+ })
+ .catch(error => {
+ console.error(error);
+ });
+ }
+ }
+
+ render() {
+ const {serviceWorkerVersionInfo, offlineManifest, offlineManifestId,
+ loadingOfflineManifest, installedApplicationUrls,
+ installedContentUrls, shouldStartInstalling} = this.state;
+
+ if (shouldStartInstalling && !this.startedInstalling) {
+ this.cacheApplication();
+ }
+
+ const installedItems = installedApplicationUrls.map(urlInfo => {
+ return (
+ {
+export class ModalDialog extends Component {
render() {
- const { title, label, showModal, onClose } = this.props;
+ const { title, label, showModal, onClose, onAccept, acceptButtonText, closeButtonText} = this.props;
const handleClose = () => {
onClose();
};
+ const handleAccept = (result: any) => {
+ if (onAccept) {
+ onAccept(result);
+ }
+ };
+ const okText = acceptButtonText ? acceptButtonText : "OK";
+ const closeText = closeButtonText ? closeButtonText : (onAccept ? "Cancel" : "Close");
return (
{
>
);
diff --git a/src/components/offline-activities.scss b/src/components/offline-activities.scss
new file mode 100644
index 00000000..68a29e45
--- /dev/null
+++ b/src/components/offline-activities.scss
@@ -0,0 +1,17 @@
+.offline-activities {
+
+ .offline-content {
+ padding: 20px;
+ background-color: white;
+
+ th {
+ text-align: left;
+ }
+
+ .activity {
+ color: #00f;
+ text-decoration: underline;
+ cursor: pointer;
+ }
+ }
+}
\ No newline at end of file
diff --git a/src/components/offline-activities.tsx b/src/components/offline-activities.tsx
new file mode 100644
index 00000000..7c57444c
--- /dev/null
+++ b/src/components/offline-activities.tsx
@@ -0,0 +1,95 @@
+import React from "react";
+import { getOfflineActivities } from "../offline-manifest-api";
+import { OfflineActivity } from "../types";
+import { Header } from "./activity-header/header";
+
+import "./offline-activities.scss";
+
+const OfflineActivityListRow = (props: {activity: OfflineActivity}) => {
+ const {name, manifestName, contentUrl, resourceUrl} = props.activity;
+ const displayName = manifestName.length > 0 ? `${manifestName}: ${name}` : name;
+ return (
+
+ {
+ // Add class column back at a later date
+ // TDB
+ }
+
+ {displayName}
+
+
+ );
+};
+
+interface IProps {
+ username: string;
+}
+
+interface IState {
+ loading: boolean;
+ offlineActivities: OfflineActivity[]
+}
+
+export class OfflineActivities extends React.Component {
+
+ constructor (props: IProps) {
+ super(props);
+ this.state = {
+ loading: true,
+ offlineActivities: []
+ };
+ }
+
+ async UNSAFE_componentWillMount() {
+ const offlineActivities = await getOfflineActivities();
+ this.setState({offlineActivities, loading: false});
+ }
+
+ renderNoActivitiesFound() {
+ return (
+
+
+
+ );
+ }
+
+ render() {
+ const { username } = this.props;
+ const { loading, offlineActivities } = this.state;
+
+ return (
+ {
+ constructor(props: IProps) {
+ super(props);
+
+ this.state = {
+ };
+ }
+
+ render() {
+ const { serviceWorkerStatus } = this.props;
+ if (serviceWorkerStatus !== "activated") {
+ return (
+ {
+ render() {
+ const { offlineManifest, offlineManifestAuthoringId, offlineManifestAuthoringActivities, offlineManifestAuthoringCacheList } = this.props;
+
+ const handleDownloadClicked = (e: React.MouseEvent) => {
+ const json = getOfflineManifestAuthoringDownloadJSON(
+ offlineManifest?.name ?? "Untitled Offline Manifest",
+ {activities: offlineManifestAuthoringActivities, cacheList: offlineManifestAuthoringCacheList.slice().sort()}
+ );
+ const blob = new Blob([ JSON.stringify(json, null, 2) ], { type: "application/json" });
+ e.currentTarget.href = URL.createObjectURL(blob);
+ };
+
+ const handleClearAuthoringId = () => {
+ if (confirm("Exit authoring (clears the offline manifest authoring id in localstorage)?")) {
+ clearOfflineManifestAuthoringId();
+ const query = queryString.parse(window.location.search);
+ delete query.setOfflineManifestAuthoringId;
+ window.location.replace(`?${queryString.stringify(query)}`);
+ }
+ };
+
+ const handleClearAuthoringData = () => {
+ if (confirm("Are your SURE you want to clear ALL the saved authoring data?")) {
+ clearOfflineManifestAuthoringData(offlineManifestAuthoringId);
+ window.location.reload();
+ }
+ };
+
+ return (
+ {
+ constructor(props: IProps) {
+ super(props);
+
+ this.state = {
+ urlsToCache: [],
+ urlsCached: [],
+ urlsFailedToCache: [],
+ caching: true,
+ };
+ }
+
+ componentDidMount() {
+ const { offlineManifest, workbox } = this.props;
+
+ cacheOfflineManifest({
+ workbox,
+ offlineManifest,
+ onCachingStarted: (urls) => {
+ this.setState({urlsToCache: urls});
+ this.props.onCachingStarted?.(urls);
+ },
+ onUrlCached: (url) => {
+ this.setState((prevState) => ({urlsCached: prevState.urlsCached.concat(url)}));
+ this.props.onUrlCached?.(url);
+ },
+ onUrlCacheFailed: (url, err) => {
+ console.error("Failed to cache:", url);
+ this.setState((prevState) => ({urlsFailedToCache: prevState.urlsFailedToCache.concat(url)}));
+ this.props.onUrlCacheFailed?.(url, err);
+ },
+ onCachingFinished: () => {
+ this.setState({caching: false});
+ this.props.onCachingFinished?.();
+ }
+ });
+ }
+
+ renderCaching() {
+ const { offlineManifest } = this.props;
+ const { urlsToCache, urlsCached, urlsFailedToCache} = this.state;
+
+ return (
+ <>
+ {
+ render() {
+ return (
+ = (props) => {
- const { activity, teacherEditionMode, pluginsLoaded } = props;
+ const { activity, teacherEditionMode, pluginsLoaded, offlineMode } = props;
let questionNumber = 0;
let embeddableNumber = 0;
@@ -41,6 +42,7 @@ export const SinglePageContent: React.FC = (props) => {
linkedPluginEmbeddable={linkedPluginEmbeddable}
teacherEditionMode={teacherEditionMode}
pluginsLoaded={pluginsLoaded}
+ offlineMode={offlineMode}
/>
);
})
diff --git a/src/components/student-info-modal.scss b/src/components/student-info-modal.scss
new file mode 100644
index 00000000..f1bb4f20
--- /dev/null
+++ b/src/components/student-info-modal.scss
@@ -0,0 +1,5 @@
+// @import "./vars.scss";
+
+.student-info-modal {
+
+}
diff --git a/src/components/student-info-modal.tsx b/src/components/student-info-modal.tsx
new file mode 100644
index 00000000..ca7445b1
--- /dev/null
+++ b/src/components/student-info-modal.tsx
@@ -0,0 +1,61 @@
+import React, { ChangeEvent, Component } from "react";
+// import Modal from "react-modal";
+import {ModalDialog} from "./modal-dialog";
+import {StudentInfo} from "../student-info";
+
+import "./student-info-modal.scss";
+
+interface IProps {
+ studentInfo: StudentInfo;
+ showModal: boolean;
+ onClose: (newName?: string) => void;
+}
+
+interface IState {
+ studentName: string;
+}
+
+export class StudentInfoModal extends Component {
+ public constructor(props: IProps) {
+ super(props);
+ this.state = {
+ studentName: this.props.studentInfo.name
+ };
+ }
+
+
+ render() {
+ const { studentInfo, showModal, onClose } = this.props;
+ const changeName = (event: ChangeEvent) => {
+ const value = event.target.value;
+ if (studentInfo.setName(value)) {
+ this.setState({studentName: studentInfo.name});
+ }
+ };
+
+ const _onSave = () => {
+ onClose(this.state.studentName);
+ };
+
+ const _onClose = () => {
+ onClose();
+ };
+
+ return (
+
+
+
+ );
+ }
+}
diff --git a/src/components/warning-banner.scss b/src/components/warning-banner.scss
index 04f3646c..37c43a97 100644
--- a/src/components/warning-banner.scss
+++ b/src/components/warning-banner.scss
@@ -1,12 +1,22 @@
@import "./vars.scss";
.warning-banner {
- display: flex;
- flex-direction: row;
- background-color: $cc-orange;
- color: black;
- font-size: 22px;
- padding: 10px;
- min-height: 50px;
+ height: 60px;
width: 100%;
+ margin-bottom: 3px;
+ font-size: 18px;
+ font-weight: bold;
+
+ .inner {
+ display: flex;
+ flex-direction: row;
+ align-items: center;
+ justify-content: center;
+ height: 100%;
+ width: $content-width;
+ box-sizing: border-box;
+ margin: auto;
+ background-color: #f00;
+ color: #fff;
+ }
}
diff --git a/src/components/warning-banner.tsx b/src/components/warning-banner.tsx
index bc28243c..64036a5c 100644
--- a/src/components/warning-banner.tsx
+++ b/src/components/warning-banner.tsx
@@ -5,7 +5,11 @@ import "./warning-banner.scss";
export const WarningBanner: React.FC = () => {
return (
Activity Player
+
+
+
+
+
+
+
+
diff --git a/src/install.sass b/src/install.sass
new file mode 100644
index 00000000..761e33a4
--- /dev/null
+++ b/src/install.sass
@@ -0,0 +1,2 @@
+body
+ font-family: arial, helvetica, sans-serif;
diff --git a/src/install.tsx b/src/install.tsx
new file mode 100644
index 00000000..a03b0d6a
--- /dev/null
+++ b/src/install.tsx
@@ -0,0 +1,11 @@
+import "ts-polyfill";
+import React from "react";
+import ReactDOM from "react-dom";
+import { InstallApp } from "./components/install-app";
+
+import "./install.sass";
+
+ReactDOM.render(
+ => {
return new Promise((resolve, reject) => {
- const urlRegex = /^(https:|http:)\/\/\S+/;
- if (activity.match(urlRegex)) {
- getActivityDefinitionFromLara(activity).then(resolve);
+ if (isNotSampleActivityUrl(activity)) {
+ fetchActivityDefinition(activity).then(resolve);
+ } else if (sampleActivities[activity]) {
+ setTimeout(() => resolve(rewriteProxiableIframeUrls(sampleActivities[activity])), 250);
} else {
- if (sampleActivities[activity]) {
- setTimeout(() => resolve(sampleActivities[activity]), 250);
- } else {
- reject(`No sample activity matches ${activity}`);
- }
+ reject(`No sample activity matches ${activity}`);
}
});
};
-const getActivityDefinitionFromLara = (activityUrl: string): Promise => {
+const fetchActivityDefinition = (activityUrl: string): Promise => {
return new Promise((resolve, reject) => {
- fetch(activityUrl)
- .then(response => {
- if (response.status !== 200) {
- reject(`Errored fetching ${activityUrl}. Status Code: ${response.status}`);
- return;
- }
-
- response.json().then(function(data) {
- resolve(data);
+ return fetch(activityUrl)
+ .then(response => {
+ if (response.status !== 200) {
+ reject(`Errored fetching ${activityUrl}. Status Code: ${response.status}`);
+ return;
+ }
+ response.json()
+ .then((data) => resolve(rewriteProxiableIframeUrls(data)))
+ .catch(reject);
+ })
+ .catch(function(err) {
+ reject(`Errored fetching ${activityUrl}. ${err}`);
});
- })
- .catch(function(err) {
- reject(`Errored fetching ${activityUrl}. ${err}`);
- });
});
};
diff --git a/src/lara-plugin/events/index.ts b/src/lara-plugin/events/index.ts
index c152aee6..4859de1f 100644
--- a/src/lara-plugin/events/index.ts
+++ b/src/lara-plugin/events/index.ts
@@ -50,11 +50,30 @@ export interface IInteractiveSupportedFeaturesEvent {
supportedFeatures: ISupportedFeatures;
}
+export interface IPluginSyncUpdate {
+ status: "started" | "working" | "failed" | "completed";
+ message?: string;
+}
+
+export type PluginSyncUpdateCallback = (update: IPluginSyncUpdate) => void;
+
+export interface IPluginSyncEvent {
+ maxUpdateCallbackInterval: number;
+ updateCallback: PluginSyncUpdateCallback;
+}
+
+// Events for plugin communication.
+
/**
* SupportedFeatures event handler.
*/
export type IInteractiveSupportedFeaturesEventHandler = (event: IInteractiveSupportedFeaturesEvent) => void;
+/**
+ * PluginSync event handler.
+ */
+export type IPluginSyncRequestEventHandler = (event: IPluginSyncEvent) => void;
+
const emitter = new EventEmitter2({
maxListeners: Infinity
});
@@ -88,3 +107,13 @@ export const onInteractiveSupportedFeatures = (handler: IInteractiveSupportedFea
export const offInteractiveSupportedFeatures = (handler: IInteractiveSupportedFeaturesEventHandler) => {
emitter.off("interactiveSupportedFeatures", handler);
};
+
+export const emitPluginSyncRequest = (event: IPluginSyncEvent) => {
+ emitter.emit("PluginSyncRequest", event);
+};
+export const onPluginSyncRequest = (handler: IPluginSyncRequestEventHandler) => {
+ emitter.on("PluginSyncRequest", handler);
+};
+export const offPluginSyncRequest = (handler: IPluginSyncRequestEventHandler) => {
+ emitter.off("PluginSyncRequest", handler);
+};
diff --git a/src/lara-plugin/plugin-api/events.spec.ts b/src/lara-plugin/plugin-api/events.spec.ts
new file mode 100644
index 00000000..73fd80c2
--- /dev/null
+++ b/src/lara-plugin/plugin-api/events.spec.ts
@@ -0,0 +1,32 @@
+import { events } from "./events";
+import * as EventsImpl from "../events";
+
+describe("Events", () => {
+ it("should delegate methods to events lib", () => {
+ jest.spyOn(EventsImpl, "onLog");
+ jest.spyOn(EventsImpl, "offLog");
+ jest.spyOn(EventsImpl, "onInteractiveAvailable");
+ jest.spyOn(EventsImpl, "offInteractiveAvailable");
+ jest.spyOn(EventsImpl, "onInteractiveSupportedFeatures");
+ jest.spyOn(EventsImpl, "offInteractiveSupportedFeatures");
+ jest.spyOn(EventsImpl, "onPluginSyncRequest");
+ jest.spyOn(EventsImpl, "offPluginSyncRequest");
+ const handler = jest.fn();
+ events.onLog(handler);
+ expect(EventsImpl.onLog).toHaveBeenCalledWith(handler);
+ events.offLog(handler);
+ expect(EventsImpl.offLog).toHaveBeenCalledWith(handler);
+ events.onInteractiveAvailable(handler);
+ expect(EventsImpl.onInteractiveAvailable).toHaveBeenCalledWith(handler);
+ events.offInteractiveAvailable(handler);
+ expect(EventsImpl.offInteractiveAvailable).toHaveBeenCalledWith(handler);
+ events.onInteractiveSupportedFeatures(handler);
+ expect(EventsImpl.onInteractiveSupportedFeatures).toHaveBeenCalledWith(handler);
+ events.offInteractiveSupportedFeatures(handler);
+ expect(EventsImpl.offInteractiveSupportedFeatures).toHaveBeenCalledWith(handler);
+ events.onPluginSyncRequest(handler);
+ expect(EventsImpl.onPluginSyncRequest).toHaveBeenCalledWith(handler);
+ events.offPluginSyncRequest(handler);
+ expect(EventsImpl.offPluginSyncRequest).toHaveBeenCalledWith(handler);
+ });
+});
diff --git a/src/lara-plugin/plugin-api/events.ts b/src/lara-plugin/plugin-api/events.ts
new file mode 100644
index 00000000..dc76ee5e
--- /dev/null
+++ b/src/lara-plugin/plugin-api/events.ts
@@ -0,0 +1,61 @@
+import {
+ onLog, offLog, ILogEventHandler,
+ onInteractiveAvailable, offInteractiveAvailable, IInteractiveAvailableEventHandler,
+ onInteractiveSupportedFeatures, offInteractiveSupportedFeatures, IInteractiveSupportedFeaturesEventHandler,
+ onPluginSyncRequest, offPluginSyncRequest, IPluginSyncRequestEventHandler
+} from "../events";
+// Export event types as a part of Plugin API.
+export {
+ onLog, offLog, ILogData, ILogEventHandler,
+ onInteractiveAvailable, offInteractiveAvailable,
+ IInteractiveAvailableEvent, IInteractiveAvailableEventHandler,
+ onInteractiveSupportedFeatures, offInteractiveSupportedFeatures,
+ IInteractiveSupportedFeaturesEvent, IInteractiveSupportedFeaturesEventHandler
+} from "../events";
+
+/**
+ * Functions related to event observing provided by LARA.
+ */
+export const events = {
+ // Why do we need explicit delegation instead of something like:
+ // onLog: onLogImpl
+ // Because that's the only way for TypeDoc to pick up types and generate nice docs.
+
+ /**
+ * Subscribes to log events. Gets called when any event is logged to the CC Log Manager app.
+ */
+ onLog: (handler: ILogEventHandler) => onLog(handler),
+ /**
+ * Removes log event handler.
+ */
+ offLog: (handler: ILogEventHandler) => offLog(handler),
+ /**
+ * Subscribes to InteractiveAvailable events. Gets called when any interactive changes its availability state.
+ * Currently uses when click to play mode is enabled and the click to play overlay is clicked.
+ */
+ onInteractiveAvailable: (handler: IInteractiveAvailableEventHandler) => onInteractiveAvailable(handler),
+ /**
+ * Removes InteractiveAvailable event handler.
+ */
+ offInteractiveAvailable: (handler: IInteractiveAvailableEventHandler) => offInteractiveAvailable(handler),
+ /**
+ * Subscribes to InteractiveSupportedFeatures events. Gets called when any interactive calls setSupportedFeatures().
+ */
+ onInteractiveSupportedFeatures:
+ (handler: IInteractiveSupportedFeaturesEventHandler) => onInteractiveSupportedFeatures(handler),
+ /**
+ * Removes InteractiveSupportedFeatures event handler.
+ */
+ offInteractiveSupportedFeatures:
+ (handler: IInteractiveSupportedFeaturesEventHandler) => offInteractiveSupportedFeatures(handler),
+ /**
+ * Subscribes to PluginSyncRequest events. Gets called when the plugins are commanded to sync their offline data.
+ */
+ onPluginSyncRequest:
+ (handler: IPluginSyncRequestEventHandler) => onPluginSyncRequest(handler),
+ /**
+ * Removes PluginSyncRequest event handler.
+ */
+ offPluginSyncRequest:
+ (handler: IPluginSyncRequestEventHandler) => offPluginSyncRequest(handler)
+};
diff --git a/src/lara-plugin/plugin-api/index.ts b/src/lara-plugin/plugin-api/index.ts
index 61155b61..c93216f0 100644
--- a/src/lara-plugin/plugin-api/index.ts
+++ b/src/lara-plugin/plugin-api/index.ts
@@ -3,4 +3,4 @@ export * from "./plugins";
export * from "./sidebar";
export * from "./popup";
export * from "./decorate-content";
-// LARA_CODE export * from "./events";
+export * from "./events";
diff --git a/src/lara-plugin/plugins/plugin-context.spec.ts b/src/lara-plugin/plugins/plugin-context.spec.ts
index 32a62abb..17c60543 100644
--- a/src/lara-plugin/plugins/plugin-context.spec.ts
+++ b/src/lara-plugin/plugins/plugin-context.spec.ts
@@ -33,7 +33,8 @@ describe("Plugin runtime context helper", () => {
firebaseJwtUrl: "http://firebase.jwt._FIREBASE_APP_.com",
wrappedEmbeddable: null,
componentLabel: "test",
- resourceUrl: "http://lara.activity.com/123"
+ resourceUrl: "http://lara.activity.com/123",
+ offlineMode: false
};
it("should copy basic properties to runtime context", () => {
diff --git a/src/lara-plugin/plugins/plugin-context.ts b/src/lara-plugin/plugins/plugin-context.ts
index c8cecc03..db91af2a 100644
--- a/src/lara-plugin/plugins/plugin-context.ts
+++ b/src/lara-plugin/plugins/plugin-context.ts
@@ -7,7 +7,7 @@ import $ from "jquery";
// LARA_CODE import * as $ from "jquery";
// ACTIVITY_PLAYER_CODE:
import { Logger } from "../../lib/logger";
-import { getPortalData, setLearnerPluginState } from "../../firebase-db";
+import { getStorage } from "../../storage/storage-facade";
import { getFirebaseJWT } from "../../portal-api";
export type IPluginContextOptions = IPluginRuntimeContextOptions | IPluginAuthoringContextOptions;
@@ -53,6 +53,8 @@ export interface IPluginRuntimeContextOptions extends IPluginCommonOptions {
embeddablePluginId: number | null;
/** URL of the resource associated with the current run (sequence URL or activity URL) */
resourceUrl: string;
+ /** Flag denoting offline mode of an Activity Player activity */
+ offlineMode: boolean;
}
export interface IPluginAuthoringContextOptions extends IPluginCommonOptions {
@@ -138,7 +140,8 @@ export const saveAuthoredPluginState = (authoringSaveStateUrl: string, authorDat
const getFirebaseJwtFromPortal = (appName: string): Promise => {
return new Promise((resolve, reject) => {
- const portalData = getPortalData();
+ const storage = getStorage();
+ const portalData = storage.getPortalData();
if (portalData && (portalData.type === "authenticated") && portalData.basePortalUrl && portalData.rawPortalJWT) {
return getFirebaseJWT(portalData.basePortalUrl, portalData.rawPortalJWT, {firebase_app: appName})
.then(([token, firebaseJWT]) => {
@@ -194,6 +197,7 @@ const fetchPluginEventLogData = (context: IPluginRuntimeContextOptions) => {
};
export const generateRuntimePluginContext = (options: IPluginRuntimeContextOptions): IPluginRuntimeContext => {
+ const storage = getStorage();
const context = {
name: options.name,
url: options.url,
@@ -205,11 +209,12 @@ export const generateRuntimePluginContext = (options: IPluginRuntimeContextOptio
remoteEndpoint: options.remoteEndpoint,
userEmail: options.userEmail,
resourceUrl: options.resourceUrl,
- saveLearnerPluginState: (state: string) => setLearnerPluginState(options.pluginId, state),
+ saveLearnerPluginState: (state: string) => storage.setLearnerPluginState(options.pluginId, options.resourceUrl, state),
getClassInfo: () => getClassInfo(options.classInfoUrl),
getFirebaseJwt: (appName: string) => getFirebaseJwtFromPortal(appName),
wrappedEmbeddable: options.wrappedEmbeddable ? generateEmbeddableRuntimeContext(options.wrappedEmbeddable) : null,
- log: (logData: string | ILogData) => log(options, logData)
+ log: (logData: string | ILogData) => log(options, logData),
+ offlineMode: options.offlineMode
};
return context;
};
diff --git a/src/lara-plugin/plugins/plugins.spec.ts b/src/lara-plugin/plugins/plugins.spec.ts
index c0c5679e..f9722294 100644
--- a/src/lara-plugin/plugins/plugins.spec.ts
+++ b/src/lara-plugin/plugins/plugins.spec.ts
@@ -68,7 +68,8 @@ describe("Plugins", () => {
embeddablePluginId: null,
wrappedEmbeddable: null,
componentLabel: "test",
- resourceUrl: "http://lara.activity.com/123"
+ resourceUrl: "http://lara.activity.com/123",
+ offlineMode: false
};
const authoringContextOptions: IPluginAuthoringContextOptions = {
type: "authoring",
diff --git a/src/lib/logger.ts b/src/lib/logger.ts
index 3a47060c..60d80d08 100644
--- a/src/lib/logger.ts
+++ b/src/lib/logger.ts
@@ -1,8 +1,14 @@
import { v4 as uuid } from "uuid";
import { DEBUG_LOGGER } from "../lib/debug";
import { LaraGlobalType } from "../lara-plugin/index";
+import { Role } from "../student-info";
+import { dexieStorage } from "../storage/dexie-storage";
+import { LogMessage } from "../types";
+import { isProduction } from "../utilities/host-utils";
-const logManagerUrl = "//cc-log-manager.herokuapp.com/api/logs";
+interface LogMessageWithId extends LogMessage {
+ id?: string; // has to optional to allow deletes
+}
export interface LogParams {
event: string | LogEventName,
@@ -12,26 +18,6 @@ export interface LogParams {
interactive_url?: string | undefined
}
-interface LogMessage {
- application: string;
- run_remote_endpoint?: string;
- username: string;
- role: string;
- classHash: string;
- session: string;
- appMode: string;
- sequence: string | undefined;
- sequenceActivityIndex: number;
- activity: string | undefined,
- activityPage: number;
- time: number;
- event: string;
- event_value: any;
- parameters: any;
- interactive_id: string | undefined,
- interactive_url: string | undefined,
-}
-
export enum LogEventName {
change_sequence_activity,
change_activity_page,
@@ -48,33 +34,55 @@ export enum LogEventName {
session_timeout
}
+export interface ILogSyncUpdate {
+ status: "started" | "working" | "failed" | "completed";
+ message?: string;
+}
+
+export type LogSyncUpdateCallback = (update: ILogSyncUpdate) => void;
+
export class Logger {
+ private logManagerUrl = "//cc-log-manager.herokuapp.com/api/logs";
+
public static initializeLogger(LARA: LaraGlobalType,
username: string,
- role: string,
+ role: Role,
classHash: string,
teacherEdition: boolean,
sequence: string | undefined,
sequenceActivityIndex: number,
activity: string | undefined,
activityPage: number,
- runRemoteEndpoint: string) {
+ runRemoteEndpoint: string,
+ offlineMode: boolean) {
if (DEBUG_LOGGER) {
console.log("Logger#initializeLogger called.");
}
- this._instance = new Logger(LARA, username, role, classHash, teacherEdition, sequence, sequenceActivityIndex, activity, activityPage, runRemoteEndpoint);
+ this._instance = new Logger(LARA, username, role, classHash, teacherEdition, sequence, sequenceActivityIndex, activity, activityPage, runRemoteEndpoint, offlineMode);
}
public static updateActivity(activity: string) {
- this._instance.activity = activity;
+ if (this._instance) {
+ this._instance.activity = activity;
+ }
}
public static updateActivityPage(page: number) {
- this._instance.activityPage = page;
+ if (this._instance) {
+ this._instance.activityPage = page;
+ }
}
public static updateSequenceActivityindex(index: number) {
- this._instance.sequenceActivityIndex = index;
+ if (this._instance) {
+ this._instance.sequenceActivityIndex = index;
+ }
+ }
+
+ public static setActivity(activity: string) {
+ if (this._instance) {
+ this._instance.activity = activity;
+ }
}
public static log(logParams: LogParams) {
@@ -83,10 +91,61 @@ export class Logger {
const eventString = typeof event === "string" ? event : LogEventName[event];
const logMessage = Logger.Instance.createLogMessage(eventString, parameters, event_value, interactive_id, interactive_url);
this._instance.LARA.Events.emitLog(logMessage);
- sendToLoggingService(logMessage);
+ if (this._instance.offlineMode) {
+ this._instance.saveLogMessage(logMessage);
+ } else {
+ this._instance.sendToLoggingService(logMessage);
+ }
}
- private static _instance: Logger;
+ public static async syncOfflineLogs(updateCallback: LogSyncUpdateCallback) {
+ const instance = this._instance;
+ if (!instance) return;
+
+ const heartbeat = (message: string) => updateCallback({status: "working", message});
+
+ updateCallback({status: "started"});
+
+ const {activity, classHash, username, runRemoteEndpoint} = instance;
+ if (activity) {
+ heartbeat("Querying logs...");
+ const logs = await dexieStorage.logs.where("activity").equals(activity).toArray();
+
+ heartbeat(`Found ${logs.length} logs`);
+
+ // we want to try to upload the logs in the order they are stored so this a
+ // hack to do iteration on awaits, see https://stackoverflow.com/a/49499491
+ await logs.reduce(async (promise, log: LogMessageWithId) => {
+ await promise;
+
+ // extract the dexie id but don't send it to the log manager
+ const id = log.id as string;
+ delete log.id;
+
+ // update the log entry with the portal data
+ log = {...log, classHash, username, run_remote_endpoint: runRemoteEndpoint };
+
+ try {
+ heartbeat(`Uploading log #${id}`);
+ const logged = await instance.sendToLoggingServiceAndWaitForReply(log);
+
+ if (logged) {
+ heartbeat(`Deleting log #${id}`);
+
+ // delete the log entry
+ await dexieStorage.logs.where("id").equals(id).delete();
+ }
+ } catch (e) {
+ // don't fail here
+ heartbeat(`Failed uploading log #${id}: ${e.toString()}`);
+ }
+ }, Promise.resolve());
+ }
+
+ updateCallback({status: "completed"});
+ }
+
+ private static _instance?: Logger;
public static get Instance() {
if (this._instance) {
@@ -97,7 +156,7 @@ export class Logger {
private LARA: LaraGlobalType;
private username: string;
- private role: string;
+ private role: Role;
private classHash: string;
private session: string;
private appMode: string;
@@ -106,17 +165,19 @@ export class Logger {
private activity: string | undefined;
private activityPage: number;
private runRemoteEndpoint: string;
+ private offlineMode: boolean;
private constructor(LARA: LaraGlobalType,
username: string,
- role: string,
+ role: Role,
classHash: string,
teacherEdition: boolean,
sequence: string | undefined,
sequenceActivityIndex: number,
activity: string | undefined,
activityPage: number,
- runRemoteEndpoint: string) {
+ runRemoteEndpoint: string,
+ offlineMode: boolean) {
this.LARA = LARA;
this.session = uuid();
this.username = username;
@@ -128,6 +189,11 @@ export class Logger {
this.activity = activity;
this.activityPage = activityPage;
this.runRemoteEndpoint = runRemoteEndpoint;
+ this.offlineMode = offlineMode;
+
+ this.logManagerUrl = isProduction(window.location)
+ ? "//cc-log-manager.herokuapp.com/api/logs"
+ : "//cc-log-manager-dev.herokuapp.com/api/logs";
}
private createLogMessage(
@@ -161,14 +227,30 @@ export class Logger {
return logMessage;
}
-}
+ private sendToLoggingService(data: LogMessage) {
+ if (DEBUG_LOGGER) {
+ console.log("Logger#sendToLoggingService sending", JSON.stringify(data), "to", this.logManagerUrl);
+ }
+ const request = new XMLHttpRequest();
+ request.open("POST", this.logManagerUrl, true);
+ request.setRequestHeader("Content-Type", "application/json; charset=UTF-8");
+ request.send(JSON.stringify(data));
+ }
+
+ private async sendToLoggingServiceAndWaitForReply(data: LogMessage) {
+ let logged = false;
+ try {
+ const result = await fetch(this.logManagerUrl, {
+ method: "POST",
+ body: JSON.stringify(data),
+ headers: {"Content-Type": "application/json; charset=UTF-8"}
+ });
+ logged = (result.status === 200) || (result.status === 201);
+ } catch (e) {} // eslint-disable-line no-empty
+ return logged;
+ }
-function sendToLoggingService(data: LogMessage) {
- if (DEBUG_LOGGER) {
- console.log("Logger#sendToLoggingService sending", JSON.stringify(data), "to", logManagerUrl);
+ private saveLogMessage(data: LogMessage) {
+ dexieStorage.logs.put(data);
}
- const request = new XMLHttpRequest();
- request.open("POST", logManagerUrl, true);
- request.setRequestHeader("Content-Type", "application/json; charset=UTF-8");
- request.send(JSON.stringify(data));
}
diff --git a/src/offline-manifest-api.test.ts b/src/offline-manifest-api.test.ts
new file mode 100644
index 00000000..6ccd6a77
--- /dev/null
+++ b/src/offline-manifest-api.test.ts
@@ -0,0 +1,216 @@
+import fetch from "jest-fetch-mock";
+
+import { clearOfflineManifestAuthoringData, clearOfflineManifestAuthoringId,
+ getOfflineManifest, getOfflineManifestAuthoringData, getOfflineManifestAuthoringDownloadJSON,
+ getOfflineManifestAuthoringId, getOfflineManifestUrl, mergeOfflineManifestWithAuthoringData,
+ normalizeAndSortOfflineActivities, OfflineManifestAuthoringData,
+ OfflineManifestAuthoringDataKeyPrefix, OfflineManifestAuthoringIdKey,
+ setOfflineManifestAuthoringData, setOfflineManifestAuthoringId } from "./offline-manifest-api";
+import { OfflineManifest } from "./types";
+
+(window as any).fetch = fetch;
+
+describe("offline manifest api", () => {
+
+ it("handles #getOfflineManifestUrl", () => {
+ expect(getOfflineManifestUrl("foo")).toBe("offline-manifests/foo.json");
+ expect(getOfflineManifestUrl("https://foo")).toBe("https://foo");
+ });
+
+ it("handles #getOfflineManifest", (done) => {
+ const testManifest: OfflineManifest = {
+ name: "Test Manifest",
+ activities: [],
+ cacheList: []
+ };
+ fetch.mockResponse(JSON.stringify(testManifest));
+ const resp = getOfflineManifest("test");
+ expect(fetch.mock.calls[0][0]).toEqual("offline-manifests/test.json");
+ expect(resp).toBeInstanceOf(Promise);
+ resp!.then(data => {
+ expect(data).toEqual(testManifest);
+ done();
+ });
+ });
+
+ // FIXME: This is critical and really should be tested
+ // The commented out parts were from an earlier version that did the
+ // the caching directly in the page by issuing fetch requests
+ // Now the caching happens in the service worker and it sends messages to
+ // the page about its progress
+ it.skip("handles #cacheOfflineManifest", (done) => {
+ // const testManifest: OfflineManifest = {
+ // name: "Test Manifest",
+ // activities: [
+ // {
+ // name: "Activity 1",
+ // resourceUrl: "http://example.com/activity-1-resource-url",
+ // contentUrl: "http://example.com/activity-1-content-url"
+ // },
+ // {
+ // name: "Activity 2",
+ // resourceUrl: "http://example.com/activity-2-resource-url",
+ // contentUrl: "http://example.com/activity-2-content-url"
+ // }
+ // ],
+ // cacheList: [
+ // "http://example.com/cache-list-item-1",
+ // "http://example.com/cache-list-item-2"
+ // ]
+ // };
+ // const onCachingStarted = jest.fn();
+ // const onUrlCached = jest.fn();
+ // const onUrlCacheFailed = jest.fn();
+ // const onCachingFinished = jest.fn();
+ // const resp = cacheOfflineManifest({
+ // offlineManifest: testManifest,
+ // onCachingStarted,
+ // onUrlCached,
+ // onCachingFinished,
+ // onUrlCacheFailed
+ // });
+ // expect(resp).toBeInstanceOf(Promise);
+ // resp!.then(() => {
+ // expect(onCachingStarted).toHaveBeenCalledWith([
+ // "http://example.com/activity-1-content-url",
+ // "http://example.com/activity-2-content-url",
+ // "http://example.com/cache-list-item-1",
+ // "http://example.com/cache-list-item-2"
+ // ]);
+ // expect(onUrlCached).toHaveBeenCalledTimes(4);
+ // expect(onCachingFinished).toHaveBeenCalledTimes(1);
+ // expect(onUrlCacheFailed).not.toHaveBeenCalled();
+ // done();
+ // });
+ });
+
+ it("handles #setOfflineManifestAuthoringId", () => {
+ jest.spyOn(window.localStorage.__proto__, "setItem");
+ setOfflineManifestAuthoringId(undefined);
+ expect(window.localStorage.setItem).not.toHaveBeenCalled();
+ setOfflineManifestAuthoringId("test");
+ expect(window.localStorage.setItem).toHaveBeenCalledWith(OfflineManifestAuthoringIdKey, "test");
+ });
+
+ it("handles #clearOfflineManifestAuthoringId", () => {
+ jest.spyOn(window.localStorage.__proto__, "removeItem");
+ clearOfflineManifestAuthoringId();
+ expect(window.localStorage.removeItem).toHaveBeenCalledWith(OfflineManifestAuthoringIdKey);
+ });
+
+ it("handles #getOfflineManifestAuthoringId", () => {
+ jest.spyOn(window.localStorage.__proto__, "getItem");
+ getOfflineManifestAuthoringId();
+ expect(window.localStorage.getItem).toHaveBeenCalledWith(OfflineManifestAuthoringIdKey);
+ });
+
+ it("handles #getOfflineManifestAuthoringData", () => {
+ jest.spyOn(window.localStorage.__proto__, "getItem");
+ getOfflineManifestAuthoringData("test");
+ expect(window.localStorage.getItem).toHaveBeenCalledWith(`${OfflineManifestAuthoringDataKeyPrefix}:test`);
+ });
+
+ it("handles #setOfflineManifestAuthoringData", () => {
+ const data: OfflineManifestAuthoringData = {activities: [], cacheList: []};
+ jest.spyOn(window.localStorage.__proto__, "setItem");
+ setOfflineManifestAuthoringData("test", data);
+ expect(window.localStorage.setItem).toHaveBeenCalledWith(`${OfflineManifestAuthoringDataKeyPrefix}:test`, JSON.stringify(data));
+ });
+
+ it("handles #clearOfflineManifestAuthoringData", () => {
+ jest.spyOn(window.localStorage.__proto__, "removeItem");
+ clearOfflineManifestAuthoringData("test");
+ expect(window.localStorage.removeItem).toHaveBeenCalledWith(`${OfflineManifestAuthoringDataKeyPrefix}:test`);
+ });
+
+ it("handles #getOfflineManifestAuthoringDownloadJSON", () => {
+ const data: OfflineManifestAuthoringData = {activities: [], cacheList: []};
+ expect(getOfflineManifestAuthoringDownloadJSON("test", data)).toEqual({name: "test", activities: [], cacheList: []});
+ });
+
+ it("handles #mergeOfflineManifestWithAuthoringData", () => {
+ const testManifest: OfflineManifest = {
+ name: "Test Manifest",
+ activities: [
+ {
+ name: "Activity 1",
+ resourceUrl: "http://example.com/activity-1-resource-url",
+ contentUrl: "http://example.com/activity-1-content-url"
+ },
+ {
+ name: "Activity 2",
+ resourceUrl: "http://example.com/activity-2-resource-url",
+ contentUrl: "http://example.com/activity-2-content-url"
+ }
+ ],
+ cacheList: [
+ "http://example.com/cache-list-item-1",
+ "http://example.com/cache-list-item-2"
+ ]
+ };
+ const authoringData: OfflineManifestAuthoringData = {
+ activities: [
+ {
+ name: "Activity 3",
+ resourceUrl: "http://example.com/activity-3-resource-url",
+ contentUrl: "http://example.com/activity-3-content-url"
+ }
+ ],
+ cacheList: [
+ "http://example.com/cache-list-item-3",
+ "http://example.com/cache-list-item-4"
+ ]
+ };
+ expect(mergeOfflineManifestWithAuthoringData(testManifest, authoringData)).toEqual({
+ activities: [
+ {
+ name: "Activity 3",
+ resourceUrl: "http://example.com/activity-3-resource-url",
+ contentUrl: "http://example.com/activity-3-content-url"
+ },
+ {
+ name: "Activity 1",
+ resourceUrl: "http://example.com/activity-1-resource-url",
+ contentUrl: "http://example.com/activity-1-content-url"
+ },
+ {
+ name: "Activity 2",
+ resourceUrl: "http://example.com/activity-2-resource-url",
+ contentUrl: "http://example.com/activity-2-content-url"
+ },
+ ],
+ cacheList: [
+ "http://example.com/cache-list-item-3",
+ "http://example.com/cache-list-item-4",
+ "http://example.com/cache-list-item-1",
+ "http://example.com/cache-list-item-2",
+ ]
+ });
+ });
+
+ it("handles #saveOfflineManifestToOfflineActivities", () => {
+ // TODO: add Dexie stubs, example here: https://stackoverflow.com/a/54134903
+ expect(true).toEqual(true);
+ });
+
+ it("handles #normalizeAndSortOfflineActivities", () => {
+ expect(normalizeAndSortOfflineActivities([
+ {name: "Activity 5", resourceUrl: "http://example.com/activity-5-resource-url", contentUrl: "http://example.com/activity-5-context-url", manifestName: "Manifest 3", order: 0},
+ {name: "Activity 2", resourceUrl: "http://example.com/activity-2-resource-url", contentUrl: "http://example.com/activity-2-context-url", manifestName: "Manifest 1", order: 1},
+ {name: "Activity 4", resourceUrl: "http://example.com/activity-4-resource-url", contentUrl: "http://example.com/activity-4-context-url", manifestName: "Manifest 2", order: 1},
+ {name: "Activity 1", resourceUrl: "http://example.com/activity-1-resource-url", contentUrl: "http://example.com/activity-1-context-url", manifestName: "Manifest 1", order: 0},
+ {name: "Activity 3", resourceUrl: "http://example.com/activity-3-resource-url", contentUrl: "http://example.com/activity-3-context-url", manifestName: "Manifest 2", order: 0},
+ ])).toEqual([
+ {name: "Activity 1", resourceUrl: "http://example.com/activity-1-resource-url", contentUrl: "http://example.com/activity-1-context-url", manifestName: "Manifest 1", order: 0},
+ {name: "Activity 2", resourceUrl: "http://example.com/activity-2-resource-url", contentUrl: "http://example.com/activity-2-context-url", manifestName: "Manifest 1", order: 1},
+ {name: "Activity 3", resourceUrl: "http://example.com/activity-3-resource-url", contentUrl: "http://example.com/activity-3-context-url", manifestName: "Manifest 2", order: 0},
+ {name: "Activity 4", resourceUrl: "http://example.com/activity-4-resource-url", contentUrl: "http://example.com/activity-4-context-url", manifestName: "Manifest 2", order: 1},
+ {name: "Activity 5", resourceUrl: "http://example.com/activity-5-resource-url", contentUrl: "http://example.com/activity-5-context-url", manifestName: "Manifest 3", order: 0},
+ ]);
+ });
+
+ it("handles #getOfflineActivities", () => {
+ // TODO: add Dexie stubs, example here: https://stackoverflow.com/a/54134903
+ expect(true).toEqual(true);
+ });
+});
diff --git a/src/offline-manifest-api.ts b/src/offline-manifest-api.ts
new file mode 100644
index 00000000..dbc4140a
--- /dev/null
+++ b/src/offline-manifest-api.ts
@@ -0,0 +1,190 @@
+import { dexieStorage } from "./storage/dexie-storage";
+import { OfflineActivity, OfflineManifest, OfflineManifestActivity } from "./types";
+import { Workbox } from "workbox-window/index";
+
+export interface OfflineManifestAuthoringData {
+ activities: OfflineManifestActivity[];
+ cacheList: string[]
+}
+
+export const getOfflineManifestUrl = (id: string): string => {
+ if (/^\s*https?:\/\//.test(id)) {
+ return id;
+ }
+ return `offline-manifests/${id}.json`;
+};
+
+export const getOfflineManifest = (id: string): Promise => {
+ return new Promise((resolve, reject) => {
+ const url = getOfflineManifestUrl(id);
+ fetch(url)
+ .then(response => {
+ if (response.status !== 200) {
+ reject(`Errored fetching ${url}. Status Code: ${response.status}`);
+ return;
+ }
+ response.json().then(function(data) {
+ resolve(data);
+ });
+ })
+ .catch(function(err) {
+ reject(`Errored fetching ${url}. ${err}`);
+ });
+ });
+};
+
+export interface CacheOfflineManifestOptions {
+ workbox: Workbox;
+ offlineManifest: OfflineManifest;
+ onCachingStarted: (urls: string[]) => void;
+ onUrlCached: (url: string) => void;
+ onUrlCacheFailed: (url: string, err: any) => void;
+ onCachingFinished: () => void;
+}
+
+export interface CacheUrlsOptions {
+ workbox: Workbox;
+ urls: string[];
+ onCachingStarted: (urls: string[]) => void;
+ onUrlCached: (url: string) => void;
+ onUrlCacheFailed: (url: string, err: any) => void;
+ onCachingFinished: () => void;
+}
+
+/*
+ We can't use the built in Workbox CACHE_URLS message because it doesn't provide
+ progress messages.
+ We can't use the built in Workbox messageSW because it only allows a single
+ response on the MessageChannel indicating that it completed.
+*/
+export const cacheUrlsWithProgress = async (options: CacheUrlsOptions) => {
+ const {workbox, urls, onCachingStarted, onUrlCached, onUrlCacheFailed, onCachingFinished} = options;
+
+ onCachingStarted(urls);
+
+ const sw = await workbox.getSW();
+ const messageChannel = new MessageChannel();
+
+ messageChannel.port1.onmessage = (event: MessageEvent) => {
+ // Handle the various messages from the channel
+ if (event.data?.type === "URL_CACHED") {
+ console.log("URL_CACHED", event.data.payload);
+ onUrlCached(event.data.payload?.url);
+ } else if (event.data?.type === "URL_CACHE_FAILED") {
+ console.error("URL_CACHE_FAILED", event.data.payload);
+ onUrlCacheFailed(event.data.payload?.url, event.data.payload?.error);
+ } else if (event.data?.type === "CACHING_FINISHED") {
+ console.log("CACHING_FINISHED");
+ onCachingFinished();
+ // TODO having a promise here that we can resolve could be helpful
+ }
+ };
+
+ sw.postMessage({type: "CACHE_URLS_WITH_PROGRESS", payload: {urlsToCache: urls}},
+ [messageChannel.port2]);
+
+ // We might need to block until complete so the messageChannel doesn't get
+ // garbage collected, but it isn't simple to just do an await here
+ // so maybe we can get by without blocking.
+};
+
+export const cacheOfflineManifest = (options: CacheOfflineManifestOptions) => {
+ const {workbox, offlineManifest, onCachingStarted, onUrlCached, onUrlCacheFailed, onCachingFinished} = options;
+ const urls = offlineManifest.activities.map(a => a.contentUrl).concat(offlineManifest.cacheList);
+ const cacheUrlsOptions = {workbox, urls, onCachingStarted, onUrlCached, onUrlCacheFailed, onCachingFinished};
+ return cacheUrlsWithProgress(cacheUrlsOptions);
+};
+
+export const OfflineManifestAuthoringIdKey = "offlineManifestAuthoringId";
+export const OfflineManifestAuthoringDataKeyPrefix = "offlineManifestAuthoringData:";
+
+export const setOfflineManifestAuthoringId = (value: string | undefined) => {
+ if (value !== undefined) {
+ window.localStorage.setItem(OfflineManifestAuthoringIdKey, value);
+ }
+};
+
+export const clearOfflineManifestAuthoringId = () => {
+ window.localStorage.removeItem(OfflineManifestAuthoringIdKey);
+};
+
+export const getOfflineManifestAuthoringId = (): string|undefined => {
+ return window.localStorage.getItem(OfflineManifestAuthoringIdKey) || undefined;
+};
+
+export const getOfflineManifestAuthoringData = (authoringId: string): OfflineManifestAuthoringData => {
+ try {
+ const key = `${OfflineManifestAuthoringDataKeyPrefix}:${authoringId}`;
+ return JSON.parse(window.localStorage.getItem(key) || "fail");
+ } catch (e) {
+ return ({
+ activities: [],
+ cacheList: []
+ });
+ }
+};
+
+export const setOfflineManifestAuthoringData = (authoringId: string, data: OfflineManifestAuthoringData) => {
+ const key = `${OfflineManifestAuthoringDataKeyPrefix}:${authoringId}`;
+ window.localStorage.setItem(key, JSON.stringify(data));
+};
+
+export const clearOfflineManifestAuthoringData = (authoringId: string) => {
+ const key = `${OfflineManifestAuthoringDataKeyPrefix}:${authoringId}`;
+ window.localStorage.removeItem(key);
+};
+
+export const getOfflineManifestAuthoringDownloadJSON = (name: string, data: OfflineManifestAuthoringData): OfflineManifest => {
+ const {activities, cacheList} = data;
+ return { name, activities, cacheList };
+};
+
+export const mergeOfflineManifestWithAuthoringData = (offlineManifest: OfflineManifest, authoringData: OfflineManifestAuthoringData) => {
+ const {activities, cacheList} = authoringData;
+ offlineManifest.activities.forEach(activity => {
+ // Note: if the contentUrl has changed this won't update it in the manifest
+ // but in that case it seems reasonable that the author will just manually fix it.
+ if (!activities.find(a => a.resourceUrl === activity.resourceUrl)) {
+ activities.push(activity);
+ }
+ });
+ offlineManifest.cacheList.forEach(url => {
+ if (!cacheList.find(item => item === url)) {
+ cacheList.push(url);
+ }
+ });
+ return {activities, cacheList};
+};
+
+export const saveOfflineManifestToOfflineActivities = async (offlineManifest: OfflineManifest) => {
+ const manifestName = offlineManifest.name;
+ const promises = offlineManifest.activities.map(async (offlineManifestActivity, order) => {
+ const {name, resourceUrl, contentUrl} = offlineManifestActivity;
+ const offlineActivity = await dexieStorage.offlineActivities.get({resourceUrl});
+ if (offlineActivity) {
+ await dexieStorage.offlineActivities.update(resourceUrl, {name, resourceUrl, contentUrl, manifestName, order});
+ } else {
+ await dexieStorage.offlineActivities.put({name, resourceUrl, contentUrl, manifestName, order});
+ }
+ });
+ await Promise.all(promises);
+};
+
+export const normalizeAndSortOfflineActivities = (rawList: OfflineActivity[]) => {
+ // ensure older saved offline activities have a defined manifest name and order
+ const normalizedList = rawList.map((item, order) => ({...item, manifestName: item.manifestName ?? "", order: item.order ?? order}));
+ normalizedList.sort((a, b) => {
+ const nameSort = a.manifestName.localeCompare(b.manifestName);
+ if (nameSort === 0) {
+ return a.order - b.order;
+ } else {
+ return nameSort;
+ }
+ });
+ return normalizedList;
+};
+
+export const getOfflineActivities = async () => {
+ const offlineActivities = await dexieStorage.offlineActivities.toArray();
+ return normalizeAndSortOfflineActivities(offlineActivities);
+};
diff --git a/src/portal-api.test.ts b/src/portal-api.test.ts
index 8835be92..b9bc70e7 100644
--- a/src/portal-api.test.ts
+++ b/src/portal-api.test.ts
@@ -1,4 +1,5 @@
-import { firebaseAppName, clearFirebaseAppName } from "./portal-api";
+import { firebaseAppName, clearFirebaseAppName, getToolId, convertPortalUserIdToLoggingUsername } from "./portal-api";
+import { DEFAULT_STUDENT_LOGGING_USERNAME } from "./student-info";
describe("firebaseAppName", () => {
@@ -37,7 +38,7 @@ describe("firebaseAppName", () => {
});
it("returns report-service-dev on localhost url", () => {
- url.href = "http://localhost:8080";
+ url.href = "http://localhost:11000";
expect(firebaseAppName()).toBe("report-service-dev");
});
@@ -49,3 +50,32 @@ describe("firebaseAppName", () => {
});
});
+
+describe("getToolId", () => {
+ const { location } = window;
+ it("returns an id which is a combination of the host and path", () => {
+ delete (window as any).location;
+
+ const mockLocation = {host: "", pathname: ""};
+ (window as any).location = mockLocation;
+
+ mockLocation.host = "www.example.com";
+ mockLocation.pathname = "/foo";
+ expect(getToolId()).toBe("www.example.com/foo");
+
+ mockLocation.host = "www.example.com:8080";
+ mockLocation.pathname = "/bar";
+ expect(getToolId()).toBe("www.example.com:8080/bar");
+
+ (window as any).location = location;
+ });
+});
+
+describe("misc utils", () => {
+
+ it("converts portal user ids to logging usernames", () => {
+ expect(convertPortalUserIdToLoggingUsername("http://example.com/users/1234")).toEqual("1234@example.com");
+ expect(convertPortalUserIdToLoggingUsername("https://example.com/users/1234")).toEqual("1234@example.com");
+ expect(convertPortalUserIdToLoggingUsername("invalid user id")).toEqual(DEFAULT_STUDENT_LOGGING_USERNAME);
+ });
+});
diff --git a/src/portal-api.ts b/src/portal-api.ts
index 42112e2d..2b56a9e5 100644
--- a/src/portal-api.ts
+++ b/src/portal-api.ts
@@ -1,10 +1,11 @@
import jwt from "jsonwebtoken";
import superagent from "superagent";
import { v4 as uuidv4 } from "uuid";
-import { queryValue, setQueryValue } from "./utilities/url-query";
-import { FirebaseAppName } from "./firebase-db";
+import { queryValue, queryValueBoolean, setQueryValue } from "./utilities/url-query";
import { getResourceUrl } from "./lara-api";
-import { getCanonicalHostname, isProductionOrigin } from "./utilities/host-utils";
+import { getCanonicalHostname, getHostnameWithMaybePort, isOfflineHost, isProduction } from "./utilities/host-utils";
+import { FirebaseAppName } from "./storage/firebase-db";
+import { DEFAULT_STUDENT_LOGGING_USERNAME } from "./student-info";
interface PortalClassOffering {
className: string;
@@ -69,7 +70,7 @@ export interface ILTIPartial {
resourceLinkId: string; // offering ID
}
-interface OfferingData {
+export interface OfferingData {
id: number;
activityUrl: string;
rubricUrl: string;
@@ -94,6 +95,8 @@ export interface IPortalData extends ILTIPartial {
rawPortalJWT?: string;
portalJWT?: PortalJWT;
runRemoteEndpoint: string;
+ classInfo?: ClassInfo;
+ loggingUsername: string;
}
export interface IAnonymousPortalData {
@@ -125,7 +128,7 @@ interface PortalStudentJWT extends BasePortalJWT {
offering_id: number;
}
-type PortalJWT = PortalStudentJWT; // eventually may include other user types
+export type PortalJWT = PortalStudentJWT; // eventually may include other user types
interface BasePortalFirebaseJWT {
alg: string;
@@ -232,12 +235,7 @@ export const firebaseAppName = ():FirebaseAppName => {
return _firebaseAppName;
}
- const { origin, pathname } = window.location;
- // According to the spec an empty path like https://activity-player.concord.org
- // will still have a pathname of "/", but just to be safe this checks for the
- // falsey pathname
- if(isProductionOrigin(origin) &&
- (!pathname || pathname === "/")) {
+ if (isProduction(window.location, {allowVersions: false})) {
_firebaseAppName = "report-service-pro";
} else {
_firebaseAppName = "report-service-dev";
@@ -383,13 +381,25 @@ export const getOfferingData = (params: GetOfferingParams) => {
});
};
-export const fetchPortalData = async (): Promise => {
+export const convertPortalUserIdToLoggingUsername = (userId: string) => {
+ const matches = userId.match(/https?:\/\/([^/]+)\/users\/(.+)/i);
+ return matches ? `${matches[2]}@${matches[1]}` : DEFAULT_STUDENT_LOGGING_USERNAME;
+};
+
+interface IFetchPortalDataOpts {
+ includeClassData: boolean
+}
+const fetchPortalDataDefaults: IFetchPortalDataOpts = {
+ includeClassData: true
+};
+export const fetchPortalData = async (opts: IFetchPortalDataOpts = fetchPortalDataDefaults): Promise => {
const bearerToken = queryValue("token");
const basePortalUrl = queryValue("domain");
+ const preview = queryValueBoolean("preview");
if (!bearerToken || !basePortalUrl) {
- throw new Error("No token provided for authentication (must launch from Portal)");
+ return Promise.resolve(anonymousPortalData(preview));
}
const [rawPortalJWT, portalJWT] = await getPortalJWTWithBearerToken(basePortalUrl, bearerToken);
@@ -411,19 +421,17 @@ export const fetchPortalData = async (): Promise => {
const offeringData = await getOfferingData({portalJWT, rawPortalJWT, offeringId});
const [rawFirebaseJWT, firebaseJWT] = await getActivityPlayerFirebaseJWT(basePortalUrl, rawPortalJWT, classInfo.classHash);
- // student data gets saved in different buckets of the DB, the "source," depending on the domain
- // of the activity.
+ // student data gets saved in different buckets of the DB, the "source," depending on
+ // the canonical hostname.
// This works fine, but for testing the activity player, we may want to load data that was previously
- // saved in a different domain (e.g. authoring.concord.org), so we first check for a "url-source"
+ // saved in a different domain (e.g. authoring.concord.org), so we first check for a "sourceKey"
// query parameter.
- const sourceKey = queryValue("report-source") || parseUrl(offeringData.activityUrl.toLowerCase()).hostname;
+ const sourceKey = queryValue("sourceKey") || getCanonicalHostname();
- // for the tool id we want to distinguish activity-player branches, incase this is ever helpful for
- // dealing with mis-matched data when we load data in originally saved on another branch.
- // This is currently unused for the purpose of saving and loading data
- const toolId = window.location.hostname + window.location.pathname;
const fullName = classInfo.students.find(s => s.id.toString() === portalJWT.uid.toString())?.fullName;
+ const loggingUsername = convertPortalUserIdToLoggingUsername(portalJWT.user_id);
+
const rawPortalData: IPortalData = {
type: "authenticated",
offering: offeringData,
@@ -432,7 +440,7 @@ export const fetchPortalData = async (): Promise => {
platformId: firebaseJWT.claims.platform_id,
platformUserId: firebaseJWT.claims.platform_user_id.toString(),
contextId: classInfo.classHash,
- toolId,
+ toolId: getToolId(),
resourceUrl: getResourceUrl(),
fullName,
learnerKey: firebaseJWT.claims.user_type === "learner"
@@ -446,8 +454,10 @@ export const fetchPortalData = async (): Promise => {
sourceKey,
rawFirebaseJWT,
},
- runRemoteEndpoint: firebaseJWT.returnUrl
+ runRemoteEndpoint: firebaseJWT.returnUrl,
+ loggingUsername
};
+ if(opts.includeClassData) { rawPortalData.classInfo = classInfo; }
return rawPortalData;
};
@@ -460,24 +470,32 @@ export const anonymousPortalData = (preview: boolean) => {
} else {
runKey = queryValue("runKey");
if (!runKey) {
- runKey = uuidv4();
- setQueryValue("runKey", runKey);
+ if (isOfflineHost()) {
+ runKey = "offline";
+ // don't update query string with run key in offline mode
+ } else {
+ runKey = uuidv4();
+ setQueryValue("runKey", runKey);
+ }
}
}
- const hostname = window.location.hostname;
- const toolId = hostname + window.location.pathname;
const rawPortalData: IAnonymousPortalData = {
type: "anonymous",
userType: "learner",
runKey,
resourceUrl: getResourceUrl(),
- toolId,
+ toolId: getToolId(),
toolUserId: "anonymous",
database: {
appName: firebaseAppName(),
- sourceKey: getCanonicalHostname()
+ sourceKey: queryValue("sourceKey") || getCanonicalHostname()
}
};
return rawPortalData;
};
+
+// for the tool id we want to distinguish activity-player hosts and branches, incase this is ever helpful for
+// dealing with mis-matched data when we load data in originally saved on another branch.
+// This is currently unused for the purpose of saving and loading data
+export const getToolId = () => getHostnameWithMaybePort() + window.location.pathname;
diff --git a/src/public/glossary-files/alaska.json b/src/public/glossary-files/alaska.json
new file mode 100644
index 00000000..338fa807
--- /dev/null
+++ b/src/public/glossary-files/alaska.json
@@ -0,0 +1,303 @@
+{
+ "enableStudentLanguageSwitching": true,
+ "askForUserDefinition": true,
+ "definitions": [
+ {
+ "word": "weather",
+ "definition": "The condition of the air that surrounds the Earth at a particular time and place.",
+ "image": "https://cc-project-resources.s3.amazonaws.com/precipitatingchange/Glossary/weather.jpg",
+ "imageCaption": "There can be many changes to the day-to-day temperature and precipitation conditions.",
+ "video": "https://cc-project-resources.s3.amazonaws.com/precipitatingchange/videos/weather-movie.mp4",
+ "videoCaption": "The changes in air and water surrounding the Earth form different weather conditions."
+ },
+ {
+ "word": "decomposition",
+ "definition": "Organizing a large amount of information (data) into smaller more manageable parts. ",
+ "image": "https://cc-project-resources.s3.amazonaws.com/precipitatingchange/Kathy%27s%20latest/precipitating-change-visuals/decomposition/decomposition.jpg",
+ "imageCaption": "Breaking it down into smaller parts.",
+ "video": "https://cc-project-resources.s3.amazonaws.com/precipitatingchange/Kathy%27s%20latest/precipitating-change-visuals/decomposition/decomposition.mp4",
+ "videoCaption": "Breaking it down into smaller parts."
+ },
+ {
+ "word": "pattern recognition",
+ "definition": "Recognizing that data or information is repeating in a logical (expected) way.",
+ "image": "https://cc-project-resources.s3.amazonaws.com/precipitatingchange/Glossary/pattern-recognition.jpg",
+ "imageCaption": "Matching similar sets of data or visual information.",
+ "video": "https://cc-project-resources.s3.amazonaws.com/precipitatingchange/videos/PatternRecognition.mp4",
+ "videoCaption": "Matching similar sets of data or visual information."
+ },
+ {
+ "word": "extrapolation",
+ "definition": "Following a pattern beyond the known data points. ",
+ "image": "https://cc-project-resources.s3.amazonaws.com/precipitatingchange/Kathy%27s%20latest/precipitating-change-visuals/extrapolation/exptrapolation.jpg",
+ "imageCaption": "Estimating extension based on existing patterns.",
+ "video": "https://cc-project-resources.s3.amazonaws.com/precipitatingchange/Kathy%27s%20latest/precipitating-change-visuals/extrapolation/extrapolation.mp4",
+ "videoCaption": "Estimating extension based on existing patterns."
+ },
+ {
+ "word": "interpolation",
+ "definition": "Estimating an unknown value based on surrounding information.",
+ "image": "https://cc-project-resources.s3.amazonaws.com/precipitatingchange/Kathy%27s%20latest/precipitating-change-visuals/interpolation/interpolation.jpg",
+ "video": "https://cc-project-resources.s3.amazonaws.com/precipitatingchange/Kathy%27s%20latest/precipitating-change-visuals/interpolation/interpolation.mp4"
+ },
+ {
+ "word": "prediction",
+ "definition": "Forecast based on evidence about a future event.",
+ "image": "https://cc-project-resources.s3.amazonaws.com/precipitatingchange/Kathy%27s%20latest/precipitating-change-visuals/prediction/prediction-sm.jpg",
+ "imageCaption": "A prediction or forecast can vary about possible future weather.",
+ "video": "https://cc-project-resources.s3.amazonaws.com/precipitatingchange/Kathy%27s%20latest/precipitating-change-visuals/prediction/prediction.mp4",
+ "videoCaption": "This prediction or forecast is a guess about the future weather. The guess is based on prior facts or evidence."
+ },
+ {
+ "word": "front",
+ "definition": "The area between two colliding air masses of different temperatures that result in a change in weather. ",
+ "image": "https://cc-project-resources.s3.amazonaws.com/precipitatingchange/Kathy%27s%20latest/precipitating-change-visuals/front/front.jpg",
+ "imageCaption": "A map of different air masses colliding.",
+ "video": "https://cc-project-resources.s3.amazonaws.com/precipitatingchange/Kathy%27s%20latest/precipitating-change-visuals/front/front.mp4",
+ "videoCaption": "Radar of moving air masses of different temperatures and moisture content."
+ },
+ {
+ "word": "precipitation",
+ "definition": "Any product of the condensation of water vapor in the atmosphere that falls to the ground due to gravity such as rain, snow, sleet, or hail.",
+ "image": "https://cc-project-resources.s3.amazonaws.com/precipitatingchange/Glossary/precipitation.jpg",
+ "imageCaption": "Precipitation in the form of snow falling from the sky. ",
+ "video": "https://cc-project-resources.s3.amazonaws.com/precipitatingchange/videos/precipitation_snow.mp4",
+ "videoCaption": "Precipitation in the form of snow falling from the sky. "
+ },
+ {
+ "word": "wind direction",
+ "definition": "Wind direction is described by using the direction that the wind came from. For example, a southerly wind would blow from the south to the north. Wind direction is measured a number of ways including weather vanes, flags, and windsocks. ",
+ "image": "https://cc-project-resources.s3.amazonaws.com/precipitatingchange/Glossary/wind-direction.jpg",
+ "imageCaption": "Wind socks are used at airports to determine wind direction.",
+ "video": "https://cc-project-resources.s3.amazonaws.com/precipitatingchange/videos/WindDirection.mp4",
+ "videoCaption": "Wind socks are used at airports to determine wind direction."
+ },
+ {
+ "word": "air moisture",
+ "definition": "Air moisture amount or content of water in the air.",
+ "image": "https://cc-project-resources.s3.amazonaws.com/precipitatingchange/Glossary/air_moisture_fog-high.jpg",
+ "imageCaption": "Air moisture can impact land cover.",
+ "video": "https://cc-project-resources.s3.amazonaws.com/precipitatingchange/videos/moisture-amount.mp4",
+ "videoCaption": "During rain or snow storms there is a lot of moisture in the air."
+ },
+ {
+ "word": "aggregation",
+ "definition": "Describes the data collection and organization process you use to better understand the topic. ",
+ "image": "https://cc-project-resources.s3.amazonaws.com/precipitatingchange/Glossary/aggregation.jpg",
+ "imageCaption": "Collecting and grouping data.",
+ "video": "https://cc-project-resources.s3.amazonaws.com/precipitatingchange/videos/Aggregation.mp4",
+ "videoCaption": "Collecting and grouping data."
+ },
+ {
+ "word": "abstraction",
+ "definition": "Simplifying data to make it easier to interpret and find patterns.",
+ "image": "https://cc-project-resources.s3.amazonaws.com/precipitatingchange/Glossary/abstraction.jpg",
+ "imageCaption": "Finding a trend in data.",
+ "video": "https://cc-project-resources.s3.amazonaws.com/precipitatingchange/videos/AbstractionMovie.mp4",
+ "videoCaption": "Finding a trend in data."
+ }
+ ],
+ "autoShowMediaInPopup": true,
+ "translations": {
+ "mr": {
+ "weather.word": "",
+ "weather.word_mp3_url": "",
+ "weather.definition": "",
+ "weather.definition_mp3_url": "",
+ "weather.image_caption": "Gits'anxitodoł",
+ "weather.image_caption_mp3_url": "https://cc-project-resources.s3.amazonaws.com/precipitatingchange/audio/Athabaskan/Gitsanxitodo_The_weather_is_going_to_change.mp3",
+ "weather.video_caption": "Ttheting ndadz dixet'a?",
+ "weather.video_caption_mp3_url": "https://cc-project-resources.s3.amazonaws.com/precipitatingchange/audio/Athabaskan/Tthetingndadzdixeta_What_is_it_doing_outside.mp3",
+ "decomposition.word": "",
+ "decomposition.word_mp3_url": "",
+ "decomposition.definition": "",
+ "decomposition.definition_mp3_url": "",
+ "decomposition.image_caption": "",
+ "decomposition.image_caption_mp3_url": "",
+ "decomposition.video_caption": "",
+ "decomposition.video_caption_mp3_url": "",
+ "pattern recognition.word": "",
+ "pattern recognition.word_mp3_url": "",
+ "pattern recognition.definition": "",
+ "pattern recognition.definition_mp3_url": "",
+ "pattern recognition.image_caption": "Ghoghoy yigidighoy",
+ "pattern recognition.image_caption_mp3_url": "https://cc-project-resources.s3.amazonaws.com/precipitatingchange/audio/Athabaskan/Ghoghoyyigidighoy-pattern.mp3",
+ "pattern recognition.video_caption": "Gon ghoghoy yigidighoy axa ditast'eł.",
+ "pattern recognition.video_caption_mp3_url": "https://cc-project-resources.s3.amazonaws.com/precipitatingchange/audio/Athabaskan/Gonghoghoyyigidigh_I_am_going_to_use_this_pattern.mp3",
+ "extrapolation.word": "",
+ "extrapolation.word_mp3_url": "",
+ "extrapolation.definition": "",
+ "extrapolation.definition_mp3_url": "",
+ "extrapolation.image_caption": "Ndadz chenh",
+ "extrapolation.image_caption_mp3_url": "https://cc-project-resources.s3.amazonaws.com/precipitatingchange/audio/Athabaskan/Ndadzchenh_Whats_next.mp3",
+ "extrapolation.video_caption": "Ndadz chenh",
+ "extrapolation.video_caption_mp3_url": "https://cc-project-resources.s3.amazonaws.com/precipitatingchange/audio/Athabaskan/Ndadzchenh_Whats_next.mp3",
+ "interpolation.word": "",
+ "interpolation.word_mp3_url": "",
+ "interpolation.definition": "",
+ "interpolation.definition_mp3_url": "",
+ "interpolation.image_caption": "Vitotuq, dotuq",
+ "interpolation.image_caption_mp3_url": "https://cc-project-resources.s3.amazonaws.com/precipitatingchange/audio/Athabaskan/Vitotuq_between_middle.mp3",
+ "interpolation.video_caption": "Vitotuq, dotuq",
+ "interpolation.video_caption_mp3_url": "https://cc-project-resources.s3.amazonaws.com/precipitatingchange/audio/Atthabaskan/Vitotuq_between_middle.mp3",
+ "prediction.word": "",
+ "prediction.word_mp3_url": "",
+ "prediction.definition": "",
+ "prediction.definition_mp3_url": "",
+ "prediction.image_caption": "Ndadz chenh",
+ "prediction.image_caption_mp3_url": "https://cc-project-resources.s3.amazonaws.com/precipitatingchange/audio/Athabaskan/Ndadzchenh_Whats_next.mp3",
+ "prediction.video_caption": "Ndadz chenh",
+ "prediction.video_caption_mp3_url": "https://cc-project-resources.s3.amazonaws.com/precipitatingchange/audio/Athabaskan/Ndadzchenh_Whats_next.mp3",
+ "front.word": "",
+ "front.word_mp3_url": "",
+ "front.definition": "",
+ "front.definition_mp3_url": "",
+ "front.image_caption": "",
+ "front.image_caption_mp3_url": "",
+ "front.video_caption": "",
+ "front.video_caption_mp3_url": "",
+ "precipitation.word": "",
+ "precipitation.word_mp3_url": "",
+ "precipitation.definition": "",
+ "precipitation.definition_mp3_url": "",
+ "precipitation.image_caption": "Xiyh tux iłyoth.",
+ "precipitation.image_caption_mp3_url": "https://cc-project-resources.s3.amazonaws.com/precipitatingchange/audio/Athabaskan/Xiyhtuxiyoth_It_snows_during_the_winter.mp3",
+ "precipitation.video_caption": "Xiyh tux iłyoth.",
+ "precipitation.video_caption_mp3_url": "https://cc-project-resources.s3.amazonaws.com/precipitatingchange/audio/Athabaskan/Xiyhtuxiyoth_It_snows_during_the_winter.mp3",
+ "wind direction.word": "",
+ "wind direction.word_mp3_url": "",
+ "wind direction.definition": "",
+ "wind direction.definition_mp3_url": "https://cc-project-resources.s3.amazonaws.com/precipitatingchange/audio/Athabaskan/Xidetriyh_it_is_windy.mp3",
+ "wind direction.image_caption": "Xidetr'iyh",
+ "wind direction.image_caption_mp3_url": "https://cc-project-resources.s3.amazonaws.com/precipitatingchange/audio/Athabaskan/Doodzxantidhitriyh_An_East_Wind_is_starting_to_blow.mp3",
+ "wind direction.video_caption": "Do'odz xantidhitr'iyh.",
+ "wind direction.video_caption_mp3_url": "",
+ "air moisture.word": "",
+ "air moisture.word_mp3_url": "",
+ "air moisture.definition": "",
+ "air moisture.definition_mp3_url": "",
+ "air moisture.image_caption": "",
+ "air moisture.image_caption_mp3_url": "",
+ "air moisture.video_caption": "",
+ "air moisture.video_caption_mp3_url": "",
+ "aggregation.word": "",
+ "aggregation.word_mp3_url": "",
+ "aggregation.definition": "",
+ "aggregation.definition_mp3_url": "",
+ "aggregation.image_caption": "",
+ "aggregation.image_caption_mp3_url": "",
+ "aggregation.video_caption": "",
+ "aggregation.video_caption_mp3_url": "",
+ "abstraction.word": "",
+ "abstraction.word_mp3_url": "",
+ "abstraction.definition": "",
+ "abstraction.definition_mp3_url": "",
+ "abstraction.image_caption": "",
+ "abstraction.image_caption_mp3_url": "",
+ "abstraction.video_caption": "",
+ "abstraction.video_caption_mp3_url": "",
+ "main_prompt_mp3_url": "",
+ "write_definition_mp3_url": ""
+ },
+ "gv": {
+ "weather.word": "",
+ "weather.word_mp3_url": "",
+ "weather.definition": "",
+ "weather.definition_mp3_url": "",
+ "weather.image_caption": "Qaillun ella ayuqa unuamek? [What is the weather like today?]",
+ "weather.image_caption_mp3_url": "",
+ "weather.video_caption": "Amirlirtuq [It is cloudy.]",
+ "weather.video_caption_mp3_url": "",
+ "decomposition.word": "",
+ "decomposition.word_mp3_url": "",
+ "decomposition.definition": "",
+ "decomposition.definition_mp3_url": "",
+ "decomposition.image_caption": "itume [to break into pieces]",
+ "decomposition.image_caption_mp3_url": "",
+ "decomposition.video_caption": "itume [to break into pieces]",
+ "decomposition.video_caption_mp3_url": "",
+ "pattern recognition.word": "",
+ "pattern recognition.word_mp3_url": "",
+ "pattern recognition.definition": "",
+ "pattern recognition.definition_mp3_url": "",
+ "pattern recognition.image_caption": "",
+ "pattern recognition.image_caption_mp3_url": "",
+ "pattern recognition.video_caption": "",
+ "pattern recognition.video_caption_mp3_url": "",
+ "extrapolation.word": "",
+ "extrapolation.word_mp3_url": "",
+ "extrapolation.definition": "",
+ "extrapolation.definition_mp3_url": "",
+ "extrapolation.image_caption": "",
+ "extrapolation.image_caption_mp3_url": "",
+ "extrapolation.video_caption": "",
+ "extrapolation.video_caption_mp3_url": "",
+ "interpolation.word": "",
+ "interpolation.word_mp3_url": "",
+ "interpolation.definition": "",
+ "interpolation.definition_mp3_url": "",
+ "interpolation.image_caption": "akuliq [middle, area between]",
+ "interpolation.image_caption_mp3_url": "",
+ "interpolation.video_caption": "akuliq [middle, area between]",
+ "interpolation.video_caption_mp3_url": "",
+ "prediction.word": "",
+ "prediction.word_mp3_url": "",
+ "prediction.definition": "",
+ "prediction.definition_mp3_url": "",
+ "prediction.image_caption": "ellaliuryaraq [checking the weather, weather forecasting]",
+ "prediction.image_caption_mp3_url": "",
+ "prediction.video_caption": "ellaliuryaraq [checking the weather, weather forecasting]",
+ "prediction.video_caption_mp3_url": "",
+ "front.word": "",
+ "front.word_mp3_url": "",
+ "front.definition": "",
+ "front.definition_mp3_url": "",
+ "front.image_caption": "anuqem tungai ellaliuryaraq-llu [weather directions]",
+ "front.image_caption_mp3_url": "",
+ "front.video_caption": "anuqem tungai ellaliuryaraq-llu [weather directions]",
+ "front.video_caption_mp3_url": "",
+ "precipitation.word": "",
+ "precipitation.word_mp3_url": "",
+ "precipitation.definition": "",
+ "precipitation.definition_mp3_url": "",
+ "precipitation.image_caption": "aniu [snow on ground]",
+ "precipitation.image_caption_mp3_url": "",
+ "precipitation.video_caption": "natquigem akuliini [in the midst of the snow]",
+ "precipitation.video_caption_mp3_url": "",
+ "wind direction.word": "",
+ "wind direction.word_mp3_url": "",
+ "wind direction.definition": "",
+ "wind direction.definition_mp3_url": "",
+ "wind direction.image_caption": "anuqessuun [any device used in the wind, such as a windsock]",
+ "wind direction.image_caption_mp3_url": "",
+ "wind direction.video_caption": "anuqessuun [any device used in the wind, such as a windsock]",
+ "wind direction.video_caption_mp3_url": "",
+ "air moisture.word": "",
+ "air moisture.word_mp3_url": "",
+ "air moisture.definition": "",
+ "air moisture.definition_mp3_url": "",
+ "air moisture.image_caption": "",
+ "air moisture.image_caption_mp3_url": "",
+ "air moisture.video_caption": "",
+ "air moisture.video_caption_mp3_url": "",
+ "aggregation.word": "",
+ "aggregation.word_mp3_url": "",
+ "aggregation.definition": "",
+ "aggregation.definition_mp3_url": "",
+ "aggregation.image_caption": "",
+ "aggregation.image_caption_mp3_url": "",
+ "aggregation.video_caption": "",
+ "aggregation.video_caption_mp3_url": "",
+ "abstraction.word": "",
+ "abstraction.word_mp3_url": "",
+ "abstraction.definition": "",
+ "abstraction.definition_mp3_url": "",
+ "abstraction.image_caption": "",
+ "abstraction.image_caption_mp3_url": "",
+ "abstraction.video_caption": "",
+ "abstraction.video_caption_mp3_url": "",
+ "main_prompt_mp3_url": "",
+ "write_definition_mp3_url": ""
+ }
+ }
+}
diff --git a/src/public/icons/android-icon-192x192.png b/src/public/icons/android-icon-192x192.png
new file mode 100644
index 00000000..21f4db89
Binary files /dev/null and b/src/public/icons/android-icon-192x192.png differ
diff --git a/src/public/icons/apple-icon-114x114.png b/src/public/icons/apple-icon-114x114.png
new file mode 100644
index 00000000..cbd73262
Binary files /dev/null and b/src/public/icons/apple-icon-114x114.png differ
diff --git a/src/public/icons/apple-icon-120x120.png b/src/public/icons/apple-icon-120x120.png
new file mode 100644
index 00000000..113a3760
Binary files /dev/null and b/src/public/icons/apple-icon-120x120.png differ
diff --git a/src/public/icons/apple-icon-144x144.png b/src/public/icons/apple-icon-144x144.png
new file mode 100644
index 00000000..dc7c1048
Binary files /dev/null and b/src/public/icons/apple-icon-144x144.png differ
diff --git a/src/public/icons/apple-icon-152x152.png b/src/public/icons/apple-icon-152x152.png
new file mode 100644
index 00000000..31a741e1
Binary files /dev/null and b/src/public/icons/apple-icon-152x152.png differ
diff --git a/src/public/icons/apple-icon-180x180.png b/src/public/icons/apple-icon-180x180.png
new file mode 100644
index 00000000..02c2741e
Binary files /dev/null and b/src/public/icons/apple-icon-180x180.png differ
diff --git a/src/public/icons/apple-icon-57x57.png b/src/public/icons/apple-icon-57x57.png
new file mode 100644
index 00000000..4d7aa6bd
Binary files /dev/null and b/src/public/icons/apple-icon-57x57.png differ
diff --git a/src/public/icons/apple-icon-60x60.png b/src/public/icons/apple-icon-60x60.png
new file mode 100644
index 00000000..1912d33e
Binary files /dev/null and b/src/public/icons/apple-icon-60x60.png differ
diff --git a/src/public/icons/apple-icon-72x72.png b/src/public/icons/apple-icon-72x72.png
new file mode 100644
index 00000000..1f8b8950
Binary files /dev/null and b/src/public/icons/apple-icon-72x72.png differ
diff --git a/src/public/icons/apple-icon-76x76.png b/src/public/icons/apple-icon-76x76.png
new file mode 100644
index 00000000..4995e4de
Binary files /dev/null and b/src/public/icons/apple-icon-76x76.png differ
diff --git a/src/public/icons/favicon-16x16.png b/src/public/icons/favicon-16x16.png
new file mode 100644
index 00000000..0ad1bdb1
Binary files /dev/null and b/src/public/icons/favicon-16x16.png differ
diff --git a/src/public/icons/favicon-32x32.png b/src/public/icons/favicon-32x32.png
new file mode 100644
index 00000000..615a9b75
Binary files /dev/null and b/src/public/icons/favicon-32x32.png differ
diff --git a/src/public/icons/favicon-96x96.png b/src/public/icons/favicon-96x96.png
new file mode 100644
index 00000000..dd5bde12
Binary files /dev/null and b/src/public/icons/favicon-96x96.png differ
diff --git a/src/public/manifest.json b/src/public/manifest.json
new file mode 100644
index 00000000..3eab0526
--- /dev/null
+++ b/src/public/manifest.json
@@ -0,0 +1,80 @@
+{
+ "short_name": "Activity Player",
+ "name": "Activity Player",
+ "lang": "en",
+ "description": "Concord Consortium Activity Player",
+ "start_url": "index.html",
+ "background_color": "#ea6d2f",
+ "theme_color": "#2da343",
+ "dir": "ltr",
+ "display": "standalone",
+ "orientation": "any",
+ "icons": [
+ {
+ "src": "icons/android-icon-192x192.png",
+ "type": "image/png",
+ "sizes": "192x192"
+ },
+ {
+ "src": "icons/apple-icon-180x180.png",
+ "type": "image/png",
+ "sizes": "180x180"
+ },
+ {
+ "src": "icons/apple-icon-152x152.png",
+ "type": "image/png",
+ "sizes": "152x152"
+ },
+ {
+ "src": "icons/apple-icon-144x144.png",
+ "type": "image/png",
+ "sizes": "144x144"
+ },
+ {
+ "src": "icons/apple-icon-120x120.png",
+ "type": "image/png",
+ "sizes": "120x120"
+ },
+ {
+ "src": "icons/apple-icon-114x114.png",
+ "type": "image/png",
+ "sizes": "114x114"
+ },
+ {
+ "src": "icons/favicon-96x96.png",
+ "type": "image/png",
+ "sizes": "96x96"
+ },
+ {
+ "src": "icons/apple-icon-76x76.png",
+ "type": "image/png",
+ "sizes": "76x76"
+ },
+ {
+ "src": "icons/apple-icon-72x72.png",
+ "type": "image/png",
+ "sizes": "72x72"
+ },
+ {
+ "src": "icons/apple-icon-60x60.png",
+ "type": "image/png",
+ "sizes": "60x60"
+ },
+ {
+ "src": "icons/apple-icon-57x57.png",
+ "type": "image/png",
+ "sizes": "57x57"
+ },
+ {
+ "src": "icons/favicon-32x32.png",
+ "type": "image/png",
+ "sizes": "32x32"
+ },
+ {
+ "src": "icons/favicon-16x16.png",
+ "type": "image/png",
+ "sizes": "16x16"
+ }
+ ],
+ "prefer_related_applications": false
+}
\ No newline at end of file
diff --git a/src/public/offline-activities/glossary-test-v1.json b/src/public/offline-activities/glossary-test-v1.json
new file mode 100644
index 00000000..9729f945
--- /dev/null
+++ b/src/public/offline-activities/glossary-test-v1.json
@@ -0,0 +1,85 @@
+{
+ "description": "",
+ "editor_mode": 0,
+ "layout": 0,
+ "name": "Simple AP with Glossary (master)",
+ "notes": "",
+ "project_id": null,
+ "related": "",
+ "runtime": "Activity Player",
+ "show_submit_button": true,
+ "student_report_enabled": true,
+ "thumbnail_url": "",
+ "time_to_complete": null,
+ "version": 1,
+ "theme_name": null,
+ "pages": [
+ {
+ "additional_sections": {},
+ "embeddable_display_mode": "stacked",
+ "id": 308544,
+ "is_completion": false,
+ "is_hidden": false,
+ "layout": "l-full-width",
+ "name": null,
+ "position": 1,
+ "show_header": false,
+ "show_info_assessment": false,
+ "show_interactive": true,
+ "show_sidebar": false,
+ "sidebar": null,
+ "sidebar_title": "Did you know?",
+ "toggle_info_assessment": false,
+ "embeddables": [
+ {
+ "embeddable": {
+ "content": "\r\n\r\n
",
+ "is_callout": false,
+ "is_full_width": true,
+ "is_hidden": false,
+ "name": "",
+ "type": "Embeddable::Xhtml",
+ "ref_id": "147889-Embeddable::Xhtml"
+ },
+ "section": "header_block"
+ },
+ {
+ "embeddable": {
+ "name": "",
+ "url_fragment": null,
+ "authored_state": "{\"version\":1,\"questionType\":\"multiple_choice\",\"multipleAnswers\":false,\"layout\":\"vertical\",\"choices\":[{\"id\":\"1\",\"content\":\"Alex\",\"correct\":false},{\"id\":\"2\",\"content\":\"Delana\",\"correct\":false},{\"id\":\"3\",\"content\":\"Kalin\",\"correct\":false},{\"content\":\"Sage\",\"correct\":false,\"id\":\"48ed2c41-2f41-4d5e-b70c-89cc42e2eb72\"}],\"prompt\":\"\r\n\r\n
",
+ "is_callout": false,
+ "is_full_width": true,
+ "is_hidden": false,
+ "name": "",
+ "type": "Embeddable::Xhtml",
+ "ref_id": "147795-Embeddable::Xhtml"
+ },
+ "section": "header_block"
+ },
+ {
+ "embeddable": {
+ "name": "",
+ "url_fragment": null,
+ "authored_state": "{\"version\":1,\"questionType\":\"multiple_choice\",\"multipleAnswers\":false,\"layout\":\"vertical\",\"choices\":[{\"id\":\"1\",\"content\":\"Alex\",\"correct\":false},{\"id\":\"2\",\"content\":\"Delana\",\"correct\":false},{\"id\":\"3\",\"content\":\"Kalin\",\"correct\":false},{\"content\":\"Sage\",\"correct\":false,\"id\":\"48ed2c41-2f41-4d5e-b70c-89cc42e2eb72\"}],\"prompt\":\"\r\n\r\n
",
+ "is_callout": false,
+ "is_full_width": true,
+ "is_hidden": false,
+ "name": "",
+ "type": "Embeddable::Xhtml",
+ "ref_id": "147898-Embeddable::Xhtml"
+ },
+ "section": "header_block"
+ },
+ {
+ "embeddable": {
+ "name": "",
+ "url_fragment": null,
+ "authored_state": "{\"version\":1,\"questionType\":\"multiple_choice\",\"multipleAnswers\":false,\"layout\":\"vertical\",\"choices\":[{\"id\":\"1\",\"content\":\"Alex\",\"correct\":false},{\"id\":\"2\",\"content\":\"Delana\",\"correct\":false},{\"id\":\"3\",\"content\":\"Kalin\",\"correct\":false},{\"content\":\"Sage\",\"correct\":false,\"id\":\"9d08acd6-bc42-4b6d-9c82-6a37abc8cd3e\"}]}",
+ "is_hidden": false,
+ "is_full_width": true,
+ "show_in_featured_question_report": true,
+ "inherit_aspect_ratio_method": true,
+ "custom_aspect_ratio_method": "DEFAULT",
+ "inherit_native_width": true,
+ "custom_native_width": 576,
+ "inherit_native_height": true,
+ "custom_native_height": 435,
+ "inherit_click_to_play": true,
+ "custom_click_to_play": false,
+ "inherit_full_window": true,
+ "custom_full_window": false,
+ "inherit_click_to_play_prompt": true,
+ "custom_click_to_play_prompt": null,
+ "inherit_image_url": true,
+ "custom_image_url": null,
+ "library_interactive": {
+ "hash": "98f3d10aa7f2fce6bdeb0ecda339fa56dc80b37c",
+ "data": {
+ "aspect_ratio_method": "DEFAULT",
+ "authoring_guidance": "",
+ "base_url": "https://models-resources.concord.org/question-interactives/version/v1.2.0-pre.1/multiple-choice/",
+ "click_to_play": false,
+ "click_to_play_prompt": null,
+ "description": "",
+ "enable_learner_state": true,
+ "full_window": false,
+ "has_report_url": false,
+ "image_url": null,
+ "name": "Multiple Choice",
+ "native_height": 435,
+ "native_width": 576,
+ "no_snapshots": false,
+ "show_delete_data_button": false,
+ "thumbnail_url": "",
+ "customizable": true,
+ "authorable": true
+ }
+ },
+ "type": "ManagedInteractive",
+ "ref_id": "1688-ManagedInteractive",
+ "linked_interactives": []
+ },
+ "section": null
+ },
+ {
+ "embeddable": {
+ "name": "",
+ "url_fragment": null,
+ "authored_state": "{\"version\":1,\"questionType\":\"open_response\",\"prompt\":\"\r\n\r\n
",
+ "is_callout": false,
+ "is_full_width": true,
+ "is_hidden": false,
+ "name": "",
+ "type": "Embeddable::Xhtml",
+ "ref_id": "147895-Embeddable::Xhtml"
+ },
+ "section": "header_block"
+ },
+ {
+ "embeddable": {
+ "name": "",
+ "url_fragment": null,
+ "authored_state": "{\"version\":1,\"questionType\":\"multiple_choice\",\"multipleAnswers\":false,\"layout\":\"vertical\",\"choices\":[{\"id\":\"1\",\"content\":\"Alex\",\"correct\":false},{\"id\":\"2\",\"content\":\"Delana\",\"correct\":false},{\"id\":\"3\",\"content\":\"Kalin\",\"correct\":false},{\"content\":\"Sage\",\"correct\":false,\"id\":\"9d08acd6-bc42-4b6d-9c82-6a37abc8cd3e\"}]}",
+ "is_hidden": false,
+ "is_full_width": true,
+ "show_in_featured_question_report": true,
+ "inherit_aspect_ratio_method": true,
+ "custom_aspect_ratio_method": "DEFAULT",
+ "inherit_native_width": true,
+ "custom_native_width": 576,
+ "inherit_native_height": true,
+ "custom_native_height": 435,
+ "inherit_click_to_play": true,
+ "custom_click_to_play": false,
+ "inherit_full_window": true,
+ "custom_full_window": false,
+ "inherit_click_to_play_prompt": true,
+ "custom_click_to_play_prompt": null,
+ "inherit_image_url": true,
+ "custom_image_url": null,
+ "library_interactive": {
+ "hash": "98f3d10aa7f2fce6bdeb0ecda339fa56dc80b37c",
+ "data": {
+ "aspect_ratio_method": "DEFAULT",
+ "authoring_guidance": "",
+ "base_url": "https://models-resources.concord.org/question-interactives/version/v1.2.0-pre.1/multiple-choice/",
+ "click_to_play": false,
+ "click_to_play_prompt": null,
+ "description": "",
+ "enable_learner_state": true,
+ "full_window": false,
+ "has_report_url": false,
+ "image_url": null,
+ "name": "Multiple Choice",
+ "native_height": 435,
+ "native_width": 576,
+ "no_snapshots": false,
+ "show_delete_data_button": false,
+ "thumbnail_url": "",
+ "customizable": true,
+ "authorable": true
+ }
+ },
+ "type": "ManagedInteractive",
+ "ref_id": "1687-ManagedInteractive",
+ "linked_interactives": []
+ },
+ "section": null
+ },
+ {
+ "embeddable": {
+ "name": "",
+ "url_fragment": null,
+ "authored_state": "{\"version\":1,\"questionType\":\"open_response\",\"prompt\":\"\r\n\r\n
",
+ "is_callout": false,
+ "is_full_width": true,
+ "is_hidden": false,
+ "name": "",
+ "type": "Embeddable::Xhtml",
+ "ref_id": "147904-Embeddable::Xhtml"
+ },
+ "section": "header_block"
+ },
+ {
+ "embeddable": {
+ "name": "",
+ "url_fragment": null,
+ "authored_state": "{\"version\":1,\"questionType\":\"multiple_choice\",\"multipleAnswers\":false,\"layout\":\"vertical\",\"choices\":[{\"id\":\"1\",\"content\":\"Alex\",\"correct\":false},{\"id\":\"2\",\"content\":\"Delana\",\"correct\":false},{\"id\":\"3\",\"content\":\"Kalin\",\"correct\":false},{\"content\":\"Sage\",\"correct\":false,\"id\":\"6bd7ac18-6b07-4996-9e4b-199430b43e0c\"}]}",
+ "is_hidden": false,
+ "is_full_width": true,
+ "show_in_featured_question_report": true,
+ "inherit_aspect_ratio_method": true,
+ "custom_aspect_ratio_method": "DEFAULT",
+ "inherit_native_width": true,
+ "custom_native_width": 576,
+ "inherit_native_height": true,
+ "custom_native_height": 435,
+ "inherit_click_to_play": true,
+ "custom_click_to_play": false,
+ "inherit_full_window": true,
+ "custom_full_window": false,
+ "inherit_click_to_play_prompt": true,
+ "custom_click_to_play_prompt": null,
+ "inherit_image_url": true,
+ "custom_image_url": null,
+ "library_interactive": {
+ "hash": "98f3d10aa7f2fce6bdeb0ecda339fa56dc80b37c",
+ "data": {
+ "aspect_ratio_method": "DEFAULT",
+ "authoring_guidance": "",
+ "base_url": "https://models-resources.concord.org/question-interactives/version/v1.2.0-pre.1/multiple-choice/",
+ "click_to_play": false,
+ "click_to_play_prompt": null,
+ "description": "",
+ "enable_learner_state": true,
+ "full_window": false,
+ "has_report_url": false,
+ "image_url": null,
+ "name": "Multiple Choice",
+ "native_height": 435,
+ "native_width": 576,
+ "no_snapshots": false,
+ "show_delete_data_button": false,
+ "thumbnail_url": "",
+ "customizable": true,
+ "authorable": true
+ }
+ },
+ "type": "ManagedInteractive",
+ "ref_id": "1692-ManagedInteractive",
+ "linked_interactives": []
+ },
+ "section": null
+ },
+ {
+ "embeddable": {
+ "name": "",
+ "url_fragment": null,
+ "authored_state": "{\"version\":1,\"questionType\":\"open_response\",\"prompt\":\"\r\n\r\n
",
+ "is_callout": false,
+ "is_full_width": true,
+ "is_hidden": false,
+ "name": "",
+ "type": "Embeddable::Xhtml",
+ "ref_id": "147903-Embeddable::Xhtml"
+ },
+ "section": "header_block"
+ },
+ {
+ "embeddable": {
+ "name": "",
+ "url_fragment": null,
+ "authored_state": "{\"version\":1,\"questionType\":\"multiple_choice\",\"multipleAnswers\":false,\"layout\":\"vertical\",\"choices\":[{\"id\":\"1\",\"content\":\"Alex\",\"correct\":false},{\"id\":\"2\",\"content\":\"Delana\",\"correct\":false},{\"id\":\"3\",\"content\":\"Kalin\",\"correct\":false},{\"content\":\"Sage\",\"correct\":false,\"id\":\"6bd7ac18-6b07-4996-9e4b-199430b43e0c\"}]}",
+ "is_hidden": false,
+ "is_full_width": true,
+ "show_in_featured_question_report": true,
+ "inherit_aspect_ratio_method": true,
+ "custom_aspect_ratio_method": "DEFAULT",
+ "inherit_native_width": true,
+ "custom_native_width": 576,
+ "inherit_native_height": true,
+ "custom_native_height": 435,
+ "inherit_click_to_play": true,
+ "custom_click_to_play": false,
+ "inherit_full_window": true,
+ "custom_full_window": false,
+ "inherit_click_to_play_prompt": true,
+ "custom_click_to_play_prompt": null,
+ "inherit_image_url": true,
+ "custom_image_url": null,
+ "library_interactive": {
+ "hash": "98f3d10aa7f2fce6bdeb0ecda339fa56dc80b37c",
+ "data": {
+ "aspect_ratio_method": "DEFAULT",
+ "authoring_guidance": "",
+ "base_url": "https://models-resources.concord.org/question-interactives/version/v1.2.0-pre.1/multiple-choice/",
+ "click_to_play": false,
+ "click_to_play_prompt": null,
+ "description": "",
+ "enable_learner_state": true,
+ "full_window": false,
+ "has_report_url": false,
+ "image_url": null,
+ "name": "Multiple Choice",
+ "native_height": 435,
+ "native_width": 576,
+ "no_snapshots": false,
+ "show_delete_data_button": false,
+ "thumbnail_url": "",
+ "customizable": true,
+ "authorable": true
+ }
+ },
+ "type": "ManagedInteractive",
+ "ref_id": "1690-ManagedInteractive",
+ "linked_interactives": []
+ },
+ "section": null
+ },
+ {
+ "embeddable": {
+ "name": "",
+ "url_fragment": null,
+ "authored_state": "{\"version\":1,\"questionType\":\"open_response\",\"prompt\":\"\r\n\r\n
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+ "is_callout": false,
+ "is_full_width": true,
+ "is_hidden": false,
+ "name": "",
+ "type": "Embeddable::Xhtml",
+ "ref_id": "147932-Embeddable::Xhtml"
+ },
+ "section": "header_block"
+ },
+ {
+ "embeddable": {
+ "name": "",
+ "url_fragment": null,
+ "authored_state": "{\"version\":1,\"questionType\":\"multiple_choice\",\"multipleAnswers\":false,\"layout\":\"vertical\",\"choices\":[{\"id\":\"1\",\"content\":\"Alex\",\"correct\":false},{\"id\":\"2\",\"content\":\"Delana\",\"correct\":false},{\"id\":\"3\",\"content\":\"Kalin\",\"correct\":false},{\"content\":\"Sage\",\"correct\":false,\"id\":\"48ed2c41-2f41-4d5e-b70c-89cc42e2eb72\"}],\"prompt\":\"\r\n\r\n
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+ "is_callout": false,
+ "is_full_width": true,
+ "is_hidden": false,
+ "name": "",
+ "type": "Embeddable::Xhtml",
+ "ref_id": "147929-Embeddable::Xhtml"
+ },
+ "section": "header_block"
+ },
+ {
+ "embeddable": {
+ "name": "",
+ "url_fragment": null,
+ "authored_state": "{\"version\":1,\"questionType\":\"multiple_choice\",\"multipleAnswers\":false,\"layout\":\"vertical\",\"choices\":[{\"id\":\"1\",\"content\":\"Alex\",\"correct\":false},{\"id\":\"2\",\"content\":\"Delana\",\"correct\":false},{\"id\":\"3\",\"content\":\"Kalin\",\"correct\":false},{\"content\":\"Sage\",\"correct\":false,\"id\":\"48ed2c41-2f41-4d5e-b70c-89cc42e2eb72\"}],\"prompt\":\"\r\n\r\n
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+ "is_callout": false,
+ "is_full_width": true,
+ "is_hidden": false,
+ "name": "",
+ "type": "Embeddable::Xhtml",
+ "ref_id": "147922-Embeddable::Xhtml"
+ },
+ "section": "header_block"
+ },
+ {
+ "embeddable": {
+ "name": "",
+ "url_fragment": null,
+ "authored_state": "{\"version\":1,\"questionType\":\"multiple_choice\",\"multipleAnswers\":false,\"layout\":\"vertical\",\"choices\":[{\"id\":\"1\",\"content\":\"Alex\",\"correct\":false},{\"id\":\"2\",\"content\":\"Delana\",\"correct\":false},{\"id\":\"3\",\"content\":\"Kalin\",\"correct\":false},{\"content\":\"Sage\",\"correct\":false,\"id\":\"89f32589-2b6d-47d3-8159-62a30d7f2a92\"}]}",
+ "is_hidden": false,
+ "is_full_width": true,
+ "show_in_featured_question_report": true,
+ "inherit_aspect_ratio_method": true,
+ "custom_aspect_ratio_method": "DEFAULT",
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+ "hash": "98f3d10aa7f2fce6bdeb0ecda339fa56dc80b37c",
+ "data": {
+ "aspect_ratio_method": "DEFAULT",
+ "authoring_guidance": "",
+ "base_url": "https://models-resources.concord.org/question-interactives/version/v1.2.0-pre.1/multiple-choice/",
+ "click_to_play": false,
+ "click_to_play_prompt": null,
+ "description": "",
+ "enable_learner_state": true,
+ "full_window": false,
+ "has_report_url": false,
+ "image_url": null,
+ "name": "Multiple Choice",
+ "native_height": 435,
+ "native_width": 576,
+ "no_snapshots": false,
+ "show_delete_data_button": false,
+ "thumbnail_url": "",
+ "customizable": true,
+ "authorable": true
+ }
+ },
+ "type": "ManagedInteractive",
+ "ref_id": "1687-ManagedInteractive",
+ "linked_interactives": []
+ },
+ "section": null
+ },
+ {
+ "embeddable": {
+ "name": "",
+ "url_fragment": null,
+ "authored_state": "{\"version\":1,\"questionType\":\"open_response\",\"prompt\":\"\r\n\r\n
",
+ "is_callout": false,
+ "is_full_width": true,
+ "is_hidden": false,
+ "name": "",
+ "type": "Embeddable::Xhtml",
+ "ref_id": "147904-Embeddable::Xhtml"
+ },
+ "section": "header_block"
+ },
+ {
+ "embeddable": {
+ "name": "",
+ "url_fragment": null,
+ "authored_state": "{\"version\":1,\"questionType\":\"multiple_choice\",\"multipleAnswers\":false,\"layout\":\"vertical\",\"choices\":[{\"id\":\"1\",\"content\":\"Alex\",\"correct\":false},{\"id\":\"2\",\"content\":\"Delana\",\"correct\":false},{\"id\":\"3\",\"content\":\"Kalin\",\"correct\":false},{\"content\":\"Sage\",\"correct\":false,\"id\":\"6bd7ac18-6b07-4996-9e4b-199430b43e0c\"}]}",
+ "is_hidden": false,
+ "is_full_width": true,
+ "show_in_featured_question_report": true,
+ "inherit_aspect_ratio_method": true,
+ "custom_aspect_ratio_method": "DEFAULT",
+ "inherit_native_width": true,
+ "custom_native_width": 576,
+ "inherit_native_height": true,
+ "custom_native_height": 435,
+ "inherit_click_to_play": true,
+ "custom_click_to_play": false,
+ "inherit_full_window": true,
+ "custom_full_window": false,
+ "inherit_click_to_play_prompt": true,
+ "custom_click_to_play_prompt": null,
+ "inherit_image_url": true,
+ "custom_image_url": null,
+ "library_interactive": {
+ "hash": "98f3d10aa7f2fce6bdeb0ecda339fa56dc80b37c",
+ "data": {
+ "aspect_ratio_method": "DEFAULT",
+ "authoring_guidance": "",
+ "base_url": "https://models-resources.concord.org/question-interactives/version/v1.2.0-pre.1/multiple-choice/",
+ "click_to_play": false,
+ "click_to_play_prompt": null,
+ "description": "",
+ "enable_learner_state": true,
+ "full_window": false,
+ "has_report_url": false,
+ "image_url": null,
+ "name": "Multiple Choice",
+ "native_height": 435,
+ "native_width": 576,
+ "no_snapshots": false,
+ "show_delete_data_button": false,
+ "thumbnail_url": "",
+ "customizable": true,
+ "authorable": true
+ }
+ },
+ "type": "ManagedInteractive",
+ "ref_id": "1692-ManagedInteractive",
+ "linked_interactives": []
+ },
+ "section": null
+ },
+ {
+ "embeddable": {
+ "name": "",
+ "url_fragment": null,
+ "authored_state": "{\"version\":1,\"questionType\":\"open_response\",\"prompt\":\"\r\n\r\n
",
+ "is_callout": false,
+ "is_full_width": true,
+ "is_hidden": false,
+ "name": "",
+ "type": "Embeddable::Xhtml",
+ "ref_id": "147903-Embeddable::Xhtml"
+ },
+ "section": "header_block"
+ },
+ {
+ "embeddable": {
+ "name": "",
+ "url_fragment": null,
+ "authored_state": "{\"version\":1,\"questionType\":\"multiple_choice\",\"multipleAnswers\":false,\"layout\":\"vertical\",\"choices\":[{\"id\":\"1\",\"content\":\"Alex\",\"correct\":false},{\"id\":\"2\",\"content\":\"Delana\",\"correct\":false},{\"id\":\"3\",\"content\":\"Kalin\",\"correct\":false},{\"content\":\"Sage\",\"correct\":false,\"id\":\"6bd7ac18-6b07-4996-9e4b-199430b43e0c\"}]}",
+ "is_hidden": false,
+ "is_full_width": true,
+ "show_in_featured_question_report": true,
+ "inherit_aspect_ratio_method": true,
+ "custom_aspect_ratio_method": "DEFAULT",
+ "inherit_native_width": true,
+ "custom_native_width": 576,
+ "inherit_native_height": true,
+ "custom_native_height": 435,
+ "inherit_click_to_play": true,
+ "custom_click_to_play": false,
+ "inherit_full_window": true,
+ "custom_full_window": false,
+ "inherit_click_to_play_prompt": true,
+ "custom_click_to_play_prompt": null,
+ "inherit_image_url": true,
+ "custom_image_url": null,
+ "library_interactive": {
+ "hash": "98f3d10aa7f2fce6bdeb0ecda339fa56dc80b37c",
+ "data": {
+ "aspect_ratio_method": "DEFAULT",
+ "authoring_guidance": "",
+ "base_url": "https://models-resources.concord.org/question-interactives/version/v1.2.0-pre.1/multiple-choice/",
+ "click_to_play": false,
+ "click_to_play_prompt": null,
+ "description": "",
+ "enable_learner_state": true,
+ "full_window": false,
+ "has_report_url": false,
+ "image_url": null,
+ "name": "Multiple Choice",
+ "native_height": 435,
+ "native_width": 576,
+ "no_snapshots": false,
+ "show_delete_data_button": false,
+ "thumbnail_url": "",
+ "customizable": true,
+ "authorable": true
+ }
+ },
+ "type": "ManagedInteractive",
+ "ref_id": "1690-ManagedInteractive",
+ "linked_interactives": []
+ },
+ "section": null
+ },
+ {
+ "embeddable": {
+ "name": "",
+ "url_fragment": null,
+ "authored_state": "{\"version\":1,\"questionType\":\"open_response\",\"prompt\":\"\r\n\r\n
",
+ "is_callout": false,
+ "is_full_width": true,
+ "is_hidden": false,
+ "name": "",
+ "type": "Embeddable::Xhtml",
+ "ref_id": "147932-Embeddable::Xhtml"
+ },
+ "section": "header_block"
+ },
+ {
+ "embeddable": {
+ "name": "",
+ "url_fragment": null,
+ "authored_state": "{\"version\":1,\"questionType\":\"multiple_choice\",\"multipleAnswers\":false,\"layout\":\"vertical\",\"choices\":[{\"id\":\"1\",\"content\":\"Alex\",\"correct\":false},{\"id\":\"2\",\"content\":\"Delana\",\"correct\":false},{\"id\":\"3\",\"content\":\"Kalin\",\"correct\":false},{\"content\":\"Sage\",\"correct\":false,\"id\":\"48ed2c41-2f41-4d5e-b70c-89cc42e2eb72\"}],\"prompt\":\"\r\n\r\n
",
+ "is_callout": false,
+ "is_full_width": true,
+ "is_hidden": false,
+ "name": "",
+ "type": "Embeddable::Xhtml",
+ "ref_id": "147929-Embeddable::Xhtml"
+ },
+ "section": "header_block"
+ },
+ {
+ "embeddable": {
+ "name": "",
+ "url_fragment": null,
+ "authored_state": "{\"version\":1,\"questionType\":\"multiple_choice\",\"multipleAnswers\":false,\"layout\":\"vertical\",\"choices\":[{\"id\":\"1\",\"content\":\"Alex\",\"correct\":false},{\"id\":\"2\",\"content\":\"Delana\",\"correct\":false},{\"id\":\"3\",\"content\":\"Kalin\",\"correct\":false},{\"content\":\"Sage\",\"correct\":false,\"id\":\"48ed2c41-2f41-4d5e-b70c-89cc42e2eb72\"}],\"prompt\":\"\r\n\r\n
",
+ "is_callout": false,
+ "is_full_width": true,
+ "is_hidden": false,
+ "name": "",
+ "type": "Embeddable::Xhtml",
+ "ref_id": "147922-Embeddable::Xhtml"
+ },
+ "section": "header_block"
+ },
+ {
+ "embeddable": {
+ "name": "",
+ "url_fragment": null,
+ "authored_state": "{\"version\":1,\"questionType\":\"multiple_choice\",\"multipleAnswers\":false,\"layout\":\"vertical\",\"choices\":[{\"id\":\"1\",\"content\":\"Alex\",\"correct\":false},{\"id\":\"2\",\"content\":\"Delana\",\"correct\":false},{\"id\":\"3\",\"content\":\"Kalin\",\"correct\":false},{\"content\":\"Sage\",\"correct\":false,\"id\":\"89f32589-2b6d-47d3-8159-62a30d7f2a92\"}],\"prompt\":\"\r\n\r\n
",
+ "is_callout": false,
+ "is_full_width": true,
+ "is_hidden": false,
+ "name": "",
+ "type": "Embeddable::Xhtml",
+ "ref_id": "147921-Embeddable::Xhtml"
+ },
+ "section": "header_block"
+ },
+ {
+ "embeddable": {
+ "name": "",
+ "url_fragment": null,
+ "authored_state": "{\"version\":1,\"questionType\":\"multiple_choice\",\"multipleAnswers\":false,\"layout\":\"vertical\",\"choices\":[{\"id\":\"1\",\"content\":\"Alex\",\"correct\":false},{\"id\":\"2\",\"content\":\"Delana\",\"correct\":false},{\"id\":\"3\",\"content\":\"Kalin\",\"correct\":false},{\"content\":\"Sage\",\"correct\":false,\"id\":\"89f32589-2b6d-47d3-8159-62a30d7f2a92\"}]}",
+ "is_hidden": false,
+ "is_full_width": true,
+ "show_in_featured_question_report": true,
+ "inherit_aspect_ratio_method": true,
+ "custom_aspect_ratio_method": "DEFAULT",
+ "inherit_native_width": true,
+ "custom_native_width": 576,
+ "inherit_native_height": true,
+ "custom_native_height": 435,
+ "inherit_click_to_play": true,
+ "custom_click_to_play": false,
+ "inherit_full_window": true,
+ "custom_full_window": false,
+ "inherit_click_to_play_prompt": true,
+ "custom_click_to_play_prompt": null,
+ "inherit_image_url": true,
+ "custom_image_url": null,
+ "library_interactive": {
+ "hash": "98f3d10aa7f2fce6bdeb0ecda339fa56dc80b37c",
+ "data": {
+ "aspect_ratio_method": "DEFAULT",
+ "authoring_guidance": "",
+ "base_url": "https://models-resources.concord.org/question-interactives/version/v1.2.0-pre.1/multiple-choice/",
+ "click_to_play": false,
+ "click_to_play_prompt": null,
+ "description": "",
+ "enable_learner_state": true,
+ "full_window": false,
+ "has_report_url": false,
+ "image_url": null,
+ "name": "Multiple Choice",
+ "native_height": 435,
+ "native_width": 576,
+ "no_snapshots": false,
+ "show_delete_data_button": false,
+ "thumbnail_url": "",
+ "customizable": true,
+ "authorable": true
+ }
+ },
+ "type": "ManagedInteractive",
+ "ref_id": "1694-ManagedInteractive",
+ "linked_interactives": []
+ },
+ "section": null
+ },
+ {
+ "embeddable": {
+ "name": "",
+ "url_fragment": null,
+ "authored_state": "{\"version\":1,\"questionType\":\"open_response\",\"prompt\":\"\r\n\r\n
",
+ "is_callout": false,
+ "is_full_width": true,
+ "is_hidden": false,
+ "name": "",
+ "type": "Embeddable::Xhtml",
+ "ref_id": "147924-Embeddable::Xhtml"
+ },
+ "section": "header_block"
+ },
+ {
+ "embeddable": {
+ "name": "",
+ "url_fragment": null,
+ "authored_state": "{\"version\":1,\"questionType\":\"open_response\",\"prompt\":\"![](\\\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/Lesson5WIndTablesTopDownView1.jpg\\\")
\\n\\n* To print the wind rose, click [here](https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/WindCompass.jpg) to download. \",\"content2\":\"\",\"mediaType\":\"none\",\"mediaCaption\":\"Last, First. \\\"Title of Work.\\\" Year created. Site Title [OR] Publisher. Gallery [OR] Location. http://www.url.com.\",\"mediaURL\":\"\"}}",
+ "approved_script_label": "teacherEditionTips",
+ "component_label": "windowShade",
+ "approved_script": {
+ "name": "Teacher Edition",
+ "url": "https://teacher-edition-tips-plugin.concord.org/version/v3.6.0/plugin.js",
+ "label": "teacherEditionTips",
+ "description": "This plugin provides Teacher Edition components",
+ "version": 3,
+ "json_url": "https://teacher-edition-tips-plugin.concord.org/version/v3.6.0/manifest.json",
+ "authoring_metadata": "{\"components\":[{\"label\":\"windowShade\",\"name\":\"Window Shades\",\"scope\":\"embeddable\",\"guiAuthoring\":true},{\"label\":\"sideTip\",\"name\":\"Side Tips\",\"scope\":\"embeddable\",\"guiAuthoring\":true},{\"label\":\"questionWrapper\",\"name\":\"Question Wrapper\",\"scope\":\"embeddable-decoration\",\"decorates\":[\"Embeddable::MultipleChoice\",\"Embeddable::OpenResponse\",\"Embeddable::ImageQuestion\",\"ManagedInteractive\",\"MwInteractive\",\"ImageInteractive\",\"VideoInteractive\"],\"guiAuthoring\":true,\"guiPreview\":true}]}"
+ }
+ },
+ "is_hidden": false,
+ "is_full_width": true,
+ "type": "Embeddable::EmbeddablePlugin",
+ "ref_id": "4042-Embeddable::EmbeddablePlugin"
+ },
+ "section": null
+ },
+ {
+ "embeddable": {
+ "plugin": {
+ "description": null,
+ "author_data": "{\"tipType\":\"windowShade\",\"windowShade\":{\"windowShadeType\":\"framing\",\"layout\":\"mediaLeft\",\"initialOpenState\":true,\"content\":\"Watch this video with your class to give students a perspective on the importance of weather and to build weather science career awareness.\",\"content2\":\"\",\"mediaType\":\"video\",\"mediaCaption\":\"Purcell, Jackie. \\\"Lesson 5.\\\" 2019. Good Life Productions. Anchorage, AK.\",\"mediaURL\":\"https://precipitatingchange-resources.concord.org/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/JackieLesson5_88.mp4\"}}",
+ "approved_script_label": "teacherEditionTips",
+ "component_label": "windowShade",
+ "approved_script": {
+ "name": "Teacher Edition",
+ "url": "https://teacher-edition-tips-plugin.concord.org/version/v3.6.0/plugin.js",
+ "label": "teacherEditionTips",
+ "description": "This plugin provides Teacher Edition components",
+ "version": 3,
+ "json_url": "https://teacher-edition-tips-plugin.concord.org/version/v3.6.0/manifest.json",
+ "authoring_metadata": "{\"components\":[{\"label\":\"windowShade\",\"name\":\"Window Shades\",\"scope\":\"embeddable\",\"guiAuthoring\":true},{\"label\":\"sideTip\",\"name\":\"Side Tips\",\"scope\":\"embeddable\",\"guiAuthoring\":true},{\"label\":\"questionWrapper\",\"name\":\"Question Wrapper\",\"scope\":\"embeddable-decoration\",\"decorates\":[\"Embeddable::MultipleChoice\",\"Embeddable::OpenResponse\",\"Embeddable::ImageQuestion\",\"ManagedInteractive\",\"MwInteractive\",\"ImageInteractive\",\"VideoInteractive\"],\"guiAuthoring\":true,\"guiPreview\":true}]}"
+ }
+ },
+ "is_hidden": false,
+ "is_full_width": true,
+ "type": "Embeddable::EmbeddablePlugin",
+ "ref_id": "4043-Embeddable::EmbeddablePlugin"
+ },
+ "section": null
+ }
+ ]
+ },
+ {
+ "additional_sections": null,
+ "embeddable_display_mode": "stacked",
+ "id": 308515,
+ "is_completion": false,
+ "is_hidden": false,
+ "layout": "l-full-width",
+ "name": " Activity 1 - What is an air mass?",
+ "position": 2,
+ "show_header": true,
+ "show_info_assessment": true,
+ "show_interactive": false,
+ "show_sidebar": false,
+ "sidebar": null,
+ "sidebar_title": "Did you know?",
+ "toggle_info_assessment": false,
+ "embeddables": [
+ {
+ "embeddable": {
+ "content": "");
+ }
+
+ const filenameWithExtension = filename.endsWith(".json") ? filename : `${filename}.json`;
+ const manifestPath = path.join(__dirname, "../public/offline-manifests/", filenameWithExtension);
+
+ if (!fs.existsSync(manifestPath)) {
+ die(`Cannot find ${manifestPath}`);
+ }
+
+ return manifestPath;
+};
+
+const loadJSONFile = (filename: string) => {
+ try {
+ return JSON.parse(fs.readFileSync(filename).toString());
+ } catch (e) {
+ die(`Cannot parse ${filename} - ${e.toString()}`);
+ }
+};
+
+const convertToApiUrl = (resourceUrl: string) => {
+ const matches = resourceUrl.match(/^(https?:\/\/(.*))\/activities\/(\d+)$/);
+ if (!matches) {
+ return die(`Unknown resourceUrl format: ${resourceUrl}`);
+ }
+ return `${matches[1]}/api/v1/activities/${matches[3]}.json`;
+};
+
+const getActivity = async (offlineActivity: OfflineManifestActivity): Promise => {
+ console.log("Processing", offlineActivity.name, "...");
+ const url = convertToApiUrl(offlineActivity.resourceUrl);
+ console.log(" ", url, "...");
+
+ if (fetchActivities) {
+ try {
+ const resp = await request.get(url);
+ return JSON.parse(resp.text) as Activity;
+ } catch (e) {
+ die(`Unable to get ${url} - ${e.toString()}`);
+ }
+ } else {
+ const activityPath = path.join(__dirname, "../public/", offlineActivity.contentUrl);
+ return loadJSONFile(activityPath) as Activity;
+ }
+
+ return null;
+};
+
+const maybeProxyUrl = (url: string) => /^models-resources\//.test(url) ? `http://activity-player-offline.concord.org/${url}` : url;
+
+const getOutputInfo = (manifestPath: string): OutputInfo => {
+ const {dir, base} = path.parse(manifestPath);
+
+ const matches = base.match(/^(.*)-v(\d+)\.json$/);
+ if (!matches) {
+ return die(`Not a versioned manifest we can deal with: ${manifestPath}`);
+ }
+
+ const sourceVersion = parseInt(matches[2], 10);
+ if (isNaN(sourceVersion)) {
+ return die(`Not a integer version: ${matches[2]}`);
+ }
+ const sourceVersionName = `${matches[1]}-v${sourceVersion}`;
+
+ const outputVersion = bumpVersion ? sourceVersion + 1 : sourceVersion;
+
+ const outputVersionName = `${matches[1]}-v${outputVersion}`;
+ const outputManifestPath = path.join(dir, `${outputVersionName}.json`);
+ const offlineActivitiesDir = dir.replace("offline-manifests", "offline-activities");
+
+ let outputActivityDir = offlineActivitiesDir;
+ let createOutputDir = false;
+
+ // Some manifests use directories for their activities files
+ try {
+ const possibleSourceActivityDir = path.join(offlineActivitiesDir, sourceVersionName);
+ const sourceVersionStat = fs.statSync(possibleSourceActivityDir);
+ if (sourceVersionStat.isDirectory()) {
+ outputActivityDir = path.join(outputActivityDir, outputVersionName);
+ createOutputDir = true;
+ }
+ } catch (e) {} // eslint-disable-line no-empty
+
+ return ({
+ outputManifestPath,
+ outputActivityDir,
+ createOutputDir,
+ sourceVersionName,
+ outputVersionName
+ });
+};
+
+const saveActivity = (outputInfo: OutputInfo, offlineActivity: OfflineManifestActivity, activity: Activity) => {
+ let {base} = path.parse(offlineActivity.contentUrl);
+ if (!outputInfo.createOutputDir) {
+ base = base.replace(outputInfo.sourceVersionName, outputInfo.outputVersionName);
+ }
+ const filename = path.join(outputInfo.outputActivityDir, base);
+ console.log(` saving ${filename}...`);
+ fs.writeFileSync(filename, JSON.stringify(activity, null, 2));
+};
+
+const updateActivityUrls = (activity: Activity) => {
+ activity.plugins = activity.plugins.map(plugin => {
+ if (plugin.approved_script_label === "glossary") {
+ const authorData = JSON.parse(plugin.author_data);
+ authorData.s3Url = config.glossary.s3Url;
+ plugin.author_data = JSON.stringify(authorData);
+ plugin.approved_script.url = config.glossary.pluginUrl;
+ plugin.approved_script.json_url = config.glossary.manifestUrl;
+ }
+ return plugin;
+ });
+
+ walkObject(activity, (s, key) => {
+ if (key === "base_url") {
+ const matches = s.match(/^.*\/question-interactives\/(version|branch)\/([^/]+)(\/(.*))$/);
+ if (matches) {
+ return `https://models-resources.concord.org/question-interactives/version/${config.questionInteractives.version}${matches[3]}`;
+ }
+ }
+ return s;
+ });
+};
+
+const removeTeacherEdition = (activity: Activity) => {
+ activity.pages.forEach(page => {
+ page.embeddables = page.embeddables.filter(embeddableWrapper => {
+ const embeddable = embeddableWrapper.embeddable;
+ return !(embeddable.type === "Embeddable::EmbeddablePlugin" &&
+ embeddable.plugin?.approved_script_label === "teacherEditionTips");
+ });
+ });
+};
+
+const saveUpdatedManifest = (outputInfo: OutputInfo, sourceManifest: OfflineManifest, cacheList: string[]) => {
+
+ let activities = sourceManifest.activities;
+ if (bumpVersion) {
+ activities = sourceManifest.activities.map(a => ({...a, contentUrl: a.contentUrl.replace(outputInfo.sourceVersionName, outputInfo.outputVersionName)}));
+ }
+ const newOfflineManifest: OfflineManifest = {
+ name: sourceManifest.name,
+ activities,
+ cacheList
+ };
+ console.log(` saving ${outputInfo.outputManifestPath}...`);
+ fs.writeFileSync(outputInfo.outputManifestPath, JSON.stringify(newOfflineManifest, null, 2));
+};
+
+const main = async () => {
+ const manifestPath = getManifestPath();
+ const manifestJSON = loadJSONFile(manifestPath) as OfflineManifest;
+ let cacheList: string[] = [];
+
+ const outputInfo = getOutputInfo(manifestPath);
+ if (outputInfo?.createOutputDir) {
+ try {
+ fs.mkdirSync(outputInfo.outputActivityDir);
+ } catch (e) {} // eslint-disable-line no-empty
+ }
+
+ for (const offlineActivity of manifestJSON.activities) {
+ const activity = await getActivity(offlineActivity);
+ if (activity) {
+ // update glossary urls and question interactives in activity
+ updateActivityUrls(activity);
+
+ removeTeacherEdition(activity);
+
+ saveActivity(outputInfo, offlineActivity, activity);
+
+ // Replace the iframe urls with models-resources when we can
+ // But do this after we save the activity since the same thing is going
+ // to be applied at runtime
+ // Perhaps we want to change this behavior to simplify the runtime.
+ // Also it would be useful if this function told us about iframe urls
+ // that can't be re-written because these will likely fail when offline
+ rewriteProxiableIframeUrls(activity);
+
+ const urls = await getAllUrlsInActivity(activity);
+ console.log(` found ${urls.length} urls ...`);
+ cacheList.push(...urls);
+ }
+ }
+
+ cacheList = removeDuplicateUrls(cacheList);
+ cacheList.sort();
+
+ // const oldMissingUrls = manifestJSON.cacheList.filter(url => cacheList.indexOf(url) === -1);
+ // const allUrls = cacheList.concat(oldMissingUrls);
+ // console.log(`\nFound ${cacheList.length} unique urls in content and ${oldMissingUrls.length} urls in manifest cache list not in activities`);
+ console.log(`\nFound ${cacheList.length} unique urls in content`);
+
+ saveUpdatedManifest(outputInfo, manifestJSON, cacheList);
+
+ console.log("\nTesting all urls...");
+
+ const badUrls: {url: string, status: number}[] = [];
+ for (let url of cacheList) {
+ url = maybeProxyUrl(url);
+ console.log(" ", url);
+ try {
+ await request.head(url);
+ } catch (e) {
+ if (e.status >= 400) {
+ badUrls.push({url, status: e.status});
+ }
+ }
+ }
+
+ if (badUrls.length > 0) {
+ console.error(`\nFound ${badUrls.length} bad urls...`);
+ for (const badUrl of badUrls) {
+ console.log(`${badUrl.status}: ${badUrl.url}`);
+ }
+ }
+
+};
+
+main();
diff --git a/src/service-worker.ts b/src/service-worker.ts
new file mode 100644
index 00000000..bed38253
--- /dev/null
+++ b/src/service-worker.ts
@@ -0,0 +1,265 @@
+import "ts-polyfill";
+
+declare const self: ServiceWorkerGlobalScope;
+
+import { WorkboxPlugin } from "workbox-core";
+import { registerRoute } from "workbox-routing";
+import { CacheOnly, NetworkFirst } from "workbox-strategies";
+// import { CacheableResponsePlugin } from "workbox-cacheable-response";
+import { RangeRequestsPlugin } from "workbox-range-requests";
+
+const ignoredGets: RegExp[] = [
+ /\/sockjs-node\/info/, // webpack-dev-server
+ /\.hot-update\./, // webpack-dev-server
+ /\/firestore\.googleapis\.com\//, // firebase
+ /\/install\.html/, // installer
+ /\/assets\/install\.*/, // installer
+ /\/app-manifest\.js/, // installer
+ /\/offline-manifests\/.*/, // built in manifests
+ /https:\/\/learn\.(staging\.)?concord\.org\/.*/ // portal apis when launached from the portal
+];
+
+// Disable the noisy workbox dev logs.
+// If you are debugging a stragegy issue turning these on can be useful
+(self as any).__WB_DISABLE_DEV_LOGS = true;
+
+/**
+ Strip out the __WB_REVISION__ parameter
+ Note this also escapes the parameters, so it needs to be applied to both the
+ write and read operations
+ For example URLs like this one:
+ https://fonts.googleapis.com/css2?family=Lato:wght@400;700;900&display=swap
+ get converted to this format when passing through:
+ https://fonts.googleapis.com/css2?family=Lato%3Awght%40400%3B700%3B900&display=swap
+**/
+const stripWbRevision: WorkboxPlugin = {
+ cacheKeyWillBeUsed: async ({request, mode, params, event, state}) => {
+ const url = new URL(request.url);
+ url.searchParams.delete("__WB_REVISION__");
+ // We need to create a request with headers because the return value is
+ // passed through to future callbacks. If a simple url is returned then
+ // Workbox makes a generic Request object with no headers.
+ // The headers are important specifically for the Range Plugin which
+ // hooks into the cachedResponseWillBeUsed and looks at the headers of
+ // the response object passed in.
+ return new Request(url.href, {headers: request.headers});
+ }
+};
+
+// If the service worker is loaded at:
+// https://example.com/path/service-worker.js
+// Then treat
+// https://example.com/path/
+// https://example.com/path/index.html
+// https://example.com/path/index.html?anyParam=hi&anyOtherParam
+// All as the same url from the cache they all will have the cache key of
+// https://example.com/path/index.html
+const rootUrl = new URL(".", location.href);
+const rootIndexHtmlUrl = new URL("index.html", location.href);
+const cleanIndexHtmlParams: WorkboxPlugin = {
+ cacheKeyWillBeUsed: async ({request, mode, params, event, state}) => {
+ const url = new URL(request.url);
+ if (url.origin === location.origin &&
+ (url.pathname === rootUrl.pathname ||
+ url.pathname === rootIndexHtmlUrl.pathname) ) {
+ // To be safe we pass the headers through, just like we do when
+ // stripping the __WB_REVISION__
+ return new Request(rootIndexHtmlUrl.href, {headers: request.headers});
+ } else {
+ return request;
+ }
+ }
+};
+
+registerRoute(
+ ({ request }) => {
+ const isGet = request.method.toUpperCase() === "GET";
+ // It is tempting to try to block firestore and portal requests here
+ // when we aren't launched from the portal.
+ // However, those should only happen if the application code is buggy.
+ // Additionally there isn't a good way to implement that, there is just
+ // one service worker used by all clients: browser tabs and the PWA.
+ // So it is possible there will be one 'client' that is launched from the
+ // portal and another client that is not. Because of that we can't
+ // consitently block these requests.
+ const isIgnored = !!ignoredGets.find(ig => ig.test(request.url));
+ return isGet && !isIgnored;
+ },
+ new CacheOnly({
+ cacheName: "cachedGets",
+ plugins: [
+ // handle range requests
+ new RangeRequestsPlugin(),
+ // We don't really need to delete the __WB_REVISION__ here
+ // but otherwise the cache key will not match the key used during the install
+ stripWbRevision,
+ cleanIndexHtmlParams
+ ],
+ }),
+);
+
+
+// These were taken from workbox-routing/Router
+// they will likely need to be changed so we can include revisions
+// which can force updates from what is cached.
+type RequestArgs = string | [string, RequestInit?];
+interface CacheURLsMessageData {
+ type: string;
+ payload: {
+ urlsToCache: RequestArgs[];
+ };
+}
+
+// This was taken from workbox-routing/Router
+
+/**
+ * Adds a message event listener for URLs to cache from the window.
+ * This is useful to cache resources loaded on the page prior to when the
+ * service worker started controlling it.
+ *
+ * The format of the message data sent from the window should be as follows.
+ * Where the `urlsToCache` array may consist of URL strings or an array of
+ * URL string + `requestInit` object (the same as you'd pass to `fetch()`).
+ *
+ * ```
+ * {
+ * type: 'CACHE_URLS',
+ * payload: {
+ * urlsToCache: [
+ * './script1.js',
+ * './script2.js',
+ * ['./script3.js', {mode: 'no-cors'}],
+ * ],
+ * },
+ * }
+ * ```
+ */
+function addCacheListener() {
+ const networkFirst = new NetworkFirst({
+ cacheName: "cachedGets",
+ // Skip the disk cache when fetching
+ // This fixes a problem where a user visiting an online page with some
+ // of the offline assets in it will populate the disk cache with those
+ // assets. But they might be stored without CORS headers in the response
+ // which then breaks the request made here.
+ fetchOptions: {cache: "no-store"},
+ plugins: [
+ stripWbRevision,
+ cleanIndexHtmlParams,
+ {
+ // Don't allow reads from the cache. We only want to populate the cache.
+ // If a network request fails we don't want to return the old value
+ // from the cache. It might be out of date, and we want the network
+ // error to propigate up.
+ //
+ // TODO: it'd be better if every manifest included urls with hashes in
+ // them. The Workbox generated manifests include __WB_REVISION__. If that
+ // was present in every entry then we could add that to a header in
+ // the response stored in the cache, then we'd access that response
+ // and see if the new entry matched, if so we could just return it.
+ // if it didn't match then we'd download it from the network
+ cachedResponseWillBeUsed: async ({cacheName, request, matchOptions, cachedResponse, event, state}) => {
+ return null;
+ }
+ }
+ ]
+ });
+
+ // See https://github.com/Microsoft/TypeScript/issues/28357#issuecomment-436484705
+ self.addEventListener("message", ((event: ExtendableMessageEvent) => {
+ if (event.data && event.data.type === "CACHE_URLS_WITH_PROGRESS") {
+ const {payload}: CacheURLsMessageData = event.data;
+ const messagePort: MessagePort | undefined = event.ports?.[0];
+
+ console.log(`Caching URLs from the window`, payload.urlsToCache);
+
+ const requestPromises = Promise.allSettled(payload.urlsToCache.map(
+ (entry: string | [string, RequestInit?]) => {
+ if (typeof entry === "string") {
+ entry = [entry];
+ }
+
+ const request = new Request(...entry);
+ // Use a specific strategy that is not registered as a route
+ // this way we get Workbox's strategy features without affecting
+ // regular page network requests
+ const [responsePromise, donePromise] = networkFirst.handleAll({request, event});
+
+ if (messagePort) {
+ let errorOccurred = false;
+ responsePromise.then(response => {
+ // At this point the response is ready. But this seems to happen
+ // when the browser recieves the headers from the get request.
+ // The actual caching of the data might take a while longer as
+ // there is a seperate body promise that is used to access that.
+ // The donePromise resolves when this caching is complete.
+ }).catch(error => {
+ // Only report an error once. It is possible the donePromise errored
+ // first.
+ if(!errorOccurred) {
+ messagePort.postMessage({type: "URL_CACHE_FAILED", payload: {url: request.url, error}});
+ errorOccurred = true;
+ }
+ });
+
+ donePromise.then(() => {
+ // Based on the implementation it is impossible for the responsePromise
+ // to thow an error and the donePromise to complete. But based on the
+ // api definition this could be possible, so I'm erring on the side
+ // of caution. And checking for the error here.
+ // We wouldn't want to send both a failed message and a
+ // success message for the same url.
+ if(!errorOccurred){
+ messagePort.postMessage({type: "URL_CACHED", payload: {url: request.url}});
+ }
+ }).catch(error => {
+ // Only report an error once. It is possible the responsePromise errored
+ // first.
+ if(!errorOccurred) {
+ messagePort.postMessage({type: "URL_CACHE_FAILED", payload: {url: request.url, error}});
+ errorOccurred = true;
+ }
+ });
+ }
+
+ return donePromise;
+
+ // TODO(philipwalton): TypeScript errors without this typecast for
+ // some reason (probably a bug). The real type here should work but
+ // doesn't: `Array | undefined>`.
+ }) as any[]); // TypeScript
+
+ // This is needed to keep the service worker alive while it is fetching
+ // otherwise the browser can aggresively stop the worker.
+ // This might not actually be needed because the event is being passed
+ // to the networkFirst handler too, which ought to call waitUntil itself
+ event.waitUntil(requestPromises);
+
+ if (messagePort) {
+ requestPromises.then(() => {
+ // We are using allSettled so if there is an error the caching will
+ // continue
+ messagePort.postMessage({type: "CACHING_FINISHED"});
+ });
+ }
+ }
+ }) as EventListener);
+}
+
+addCacheListener();
+
+addEventListener("message", (event) => {
+ if (event.data) {
+ switch (event.data.type) {
+ case "SKIP_WAITING":
+ self.skipWaiting();
+ break;
+
+ case "GET_VERSION_INFO":
+ event.ports[0].postMessage(__VERSION_INFO__);
+ break;
+ }
+ }
+});
+
+console.log("Service Worker started. version: ", __VERSION_INFO__);
diff --git a/src/storage/StorageFacade.png b/src/storage/StorageFacade.png
new file mode 100644
index 00000000..1ec5dc98
Binary files /dev/null and b/src/storage/StorageFacade.png differ
diff --git a/src/storage/architecture.md b/src/storage/architecture.md
new file mode 100644
index 00000000..7966b0ab
--- /dev/null
+++ b/src/storage/architecture.md
@@ -0,0 +1,51 @@
+
+# Storage Façade for saving student work.
+The `storage-facade.ts` file presents a single interface to two different storage
+backends for saving student data. Depending on whether or not the student is
+working **`offline`** methods on this singleton class will delegate storage
+functions to one of `FireStoreStorageProvider` or `DexieStorageProvider`.
+
+
+
+## The Storage API defined by `IStorageInterface`:
+
+```typescript
+ export interface IStorageInterface {
+ setPortalData: (_portalData: IPortalData | IAnonymousPortalData) => void,
+ initializeDB: (initializer: IDBInitializer) => Promise,
+ // initializeAnonymousDB?: (preview: boolean) => Promise
+ // signInWithToken?: (rawFirestoreJWT: string) => Promise,
+
+ getPortalData: () => IPortalData | IAnonymousPortalData | null,
+
+ // These are directly related to storing student answers and fetching them back
+ watchAnswer(embeddableRefId: string, callback: (wrappedAnswer: IWrappedDBAnswer | null) => void): () => void
+ watchAllAnswers: (callback: (wrappedAnswer: IWrappedDBAnswer[]) => void) => void,
+ createOrUpdateAnswer: (answer: IExportableAnswerMetadata) => void,
+ getLearnerPluginStateDocId: (pluginId: number) => string|undefined,
+ getCachedLearnerPluginState: (pluginId: number) => string|null,
+ getLearnerPluginState: (pluginId: number) => Promise,
+ setLearnerPluginState: (pluginId: number, state: string) => Promise,
+ // checkIfOnline: () => Promise,
+
+ // for saving a whole activity to JSON
+ exportActivityToJSON: (activityId?: string) => Promise,
+ importStudentAnswersFromJSONFile: (studentAnswers: string, filename: string) => boolean,
+ canSyncData(): boolean,
+ syncData(): void
+ }
+```
+
+## Initialization:
+Call the storage initializer `Storage.initStorage` with a few parameters.
+The `offline` parameter is the one which will switch between FireSTore and Dexie Storage providers:
+
+```typescript
+ Storage.initStorage(name: FirebaseImp.FirebaseAppName, preview: boolean, offline: boolean);
+```
+
+## Use:
+Obtain a reference to the storage provider by calling `Storage.getStorage()`.
+
+## Link to Lucid Chart Diagram:
+https://lucid.app/lucidchart/6d68f2a7-ae09-4ba1-9cea-b0a251cf43bd/edit?page=0_0#
\ No newline at end of file
diff --git a/src/storage/data-sync-tracker.test.ts b/src/storage/data-sync-tracker.test.ts
new file mode 100644
index 00000000..430f965b
--- /dev/null
+++ b/src/storage/data-sync-tracker.test.ts
@@ -0,0 +1,142 @@
+import { DataSyncTracker } from "./data-sync-tracker";
+import { IPluginSyncRequestEventHandler, IPluginSyncUpdate, offPluginSyncRequest, onPluginSyncRequest } from "../lara-plugin/events";
+
+
+interface ITimedResponse {fracInterval:number, state: IPluginSyncUpdate["status"]}
+
+class FakePlugin {
+ timedResponses: Array;
+ updateCallback: (update: IPluginSyncUpdate) => void;
+ maxInterval: number;
+ syncRecHandler: IPluginSyncRequestEventHandler;
+ constructor(timedResponses: Array) {
+ this.timedResponses = timedResponses;
+ this.syncRecHandler = (req) => {
+
+ this.updateCallback = req.updateCallback;
+ this.maxInterval = req.maxUpdateCallbackInterval;
+ this.respond();
+ };
+ onPluginSyncRequest(this.syncRecHandler);
+ }
+
+ respond() {
+ this.timedResponses.map( r => {
+ window.setTimeout(() => {
+ this.updateCallback({status: r.state});
+ }, r.fracInterval * this.maxInterval);
+ });
+ }
+
+ stopListening() {
+ offPluginSyncRequest(this.syncRecHandler);
+ }
+}
+
+describe("DataSyncTracker", () => {
+ it("When no plugins answer the call", ()=> {
+ const mySyncTracker = new DataSyncTracker(2,1);
+ const syncDone =jest.spyOn(mySyncTracker,"syncDone");
+ const receivedPluginStatus = jest.spyOn(mySyncTracker, "receivedPluginStatus");
+ const syncTimeout = jest.spyOn(mySyncTracker,"syncTimeout");
+
+ return mySyncTracker.start().then(() => {
+ expect(syncDone).toBeCalledTimes(1);
+ expect(receivedPluginStatus).not.toHaveBeenCalled();
+ expect(syncTimeout).not.toHaveBeenCalled();
+ expect(mySyncTracker.pluginSuccesses).toEqual(0);
+ expect(mySyncTracker.pluginFailures).toEqual(0);
+ });
+ });
+
+
+ it("When there are some plugins answering on time", () => {
+
+ const happyPlugin = new FakePlugin([
+ {fracInterval: 0.4, state: "started"},
+ {fracInterval: 0.4, state: "working"},
+ {fracInterval: 0.4, state: "working"},
+ {fracInterval: 0.4, state: "completed"}
+ ]);
+
+ const sadPlugin = new FakePlugin([
+ {fracInterval: 0.4, state: "started"},
+ {fracInterval: 0.4, state: "working"},
+ {fracInterval: 0.4, state: "working"},
+ {fracInterval: 0.4, state: "completed"}
+ ]);
+ const promiseFunc = jest.fn();
+ const myPromise:Promise = new Promise( (resolve, reject) => {
+ window.setTimeout(()=> {
+ promiseFunc();
+ resolve();
+ }, 1);
+ });
+ const mySyncTracker = new DataSyncTracker(100,1);
+ mySyncTracker.addPromise(myPromise);
+ const syncDone =jest.spyOn(mySyncTracker,"syncDone");
+ const receivedPluginStatus = jest.spyOn(mySyncTracker, "receivedPluginStatus");
+ const syncTimeout = jest.spyOn(mySyncTracker,"syncTimeout");
+
+ return mySyncTracker.start().then(() => {
+ expect(syncDone).toBeCalledTimes(1);
+ expect(receivedPluginStatus).toBeCalledTimes(8); // 4 happy, 4 sad
+ expect(syncTimeout).not.toHaveBeenCalled();
+ expect(mySyncTracker.pluginSuccesses).toEqual(2);
+ expect(mySyncTracker.pluginFailures).toEqual(0);
+ expect(mySyncTracker.pluginDrops).toEqual(0);
+ expect(promiseFunc).toHaveBeenCalled();
+ happyPlugin.stopListening();
+ sadPlugin.stopListening();
+ });
+ });
+
+ it("When some plugins are too slow in responding", () => {
+
+ const slowPlugin = new FakePlugin([
+ {fracInterval: 0.4, state: "started"},
+ {fracInterval: 3, state: "failed"}
+ ]);
+
+ const sadPlugin = new FakePlugin([
+ {fracInterval: 0.4, state: "started"},
+ {fracInterval: 0.4, state: "failed"}
+ ]);
+
+ const mySyncTracker = new DataSyncTracker(10,1);
+ // mySyncTracker.addPromise(myPromise);
+ const syncDone =jest.spyOn(mySyncTracker,"syncDone");
+ const receivedPluginStatus = jest.spyOn(mySyncTracker, "receivedPluginStatus");
+ const syncTimeout = jest.spyOn(mySyncTracker,"syncTimeout");
+
+ return mySyncTracker.start().then(() => {
+ expect(syncDone).toBeCalledTimes(1);
+ expect(syncTimeout).not.toHaveBeenCalled();
+ expect(receivedPluginStatus).toBeCalledTimes(3); // 1 slow, 2 sad
+ expect(mySyncTracker.pluginSuccesses).toEqual(0);
+ expect(mySyncTracker.pluginDrops).toEqual(1);
+ expect(mySyncTracker.pluginFailures).toEqual(1);
+ slowPlugin.stopListening();
+ sadPlugin.stopListening();
+ });
+ });
+
+ it("When a promise takes too long", () => {
+
+ const mySyncTracker = new DataSyncTracker(2,1);
+ const myPromise:Promise = new Promise( (resolve) => {
+ window.setTimeout(()=> {
+ resolve();
+ }, 3000);
+ });
+ mySyncTracker.addPromise(myPromise);
+ return mySyncTracker.start()
+ .then()
+ .catch((error) => {
+ expect(error).toMatch(/TimeOut/);
+ });
+ });
+});
+
+
+
diff --git a/src/storage/data-sync-tracker.ts b/src/storage/data-sync-tracker.ts
new file mode 100644
index 00000000..0b17946e
--- /dev/null
+++ b/src/storage/data-sync-tracker.ts
@@ -0,0 +1,121 @@
+import { emitPluginSyncRequest, IPluginSyncUpdate } from "../lara-plugin/events";
+import { ILogSyncUpdate, Logger } from "../lib/logger";
+
+const KDefaultSyncTimeoutSeconds = 60 * 60; // 1 hour save timeout
+const KDefaultPluginHeartbeatSeconds = 10; // 10 seconds before we give up
+
+// We save: Logs, student data, plugin data, and also ask plugins to save
+export class DataSyncTracker {
+ pluginTimeoutS: number; // Seconds
+ syncTimeoutS: number; // Seconds
+ startTimeMs: number; // Millies
+ pluginPromise: Promise;
+ promiseResolver: (result?:any)=>void|null;
+ promiseRejector: (reason: any)=>void;
+ pluginFailures: number;
+ pluginSuccesses: number;
+ pluginDrops: number;
+ pendingPromises: Array>;
+ timeoutRef: number
+ logsSynced: boolean;
+
+ constructor(
+ syncTimeoutS: number = KDefaultSyncTimeoutSeconds,
+ pluginTimeoutS: number = KDefaultPluginHeartbeatSeconds) {
+ this.syncTimeoutS = syncTimeoutS;
+ this.pluginTimeoutS = pluginTimeoutS;
+ this.pendingPromises = [];
+ this.pluginFailures = 0;
+ this.pluginSuccesses = 0;
+ this.pluginDrops = 0;
+ this.logsSynced = false;
+
+ this.receivedLoggerStatus = this.receivedLoggerStatus.bind(this);
+ }
+
+ start() {
+ this.startTimeMs = Date.now();
+ emitPluginSyncRequest({
+ maxUpdateCallbackInterval: this.pluginTimeoutS * 1000,
+ updateCallback: (status:IPluginSyncUpdate) => this.receivedPluginStatus(status)
+ });
+
+ this.pluginPromise = new Promise((resolve, reject) => {
+ this.promiseResolver = resolve;
+ this.promiseRejector = reject;
+ });
+
+ this.pendingPromises=[this.pluginPromise];
+ this.registerTimeOut();
+ this.registerSyncTimeOut();
+
+ Logger.syncOfflineLogs(this.receivedLoggerStatus);
+
+ return this.finish();
+ }
+
+ addPromise(promise: Promise) {
+ this.pendingPromises.push(promise);
+ }
+
+ registerSyncTimeOut() {
+ window.setTimeout(() => this.syncTimeout(), this.syncTimeoutS * 1000);
+ }
+
+ registerTimeOut() {
+ if(this.timeoutRef) { window.clearTimeout(this.timeoutRef); }
+ this.timeoutRef = window.setTimeout(() => this.syncDone(), this.pluginTimeoutS * 1000);
+ }
+
+ syncTimeout() {
+ this.promiseRejector("Sync operation TimeOut");
+ }
+
+ // We call this when we stop hearing from any plugins and the logger:
+ syncDone() {
+ // Resolve our internal promise:
+ this.promiseResolver();
+ }
+
+ finish():Promise {
+ return Promise.all(this.pendingPromises).then(() => {
+ const endTimeMs = Date.now();
+ const elapsedMs = endTimeMs - this.startTimeMs;
+ const elapsedS = elapsedMs / 1000;
+ console.info(`sync finished in ${elapsedS} seconds`);
+ return true;
+ });
+ }
+
+ receivedPluginStatus(status: IPluginSyncUpdate) {
+ // We don't reset the timer if the status is fail or ok, which are terminal.
+ if(status.status===("started" || "working")) {
+ if(status.status === "started") {
+ this.pluginDrops++;
+ }
+ this.registerTimeOut();
+ }
+ if(status.status === "completed") {
+ this.pluginSuccesses++;
+ this.pluginDrops--;
+ }
+ if(status.status === "failed") {
+ this.pluginFailures++;
+ this.pluginDrops--;
+ }
+ }
+
+ receivedLoggerStatus(status: ILogSyncUpdate) {
+ console.log(">==== LOGGER SYNC ==>", status);
+ // We don't reset the timer if the status is fail or ok, which are terminal.
+ if(status.status===("started" || "working")) {
+ this.registerTimeOut();
+ }
+ if(status.status === "completed") {
+ this.logsSynced = true;
+ }
+ if(status.status === "failed") {
+ this.logsSynced = false;
+ }
+ }
+}
diff --git a/src/storage/dexie-storage.ts b/src/storage/dexie-storage.ts
new file mode 100644
index 00000000..746d5e09
--- /dev/null
+++ b/src/storage/dexie-storage.ts
@@ -0,0 +1,37 @@
+import Dexie from "dexie";
+import { OfflineActivity, LogMessage } from "../types";
+import { IIndexedDBAnswer } from "./storage-facade";
+
+// We need to ensure a version match between data stored and exported
+// version 5: switched from activity to resource_url field for identifying answer's activity
+export const kOfflineAnswerSchemaVersion = 7;
+export interface IDexiePluginRecord {
+ pluginId: number,
+ resourceUrl: string,
+ state: string|null
+}
+
+// Copy and pasted from the example: https://dexie.org/docs/Typescript
+export class DexieStorage extends Dexie {
+ // Declare implicit table properties.
+ // (just to inform Typescript. Instantiated by Dexie in stores() method)
+ logs: Dexie.Table;
+ offlineActivities: Dexie.Table;
+ answers: Dexie.Table; // number = type of the primary key
+ savedPluginStates: Dexie.Table;
+
+ constructor () {
+ // the database was called ActivityPlayer, but changes to the offlineActivities
+ // primary key required deleting that table to upgrade it, so renaming
+ // the database was easier
+ super("ActivityPlayerDb");
+ this.version(kOfflineAnswerSchemaVersion).stores({
+ logs: "++id, activity",
+ answers: "id, resource_url, [resource_url+question_id]",
+ savedPluginStates: "[resourceUrl+pluginId]",
+ offlineActivities: "&resourceUrl" // unique by resourceUrl
+ });
+ }
+}
+
+export const dexieStorage = new DexieStorage();
diff --git a/src/firebase-db.test.ts b/src/storage/firebase-db.test.ts
similarity index 92%
rename from src/firebase-db.test.ts
rename to src/storage/firebase-db.test.ts
index f381cd14..2ba4dc50 100644
--- a/src/firebase-db.test.ts
+++ b/src/storage/firebase-db.test.ts
@@ -1,8 +1,8 @@
import { IRuntimeMetadata } from "@concord-consortium/lara-interactive-api";
-import { setPortalData, setAnonymousPortalData, createOrUpdateAnswer, initializeDB, signInWithToken, setLearnerPluginState, getLearnerPluginStateDocId, getLearnerPluginState } from "./firebase-db";
-import { DefaultManagedInteractive } from "./test-utils/model-for-tests";
-import { getAnswerWithMetadata } from "./utilities/embeddable-utils";
-import { IExportableAnswerMetadata } from "./types";
+import { setPortalData, createOrUpdateAnswer, initializeDB, signInWithToken, setLearnerPluginState, getLearnerPluginStateDocId, getLearnerPluginState } from "./firebase-db";
+import { DefaultManagedInteractive } from "../test-utils/model-for-tests";
+import { getAnswerWithMetadata } from "../utilities/embeddable-utils";
+import { IExportableAnswerMetadata } from "../types";
import firebase from "firebase/app";
import "firebase/firestore";
@@ -49,7 +49,7 @@ describe("Firestore", () => {
expect(signInWithCustomTokenMock).toHaveBeenCalledWith("test");
});
- it("does nothing in the absence of metadata", () => {
+ it("Throws exception without metadata", () => {
const embeddable = {
...DefaultManagedInteractive,
authored_state: `{"version":1,"questionType":"open_response","prompt":", {merge: true});
requestTracker.registerRequest(firestoreSetPromise);
-
return firestoreSetPromise;
}
+export function batchCreateOrUpdateAnswers(answers: Array) {
+ const batch = app.firestore().batch();
+ for(const answer of answers) {
+ const answerDocData = prepareAnswerForFireStore(answer);
+ const doc = app.firestore().doc(answersPath(answer.id));
+ batch.set(doc, answerDocData, {merge: true});
+ }
+ return batch.commit();
+}
+
export const getLearnerPluginStateDocId = (pluginId: number) => {
if (!portalData) {
return undefined;
@@ -283,13 +305,6 @@ export const getLearnerPluginStateDocId = (pluginId: number) => {
return docId.replace(/[.$[\]#/]/g, "_");
};
-// A write-though cache of the learner plugin states is kept as the plugin's learner state is only loaded
-// once at app startup but it is supplied on the plugin init which happens on any page change.
-
-// TODO: change to watch the learner state so that it works across sessions and not just on the same page
-
-const cachedLearnerPluginState: Record = {};
-export const getCachedLearnerPluginState = (pluginId: number) => cachedLearnerPluginState[pluginId] || null;
export const getLearnerPluginState = async (pluginId: number) => {
const docId = getLearnerPluginStateDocId(pluginId);
@@ -297,10 +312,6 @@ export const getLearnerPluginState = async (pluginId: number) => {
return null;
}
- if (cachedLearnerPluginState[pluginId]) {
- return cachedLearnerPluginState[pluginId];
- }
-
let state: string|null = null;
try {
const doc = await app.firestore()
@@ -312,8 +323,6 @@ export const getLearnerPluginState = async (pluginId: number) => {
state = data?.state || null;
} catch (e) {} // eslint-disable-line no-empty
- cachedLearnerPluginState[pluginId] = state;
-
return state;
};
@@ -361,7 +370,30 @@ export const setLearnerPluginState = async (pluginId: number, state: string): Pr
.doc(learnerPluginStatePath(docId))
.set(learnerPluginState);
- cachedLearnerPluginState[pluginId] = state;
+
return state;
};
+
+export const checkIfOnline = () => {
+ return new Promise((resolve) => {
+ /*
+
+ DISABLED FOR NOW: need to decide if we also want to add both the size of the database import
+ and enable the database in the Firebase console. Use a POST request instead.
+
+ const connectedRef = app.database().ref(".info/connected");
+ return connectedRef.once("value")
+ .then(snap => resolve(snap.val() === true))
+ .catch(() => resolve(false));
+ */
+
+ // if online this will result in a 400 error due to the portal token not being included
+ // we don't care about the status code, just that we get a response to check if we are online
+ // NOTE: if this is the final method we need our own POST endpoint that returns 200 instead
+ // of using this (free) external service which may go down
+ return fetch("https://ipapi.co/json/", {method: "POST"})
+ .then(() => resolve(true))
+ .catch(() => resolve(false));
+ });
+};
diff --git a/src/storage/storage-facade.test.ts b/src/storage/storage-facade.test.ts
new file mode 100644
index 00000000..eac6c7ba
--- /dev/null
+++ b/src/storage/storage-facade.test.ts
@@ -0,0 +1,115 @@
+
+import {
+ initStorage, IInitStorageParams,
+ DexieStorageProvider, FireStoreStorageProvider,
+ TrackOfflineResourceUrl, IStorageInterface
+} from "./storage-facade";
+import "firebase/firestore";
+import { IPortalData, PortalJWT } from "../portal-api";
+
+const goodPortalData: IPortalData = {
+ type: "authenticated",
+ contextId: "context-id",
+ database: {
+ appName: "report-service-dev",
+ sourceKey: "localhost",
+ rawFirebaseJWT: "abc"
+ },
+ offering: {
+ id: 1,
+ activityUrl: "http://example/activities/1",
+ rubricUrl: ""
+ },
+ platformId: "https://example",
+ platformUserId: "1",
+ resourceLinkId: "2",
+ resourceUrl: "http://example/resource",
+ toolId: "activity-player.concord.org",
+ userType: "learner",
+ runRemoteEndpoint: "https://example.com/learner/1234",
+ loggingUsername: "1@example.com"
+};
+
+const getGoodPortalJWT = ():PortalJWT => {
+ return {
+ exp: Date.now() / 1000 + 60 * 1000,
+ domain: "test",
+ alg: "alg",
+ iat: Date.now() / 1000,
+ class_info_url: "class_info_url",
+ learner_id: 777,
+ offering_id: 777,
+ uid: 777,
+ user_id: "777",
+ user_type: "learner"
+ };
+};
+
+describe("Storage Facade", () => {
+
+ const storageInitParams: IInitStorageParams = {
+ offline: true,
+ preview: false,
+ name: "report-service-dev"
+ };
+
+ let storage: IStorageInterface | null = null;
+
+ describe("initStorage", () => {
+ it("it returns a Dexie storage provider if we are offline", async () => {
+ storageInitParams.offline = true;
+ storage = await initStorage(storageInitParams);
+ expect(storage).toBeInstanceOf(DexieStorageProvider);
+ });
+
+ it("it returns a FireBase storage provider if we are offline", async () => {
+ storageInitParams.offline = false;
+ storage = await initStorage(storageInitParams);
+ expect(storage).toBeInstanceOf(FireStoreStorageProvider);
+ });
+ });
+
+
+
+ describe("canSyncData", () => {
+ describe("DexieStorageProvider", () => {
+ beforeEach(async () => {
+ storageInitParams.offline = true;
+ storage = await initStorage(storageInitParams);
+ storage.setPortalData(goodPortalData);
+ });
+
+ describe("With valid portal JWT", () => {
+ beforeEach(() => goodPortalData.portalJWT = getGoodPortalJWT());
+ describe("When on the correct activity", () => {
+ beforeEach(() => TrackOfflineResourceUrl(goodPortalData.resourceUrl));
+
+ it("can Sync", async () => {
+ expect(storage?.canSyncData()).toBeTruthy();
+ });
+ });
+
+ describe("When on a different activity", () => {
+ beforeEach(() => TrackOfflineResourceUrl("bogus"));
+ it("Can't Sync", async () => {
+ expect(storage?.canSyncData()).toBeFalsy();
+ });
+ });
+ });
+
+ describe("Without a portal JWT", () => {
+ beforeEach(() => goodPortalData.portalJWT = undefined);
+ it("can't Sync", async () => {
+ expect(storage?.canSyncData()).toBeFalsy();
+ });
+ });
+ });
+
+ describe("FireStoreStorageProvider", () => {
+ beforeEach(() => storageInitParams.offline = false);
+ it("can't sync", async () => {
+ expect(storage?.canSyncData()).toBeFalsy();
+ });
+ });
+ });
+});
diff --git a/src/storage/storage-facade.ts b/src/storage/storage-facade.ts
new file mode 100644
index 00000000..dd9d32e9
--- /dev/null
+++ b/src/storage/storage-facade.ts
@@ -0,0 +1,517 @@
+// import { WrappedDBAnswer, FirebaseAppName } from "./firebase-db";
+import * as FirebaseImp from "./firebase-db";
+import { fetchPortalData, IAnonymousPortalData, IPortalData } from "../portal-api";
+import { IExportableAnswerMetadata } from "../types";
+import { dexieStorage, IDexiePluginRecord, kOfflineAnswerSchemaVersion } from "./dexie-storage";
+import { refIdToAnswersQuestionId } from "../utilities/embeddable-utils";
+import { DataSyncTracker } from "./data-sync-tracker";
+import Dexie from "dexie";
+
+export interface IInitStorageParams {
+ name: FirebaseImp.FirebaseAppName,
+ preview: boolean,
+ offline: boolean
+}
+export interface IDBInitializer extends IInitStorageParams{
+ portalData: IPortalData | IAnonymousPortalData
+}
+
+
+interface IAnswerWatcherCallback { (answer: IWrappedDBAnswer): void }
+type IQuestionWatchersRecord = Record>;
+
+export interface IWrappedDBAnswer {
+ meta: IExportableAnswerMetadata;
+ interactiveState: any;
+}
+
+export type IIndexedDBAnswer = IExportableAnswerMetadata & { resource_url: string };
+
+export type ExportableActivity = {
+ resource_url: string,
+ filename: string,
+ version: number,
+ answers: IIndexedDBAnswer[],
+ pluginStates: IDexiePluginRecord[]
+}
+
+export const TrackOfflineResourceUrl = (newId: string) => {
+ _currentOfflineResourceUrl = newId;
+};
+
+let _currentOfflineResourceUrl = "/testactivity.json";
+
+
+// A write-though cache of the learner plugin states is kept as the plugin's
+// learner state is only loaded once at app startup but it is supplied on the
+// plugin init which happens on any page change.
+
+// TODO: change to watch the learner state so that it works across sessions and
+// not just on the same page
+
+const cachedLearnerPluginState: Record = {};
+
+export const getCachedLearnerPluginStateKey = (pluginId: number, resourceUrl: string) => `${resourceUrl}_${pluginId}`;
+
+export const getCachedLearnerPluginState = (pluginId: number, resourceUrl: string) =>
+ cachedLearnerPluginState[getCachedLearnerPluginStateKey(pluginId, resourceUrl)] || null;
+
+export const setCachedLearnerPluginState = (pluginId: number, resourceUrl: string, value: string|null) =>
+ cachedLearnerPluginState[getCachedLearnerPluginStateKey(pluginId, resourceUrl)] = value;
+
+export const docToWrappedAnswer = (doc: firebase.firestore.DocumentData) => {
+ const getInteractiveState = () => {
+ const reportState = JSON.parse(doc.report_state);
+ const returnObject = JSON.parse(reportState.interactiveState);
+ return returnObject;
+ };
+
+ const interactiveState = getInteractiveState();
+ const wrappedAnswer: IWrappedDBAnswer = {
+ meta: doc as IExportableAnswerMetadata,
+ interactiveState
+ };
+ return wrappedAnswer;
+};
+
+const activityExportFileName = (activity: string) => {
+ const d = new Date();
+ const year = (d.getFullYear()).toString();
+ let month = (d.getMonth() + 1).toString();
+ let day = (d.getDate()).toString();
+
+ if (month.length < 2) {
+ month = "0" + month;
+ }
+ if (day.length < 2) {
+ day = "0" + day;
+ }
+
+ // get the activity name - or improvise
+
+ return ["Activity_", activity, "_", year, month, day].join("");
+};
+
+export interface IStorageInterface {
+ // These seem to be FireStore specific:
+ onSaveTimeout?: (handler: () => void) => void,
+ onSaveAfterTimeout?: (handler: () => void) => void,
+
+ setPortalData: (_portalData: IPortalData | IAnonymousPortalData) => void,
+ initializeDB: (initializer: IDBInitializer) => Promise,
+ // initializeAnonymousDB?: (preview: boolean) => Promise
+ // signInWithToken?: (rawFirestoreJWT: string) => Promise,
+
+ getPortalData: () => IPortalData | IAnonymousPortalData | null,
+
+ // These are directly related to storing student answers and fetching them back
+ watchAnswer(embeddableRefId: string, callback: (wrappedAnswer: IWrappedDBAnswer | null) => void): () => void
+ watchAllAnswers: (callback: (wrappedAnswer: IWrappedDBAnswer[]) => void) => void,
+ createOrUpdateAnswer: (answer: IExportableAnswerMetadata) => void,
+ getLearnerPluginState: (pluginId: number, resourceUrl: string) => Promise,
+ setLearnerPluginState: (pluginId: number, resourceUrl: string, state: string) => Promise,
+
+ // for saving a whole activity to JSON
+ exportActivityToJSON: (activityId?: string) => Promise,
+ importStudentAnswersFromJSONFile: (studentAnswers: string, filename: string) => boolean,
+ canSyncData(): boolean,
+ canProvideStudentReport(): boolean,
+ syncData(): Promise,
+}
+
+export class FireStoreStorageProvider implements IStorageInterface {
+ portalData: IPortalData|IAnonymousPortalData;
+ isPreview: boolean;
+ onSaveTimeout(handler: () => void) {
+ return FirebaseImp.onFirestoreSaveTimeout(handler);
+ }
+
+ onSaveAfterTimeout (handler: () => void) {
+ return FirebaseImp.onFirestoreSaveAfterTimeout(handler);
+ }
+
+ async initializeDB (initializer: IDBInitializer) {
+ const {preview, portalData} = initializer;
+ this.isPreview = preview;
+ this.setPortalData(portalData);
+ try {
+ if(portalData.type === "authenticated") {
+ const token = portalData.database.rawFirebaseJWT;
+ await FirebaseImp.initializeDB({
+ name: portalData.database.appName,
+ preview});
+ await FirebaseImp.signInWithToken(token);
+ } else {
+ await FirebaseImp.initializeAnonymousDB(preview);
+ // No sign-in required for anonymous
+ }
+ }
+ catch (err) {
+ console.error("DB authentication error:", err);
+ }
+ }
+
+ setPortalData(portalData: IPortalData | IAnonymousPortalData) {
+ FirebaseImp.setPortalData(portalData);
+ }
+
+ getPortalData() {
+ return FirebaseImp.getPortalData();
+ }
+
+ // Saving and Loading student work
+ watchAnswer(embeddableRefId: string, callback: (wrappedAnswer: IWrappedDBAnswer | null) => void){
+ return FirebaseImp.watchAnswer(embeddableRefId, callback);
+ }
+
+ watchAllAnswers(callback: (wrappedAnswer: IWrappedDBAnswer[]) => void){
+ return FirebaseImp.watchAllAnswers(callback);
+ }
+
+ // Save an answer to Firebase
+ createOrUpdateAnswer(answer: IExportableAnswerMetadata) {
+ return FirebaseImp.createOrUpdateAnswer(answer);
+ }
+ batchCreateOrUpdateAnswers(answers: Array) {
+ return FirebaseImp.batchCreateOrUpdateAnswers(answers);
+ }
+
+ async getLearnerPluginState(pluginId: number, resourceUrl: string) {
+ if (getCachedLearnerPluginState(pluginId, resourceUrl)) {
+ return getCachedLearnerPluginState(pluginId, resourceUrl);
+ }
+ const state = await FirebaseImp.getLearnerPluginState(pluginId);
+ setCachedLearnerPluginState(pluginId, resourceUrl, state);
+ return state;
+ }
+
+ async setLearnerPluginState(pluginId: number, resourceUrl: string, state: string){
+ FirebaseImp.setLearnerPluginState(pluginId, state);
+ setCachedLearnerPluginState(pluginId, resourceUrl, state);
+ return state;
+ }
+
+ // TODO: Save activity to local JSON file and allow reloading from file
+ exportActivityToJSON(activityId?: string) {
+ return Promise.reject("Not yet implemented for Firebase Storage");
+ }
+
+ importStudentAnswersFromJSONFile(studentAnswers: string, filename: string) {
+ return true;
+ }
+
+ // We are FireStore, so our data is synced by default....
+ canSyncData() { return false; }
+ syncData() { return Promise.resolve(false); }
+
+ canProvideStudentReport() {
+ return !this.isPreview;
+ }
+
+ signOut() {
+ FirebaseImp.signOut();
+ }
+}
+
+
+export class DexieStorageProvider implements IStorageInterface {
+ portalData: IPortalData|IAnonymousPortalData;
+ haveFireStoreConnection: boolean;
+ answerWatchers: Record;
+
+ constructor(){
+ this.haveFireStoreConnection = false;
+ this.answerWatchers = {};
+ }
+
+ async initializeDB (initializer: IDBInitializer) {
+ const {portalData} = initializer;
+ this.setPortalData(portalData);
+ }
+
+ setPortalData(_portalData: IPortalData | IAnonymousPortalData) {
+
+ this.portalData = _portalData;
+ }
+
+ createOrUpdateAnswer(answer: IExportableAnswerMetadata) {
+ const idxDBAnswer = answer as IIndexedDBAnswer;
+ idxDBAnswer.resource_url = _currentOfflineResourceUrl;
+ dexieStorage.answers.put(idxDBAnswer);
+ const activityAnswerWatchers = this.answerWatchers[_currentOfflineResourceUrl];
+ if (!activityAnswerWatchers || !answer.question_id) {
+ return;
+ }
+ const questionAnswerWatchers = activityAnswerWatchers[answer.question_id];
+ if (!questionAnswerWatchers) {
+ return;
+ }
+ questionAnswerWatchers.forEach((callback:IAnswerWatcherCallback) => {
+ callback(docToWrappedAnswer(answer));
+ });
+ }
+
+ getPortalData() {
+ return this.portalData;
+ }
+
+ watchAllAnswers(callback: (wrappedAnswer: IWrappedDBAnswer[]) => void){
+ console.log("WatchAllAnsweres called");
+ console.log(`current resource: ${_currentOfflineResourceUrl}`);
+
+ const foundAnswers = dexieStorage
+ .answers
+ .where({resource_url: _currentOfflineResourceUrl})
+ .toArray();
+ return foundAnswers.then((answers) => {
+ console.dir(answers);
+ const response = answers.map( (a) => docToWrappedAnswer(a));
+ callback(response);
+ });
+ }
+
+ watchAnswer(embeddableRefId: string, callback: (wrappedAnswer: IWrappedDBAnswer | null) => void) {
+ const questionId = refIdToAnswersQuestionId(embeddableRefId);
+ const getAnswerFromIndexDB = (qID: string) => {
+ const foundAnswers = dexieStorage
+ .answers
+ .where({resource_url: _currentOfflineResourceUrl, question_id: qID})
+ .toArray();
+ return foundAnswers.then((answers) => {
+ return answers[0];
+ });
+ };
+
+ let activityAnswerWatchers = this.answerWatchers[_currentOfflineResourceUrl];
+ if (!activityAnswerWatchers) {
+ activityAnswerWatchers = {};
+ this.answerWatchers[_currentOfflineResourceUrl] = activityAnswerWatchers;
+ }
+
+ let questionAnswerWatchers = activityAnswerWatchers[questionId];
+ if (!questionAnswerWatchers) {
+ questionAnswerWatchers = [];
+ activityAnswerWatchers[questionId] = questionAnswerWatchers;
+ }
+
+ questionAnswerWatchers.push(callback);
+
+ getAnswerFromIndexDB(questionId).then( (answer: IIndexedDBAnswer|null) => {
+ if (answer) {
+ callback(docToWrappedAnswer(answer));
+ } else {
+ callback(null);
+ }
+ });
+ // TODO: We are supposed to return a function that will stop observing the answer ...
+ // We aren't actually watching anything...
+ return ()=>null;
+ }
+
+ async exportActivityToJSON(activityId?: string) {
+ const currentActivityId = activityId ? activityId : _currentOfflineResourceUrl;
+ const activityShortId = currentActivityId.indexOf("/") > -1 ? currentActivityId.substr(currentActivityId.lastIndexOf("/")+1).replace(".json", "") : currentActivityId;
+ const filename = activityExportFileName(activityShortId);
+
+ const getAllAnswersFromIndexDB = () => dexieStorage
+ .answers
+ .where({resource_url: _currentOfflineResourceUrl})
+ .toArray();
+
+ const getAllPluginStates = () => dexieStorage
+ .savedPluginStates
+ .where("[resourceUrl+pluginId]").between(
+ [_currentOfflineResourceUrl, Dexie.minKey],
+ [_currentOfflineResourceUrl, Dexie.maxKey])
+ .toArray();
+
+ const exportableActivity: ExportableActivity = {
+ resource_url: currentActivityId,
+ filename, version: kOfflineAnswerSchemaVersion,
+ answers: [],
+ pluginStates: [],
+ };
+
+
+ await getAllAnswersFromIndexDB().then((answers: IIndexedDBAnswer[] | null) => {
+ if (answers) {
+ exportableActivity.answers = answers;
+ return exportableActivity;
+ }
+ });
+ await getAllPluginStates().then((states: IDexiePluginRecord[]) => {
+ if(states) {
+ exportableActivity.pluginStates = states;
+ }
+ });
+ return exportableActivity;
+ }
+
+ importStudentAnswersFromJSONFile(studentAnswers: string, filename: string) {
+
+ const verifyActivityImport = (answers: ExportableActivity): boolean => {
+ // TODO:
+ // Could check the file name is in the answer file (unsure if this helps?)
+ // Check if the student that saved the file is the same as the logged in user?
+ // Warn that uploading answers will overwrite current answers (do we want this, or do we want to only update empty answers?)
+
+ if (!answers) {
+ return false;
+ }
+ if (!("resource_url" in answers)) {
+ return false;
+ }
+ if (!("version" in answers)){
+ return false;
+ }
+ if (!answers.version || answers.version <= 0 || answers.version > kOfflineAnswerSchemaVersion) {
+ return false;
+ }
+
+ console.log(`The file ${filename} appears valid`);
+ return true;
+ };
+
+ try {
+ const parsedAnswers = JSON.parse(studentAnswers) as ExportableActivity;
+ if (verifyActivityImport(parsedAnswers)) {
+ // Import answers to indexedDB
+ parsedAnswers.answers.forEach((answer: IIndexedDBAnswer) => {
+ const idxDBAnswer = answer as IIndexedDBAnswer;
+ // TODO: what happens if the answers loaded are for a different activity?
+ idxDBAnswer.resource_url = answer.resource_url;
+ dexieStorage.answers.put(idxDBAnswer);
+ });
+ return true;
+ } else {
+ return false;
+ }
+
+ } catch (ex) {
+ console.log(ex);
+ return false;
+ }
+ }
+
+ async getLearnerPluginState(pluginId: number, resourceUrl: string) {
+ if (getCachedLearnerPluginState(pluginId, resourceUrl)) {
+ return getCachedLearnerPluginState(pluginId, resourceUrl);
+ }
+ const record = await dexieStorage.savedPluginStates.get({pluginId, resourceUrl});
+ const state = record?.state || null;
+ setCachedLearnerPluginState(pluginId, resourceUrl, state);
+ return state;
+ }
+
+ async setLearnerPluginState(pluginId: number, resourceUrl: string, state: string){
+ dexieStorage.savedPluginStates.put({pluginId, resourceUrl, state});
+ setCachedLearnerPluginState(pluginId, resourceUrl, state);
+ return state;
+ }
+
+ canSyncData() {
+ const portalToken = (this.portalData as IPortalData)?.portalJWT;
+ const correctActivity = this.portalData.resourceUrl === _currentOfflineResourceUrl;
+ if(portalToken) {
+ const { exp } = portalToken;
+ const unixTimeStamp = Math.floor(Date.now()/1000);
+ const tokenStillValid = unixTimeStamp < exp;
+ return tokenStillValid && correctActivity;
+ }
+ return false;
+ }
+
+ ensureFirebaseConnection(): Promise {
+ const fsProvider = new FireStoreStorageProvider();
+ if(! this.haveFireStoreConnection) {
+ const portalData = this.portalData;
+ const appName = portalData?.database.appName ?? "report-service-dev";
+ return fsProvider
+ .initializeDB({name: appName, preview: false, offline: false, portalData})
+ .then(() => {
+ this.haveFireStoreConnection = true;
+ return fsProvider;
+ })
+ .catch((e) => {
+ console.error(e);
+ console.warn("reinitialization of database?");
+ return Promise.resolve(fsProvider);
+ });
+ }
+ return Promise.resolve(fsProvider);
+ }
+
+ syncData(): Promise {
+ const portalData = this.portalData;
+ if(portalData) {
+ // DataSyncTracker will emit an event that tells plugins
+ // that we are online, and its time to save data:
+ // NOTE: We wait 5 seconds to hear from plugins so saving will never
+ // complete in less than 5 seconds.
+ const mySyncTracker = new DataSyncTracker(60 * 30, 5);
+ const portalResourceUrl = portalData.resourceUrl;
+ // Save student answers ...
+ this.ensureFirebaseConnection()
+ .then((fsProvider) => {
+ dexieStorage.answers
+ .where({resource_url: portalResourceUrl})
+ .toArray()
+ .then((answers) => {
+ mySyncTracker.addPromise(fsProvider.batchCreateOrUpdateAnswers(answers));
+ });
+ });
+
+ // Save learner plugin states ...
+ this.ensureFirebaseConnection()
+ .then((fsProvider) => {
+ dexieStorage
+ .savedPluginStates
+ .where("[resourceUrl+pluginId]").between(
+ [portalResourceUrl, Dexie.minKey],
+ [portalResourceUrl, Dexie.maxKey])
+ .toArray()
+ .then((savedPluginStates) => {
+ for(const pState of savedPluginStates) {
+ const {pluginId, state} = pState;
+ if(state) {
+ // We could opt for batch operations in the future...
+ mySyncTracker.addPromise(fsProvider.setLearnerPluginState(pluginId, portalResourceUrl, state));
+ }
+ }
+ });
+ });
+ return mySyncTracker.start()
+ .catch((e) => {
+ console.error("Could not sync local indexDB to FireStore:");
+ console.error(e);
+ this.haveFireStoreConnection = false;
+ return Promise.resolve(false);
+ });
+ }
+ return Promise.resolve(false);
+ }
+
+ canProvideStudentReport() {
+ return this.canSyncData();
+ }
+}
+
+let storageInstance: IStorageInterface;
+
+export const initStorage = async (config: IInitStorageParams) => {
+ const portalData = await fetchPortalData();
+ const initConfig = { portalData, ...config};
+
+ if(config?.offline) {
+ storageInstance = new DexieStorageProvider();
+ }
+ else {
+ storageInstance = new FireStoreStorageProvider();
+ }
+ await storageInstance.initializeDB(initConfig);
+ return storageInstance;
+};
+
+export const getStorage = () => {
+ return storageInstance;
+};
diff --git a/src/student-info.ts b/src/student-info.ts
new file mode 100644
index 00000000..26ffab91
--- /dev/null
+++ b/src/student-info.ts
@@ -0,0 +1,241 @@
+import { fetchPortalData, IPortalData } from "./portal-api";
+import { IStorageInterface } from "./storage/storage-facade";
+
+export const DEFAULT_STUDENT_NAME = "Anonymous";
+export const DEFAULT_STUDENT_LOGGING_USERNAME = "0@anonymous";
+
+const DEFAULT_TEACHER_NAME = "A teacher";
+const STUDENT_LOCAL_STORAGE_KEY = "ActivityPlayerStudent";
+const DEFAULT_CLASS_HASH = ""; // From `app.tsx` 2021-02-25
+const DEFAULT_RUN_REMOTE_ENDPOINT= ""; // From `app.tsx` 2021-02-25
+
+
+export enum Role { "student", "teacher", "unknown"}
+
+/*
+The purpose of this class is to allow us to reconcile users and their data
+at a later time.
+*/
+
+interface IAnonymousRun {
+ activityUrl: string,
+ runKey: string,
+}
+
+interface IPortalRun extends IAnonymousRun {
+ offeringId: string,
+ runRemoteEndpoint: string,
+ learnerKey: string,
+ className: string,
+ classID: string,
+ contextID: string
+}
+
+type Run = IAnonymousRun | IPortalRun;
+
+
+
+interface IStudentRecord {
+ name: string,
+ loggingUsername: string;
+ role: Role,
+ teacherName: string,
+ platformUserId: string,
+ runs: Array,
+ platformId?: string
+ rawPortalData?: IPortalData
+}
+
+export class StudentInfo implements IStudentRecord {
+ name: string;
+ loggingUsername: string;
+ teacherName: string;
+ platformUserId: string;
+ role: Role;
+ runs: Run[];
+ rawPortalData: IPortalData;
+ dataReady: boolean;
+ storage: IStorageInterface|null;
+ preview: boolean;
+ private _validTokens: boolean;
+
+ constructor(storage: IStorageInterface) {
+ // Start with defaults.
+ // Calling async operation init() will load real values.
+ this.storage = storage;
+ this.loadDefaults();
+ }
+
+ private loadDefaults() {
+ this.role = Role.student;
+ this.name = DEFAULT_STUDENT_NAME;
+ this.loggingUsername = DEFAULT_STUDENT_LOGGING_USERNAME;
+ this.teacherName = DEFAULT_TEACHER_NAME;
+ this._validTokens = false;
+ }
+
+ public init(): Promise {
+ return fetchPortalData({includeClassData: true})
+ .then( (portalData: IPortalData) => this.updateFromPortalData(portalData))
+ .catch( () => this.updateFromIndexedDB());
+ }
+
+ public isAuthenticated() : boolean{
+ return this._validTokens === true;
+ }
+
+ // TODO: Anonymous users can also send data ...
+ public canSendData() : boolean {
+ return this.isAuthenticated();
+ }
+
+ public canChangeName() : boolean {
+ return (! (this.platformUserId && this.platformUserId.length >= 1));
+ }
+
+ public hasValidTeacherName() : boolean{
+ return this.teacherName !== DEFAULT_TEACHER_NAME;
+ }
+
+ public hasValidStudentName() {
+ return this.name !== DEFAULT_STUDENT_NAME;
+ }
+
+ public getClassHash() {
+ return this.rawPortalData?.contextId ?? DEFAULT_CLASS_HASH;
+ }
+
+ public getRunRemoteEndpoint() {
+ return this.rawPortalData?.runRemoteEndpoint ?? DEFAULT_RUN_REMOTE_ENDPOINT;
+ }
+
+ public setName(newName: string) {
+ if(this.platformUserId && this.platformUserId.length >= 1) {
+ // Cant change an authenticated students name
+ return false;
+ }
+ else {
+ this.name=newName;
+ window.localStorage.setItem(STUDENT_LOCAL_STORAGE_KEY, this.serializeData());
+ return true;
+ }
+ }
+
+ private validateSerializedData(data: IStudentRecord) {
+ // TODO: More careful inspection
+ return (
+ (data.name?.length >= 1) &&
+ (data.teacherName?.length >= 1)
+ );
+ }
+
+ private updateFromIndexedDB() {
+ // We have to load any data we can from the DB, but tokens will be stale.
+ // TODO: remove stale tokens if the exist
+ console.log("LOADING FROM LOCAL STORAGE");
+ const localStorageStudentInfo = localStorage.getItem(STUDENT_LOCAL_STORAGE_KEY) ?? "{}";
+ this.loadSerializedData(localStorageStudentInfo);
+ this._validTokens=false;
+ }
+
+ private loadSerializedData(json: string) : boolean{
+ try {
+ const data: IStudentRecord = JSON.parse(json) as IStudentRecord;
+ if(this.validateSerializedData(data)) {
+ this.loadData(data);
+ return true;
+ }
+ } catch (e) {
+ console.error("Failed to load serialized student data");
+ console.error(e);
+ }
+ return false;
+ }
+
+ private serializeData() {
+ const data: IStudentRecord = {
+ name: this.name,
+ loggingUsername: this.loggingUsername,
+ role: this.role,
+ teacherName: this.teacherName,
+ platformUserId: this.platformUserId,
+ runs: this.runs,
+ rawPortalData: this.rawPortalData
+ };
+ return JSON.stringify(data);
+ }
+
+ private loadData(data: IStudentRecord ) {
+ this.name = data.name ?? DEFAULT_STUDENT_NAME;
+ this.loggingUsername = data.loggingUsername ?? DEFAULT_STUDENT_LOGGING_USERNAME;
+ this.teacherName = data.name ?? DEFAULT_TEACHER_NAME;
+ this.platformUserId = data.platformUserId;
+ this.runs = data.runs;
+ this.role = data.role;
+ if (data.rawPortalData) {
+ this.rawPortalData = data.rawPortalData;
+ }
+ }
+
+ private updateFromPortalData(portalData: IPortalData) {
+ // Raw Portal Data JWT includes expiration time (`exp`) and Issued at (`iat`)
+ // exp: 1614635737
+ // iat: 1614632137
+ this.rawPortalData = portalData;
+ this.name = portalData.fullName ?? DEFAULT_STUDENT_NAME;
+ this.loggingUsername = portalData.loggingUsername ?? DEFAULT_STUDENT_LOGGING_USERNAME;
+ this.teacherName = portalData?.classInfo?.teachers[0]?.fullName ?? DEFAULT_TEACHER_NAME;
+ this.platformUserId = portalData.platformUserId;
+ this._validTokens = true;
+ this.saveSerializedLocalData();
+ }
+
+ private saveSerializedLocalData() {
+ window.localStorage.setItem(STUDENT_LOCAL_STORAGE_KEY, this.serializeData());
+ }
+
+}
+
+
+/**
+ * To match LARA we would normally also include a tool_user_id, but the activity player
+ * keeps no user ids of its own.
+ */
+// export interface ILTIPartial {
+// platform_id: string; // portal
+// platform_user_id: string; // Portal user_id
+// context_id: string; // class hash
+// resource_link_id: string; // offering ID
+// resource_url: string; // Activity or sequence ID
+// run_key: string; // Unique run identifier
+// source_key: string;
+// tool_id: string;
+// }
+
+// export interface IAnonymousMetadataPartial {
+// resource_url: string;
+// run_key: string;
+// source_key: string;
+// tool_id: string;
+// tool_user_id: "anonymous";
+// platform_user_id: string;
+// }
+
+
+// What data gets set in the Activity Player URL when launched from portal
+// http://localhost:11000/activity=https%3A%2F%2Fauthoring.staging.concord.org%2Fapi%2Fv1%2Factivities%2F20926.json?token=123&domain=https://learn.staging.concord.org/&domain_uid=383
+
+// if there is a token, get some JWTs
+// Portal JWT
+// FireStore JWT
+// Inspect the JWT for class info
+
+// You can pull this data out of the portal_api.ts file
+// Launch URL instead of URL:
+// http://localhost:11000/activity=https%3A%2F%2Fauthoring.staging.concord.org%2Fapi%2Fv1%2Factivities%2F20926.json?class_info_url=https%3A%2F%2Flearn.staging.concord.org%2Fapi%2Fv1%2Fclasses%2F1&context_id=b1c1cab9c696a5cdbeaf700d704ac9f848df87907d008534&domain=https%3A%2F%2Flearn.staging.concord.org%2F&domain_uid=383&externalId=2029&logging=true&platform_id=https%3A%2F%2Flearn.staging.concord.org&platform_user_id=383&resource_link_id=1610&returnUrl=https%3A%2F%2Flearn.staging.concord.org%2Fdataservice%2Fexternal_activity_data%2F4bd0b794-cb90-43fe-8598-2c85924efefc
+/*
+
+http://localhost:11000/index.html?class_info_url=https://learn.staging.concord.org/api/v1/classes/1&context_id=b1c1cab9c696a5cdbeaf700d704ac9f848df87907d008534&domain=https://learn.staging.concord.org/&domain_uid=383&externalId=2029&logging=true&platform_id=https://learn.staging.concord.org&platform_user_id=383&resource_link_id=1610&returnUrl=https://learn.staging.concord.org/dataservice/external_activity_data/4bd0b794-cb90-43fe-8598-2c85924efefc
+
+*/
+
diff --git a/src/types.ts b/src/types.ts
index ca73f289..98aa4746 100644
--- a/src/types.ts
+++ b/src/types.ts
@@ -1,3 +1,5 @@
+import { Role } from "./student-info";
+
export type Mode = "runtime" | "authoring" | "report";
export interface IframePhone {
@@ -183,11 +185,11 @@ export interface IReportState {
*/
export interface ILTIPartial {
platform_id: string; // portal
- platform_user_id: string;
+ platform_user_id: string; // Portal user_id
context_id: string; // class hash
- resource_link_id: string; // offering ID
- resource_url: string;
- run_key: string;
+ resource_link_id: string; // offering ID
+ resource_url: string; // Activity or sequence ID
+ run_key: string; // Unique run identifier
source_key: string;
tool_id: string;
// This is not an LTI property but it is required in our authenticated answers
@@ -264,3 +266,53 @@ export interface IAnonymousLearnerPluginState extends IAnonymousMetadataPartial
pluginId: number;
state: string;
}
+
+export interface OfflineManifestActivity {
+ name: string;
+ resourceUrl: string;
+ contentUrl: string;
+}
+export interface OfflineManifest {
+ name: string
+ activities: OfflineManifestActivity[];
+ cacheList: string[]
+}
+
+export interface OfflineActivity extends OfflineManifestActivity {
+ manifestName: string;
+ order: number;
+ // TBD: add class info once that is figured out
+}
+
+// This is a combination of the standard service worker states:
+// installing, installed, activating, activated, redundant
+// https://developer.mozilla.org/en-US/docs/Web/API/ServiceWorker/state
+// With additional states for the initial "unknown" startup state and
+// a "controlling" state which isn't captured as a "state" by the service worker API
+// a "parsed" state is added to satisfy the ServiceWorker types,
+// this state is documented here: https://bitsofco.de/the-service-worker-lifecycle/
+// but it isn't lised in the MDN article above
+// The actual status is more complex than this because there can be external
+// service workers, but perhaps this simplified list
+// will be good enough for deciding what to do with the UI
+export type ServiceWorkerStatus = "unknown" | "parsed" | "installing" | "installed" | "activating" | "activated" | "redundant" | "controlling";
+
+export interface LogMessage {
+ application: string;
+ run_remote_endpoint?: string;
+ username: string;
+ role: Role;
+ classHash: string;
+ session: string;
+ appMode: string;
+ sequence: string | undefined;
+ sequenceActivityIndex: number;
+ activity: string | undefined,
+ activityPage: number;
+ time: number;
+ event: string;
+ event_value: any;
+ parameters: any;
+ interactive_id: string | undefined,
+ interactive_url: string | undefined,
+}
diff --git a/src/utilities/activity-utils.test.ts b/src/utilities/activity-utils.test.ts
index 3fe5b4c6..d1fa7344 100644
--- a/src/utilities/activity-utils.test.ts
+++ b/src/utilities/activity-utils.test.ts
@@ -1,12 +1,18 @@
+import fetch from "jest-fetch-mock";
+
import { Activity } from "../types";
import { isQuestion, isEmbeddableSectionHidden, getVisibleEmbeddablesOnPage, VisibleEmbeddables,
- EmbeddableSections, getPageSectionQuestionCount, numQuestionsOnPreviousPages, enableReportButton, getPagePositionFromQueryValue } from "./activity-utils";
+ EmbeddableSections, getPageSectionQuestionCount, numQuestionsOnPreviousPages, enableReportButton, getPagePositionFromQueryValue, isNotSampleActivityUrl, orderedQuestionsOnPage, isExternalOrModelsResourcesUrl, getAllUrlsInActivity, removeDuplicateUrls, rewriteModelsResourcesUrl } from "./activity-utils";
import _activityHidden from "../data/sample-activity-hidden-content.json";
import _activity from "../data/sample-activity-multiple-layout-types.json";
+import _glossaryActivity from "../data/sample-activity-glossary-plugin.json";
import { DefaultTestActivity } from "../test-utils/model-for-tests";
+(window as any).fetch = fetch;
+
const activityHidden = _activityHidden as unknown as Activity;
const activity = _activity as unknown as Activity;
+const glossaryActivity = _glossaryActivity as unknown as Activity;
describe("Activity utility functions", () => {
it("determines if embeddable is a question", () => {
@@ -94,4 +100,121 @@ describe("Activity utility functions", () => {
expect(getPagePositionFromQueryValue(activity, "page_2000")).toBe(2);
expect(getPagePositionFromQueryValue(activity, "page_3000")).toBe(3);
});
+
+ it("determines if an activity url is not a sample activity", () => {
+ expect(isNotSampleActivityUrl("foo")).toBe(false);
+ expect(isNotSampleActivityUrl("http://example.com/foo")).toBe(true);
+ expect(isNotSampleActivityUrl("offline-activities/foo")).toBe(true);
+ });
+
+ it("Returns an ordered list of questions, taking into account the layout of sections", () => {
+ const page = activity.pages[0];
+ const expectedRefIds = [
+ "319-ManagedInteractive", // In header block, but defined last
+ "312-ManagedInteractive", // Section is null
+ "313-ManagedInteractive", // Section is null
+ "352-ManagedInteractive" // Section is null
+ ];
+ const foundRefIds = orderedQuestionsOnPage(page).map( e=> e.embeddable.ref_id);
+ expect(foundRefIds).toEqual(expectedRefIds);
+ // In the hidden activity we only expect to find:
+ // page0: 2 visible, page1: no visible, page2: 2 visible, page3: 0 visible
+ expect(orderedQuestionsOnPage(activityHidden.pages[0]).length).toEqual(2);
+ expect(orderedQuestionsOnPage(activityHidden.pages[1]).length).toEqual(0);
+ expect(orderedQuestionsOnPage(activityHidden.pages[2]).length).toEqual(2);
+ expect(orderedQuestionsOnPage(activityHidden.pages[3]).length).toEqual(0);
+ });
+
+ it("determines if string is an external or models resources url", () => {
+ expect(isExternalOrModelsResourcesUrl("http://example.com")).toBe(true);
+ expect(isExternalOrModelsResourcesUrl("https://example.com")).toBe(true);
+ expect(isExternalOrModelsResourcesUrl("models-resources/foo")).toBe(true); // models-resources is special as it is proxied
+ expect(isExternalOrModelsResourcesUrl("bar")).toBe(false);
+ });
+
+ it("removes duplicate urls", () => {
+ expect(removeDuplicateUrls([
+ "http://example.com/",
+ "http://example.com/foo",
+ "http://example.com/bar",
+ "http://example.com/",
+ "http://example.com/foo"
+ ])).toEqual([
+ "http://example.com/",
+ "http://example.com/foo",
+ "http://example.com/bar"
+ ]);
+ });
+
+ it("gets all urls in an activity including glossary urls", async () => {
+
+ // first test an activity with no glossary
+ let urls = await getAllUrlsInActivity(activity);
+ expect(urls).toEqual([
+ "https://upload.wikimedia.org/wikipedia/commons/c/c1/Six_weeks_old_cat_%28aka%29.jpg",
+ "https://models-resources.concord.org/question-interactives/branch/master/multiple-choice/",
+ "https://models-resources.concord.org/question-interactives/branch/master/open-response/",
+ "https://connected-bio-spaces.concord.org/",
+ "https://s-media-cache-ak0.pinimg.com/originals/73/ec/f3/73ecf348c3ef190be4e8c4a3269fc0d8.jpg",
+ // This is an example of a href link that we wouldn't want to cache,
+ // but at the same time we probably want to know about it to warn the author
+ // This particular one is further complicated because it is inside of a description
+ // that is only shown at authoring time, so our getAllUrlsInActivity could be
+ // smarter about this
+ "https://connected-bio-spaces.concord.org/?authoring",
+ "https://www.wikipedia.org/"
+ ]);
+
+ // mock the glossary json
+ fetch.mockResponse(JSON.stringify({
+ askForUserDefinition: true,
+ autoShowMediaInPopup: false,
+ showSideBar: false,
+ definitions: [
+ {
+ word: "test",
+ definition: "this is a test",
+ image: "https://token-service-files.s3.amazonaws.com/glossary-plugin/ISnn8j8r2veEFjPCx3XH/5cacbe00-1c44-11ea-90e3-39c0ba8d079c-sticky note.svg",
+ zoomImage: "https://token-service-files.s3.amazonaws.com/glossary-plugin/ISnn8j8r2veEFjPCx3XH/5d298f20-1c44-11ea-90e3-39c0ba8d079c-IMG_8603.jpeg"
+ }
+ ]
+ }));
+
+ // then test an activity with a glossary
+ urls = await getAllUrlsInActivity(glossaryActivity);
+ expect(urls).toEqual([
+ "https://models-resources.concord.org/question-interactives/branch/master/open-response/",
+ "https://example.com/fake.mp4",
+ "https://teacher-edition-tips-plugin.concord.org/version/v3.5.6/plugin.js",
+ "https://example.com/manifest.json",
+ "https://token-service-files.s3.amazonaws.com/glossary-plugin/ISnn8j8r2veEFjPCx3XH/glossary.json",
+ "https://glossary-plugin.concord.org/plugin.js",
+ "https://glossary-plugin.concord.org/manifest.json",
+ "https://token-service-files.s3.amazonaws.com/glossary-plugin/ISnn8j8r2veEFjPCx3XH/5cacbe00-1c44-11ea-90e3-39c0ba8d079c-sticky note.svg",
+ "https://token-service-files.s3.amazonaws.com/glossary-plugin/ISnn8j8r2veEFjPCx3XH/5d298f20-1c44-11ea-90e3-39c0ba8d079c-IMG_8603.jpeg"
+ ]);
+ });
+
+ it("rewrites some domains to models-resources with trailing slash", () => {
+ const rewriteMap: Record = {
+ "https://models-resources.concord.org/foo": "models-resources/foo/",
+ "https://models-resources.concord.org/foo/": "models-resources/foo/",
+ "https://models-resources.concord.org/foo/image.jpg": "models-resources/foo/image.jpg",
+ "https://models-resources.s3.amazonaws.com/foo": "models-resources/foo/",
+ "https://models-resources.s3.amazonaws.com/foo/": "models-resources/foo/",
+ "https://models-resources.s3.amazonaws.com/foo/image.jpg": "models-resources/foo/image.jpg",
+ // NOTE how non-rewritten urls do not have slashes appended
+ "https://non-rewritten-domain.com/foo": "https://non-rewritten-domain.com/foo",
+ "https://non-rewritten-domain.com/foo/": "https://non-rewritten-domain.com/foo/"
+ };
+ Object.keys(rewriteMap).forEach(url => {
+ expect(rewriteModelsResourcesUrl(url)).toBe(rewriteMap[url]);
+ });
+ // Check them all with http for completeness
+ Object.keys(rewriteMap).forEach(url => {
+ const httpUrl = url.replace("https://", "http://");
+ const rewrittenUrl = rewriteMap[url].replace("https://", "http://");
+ expect(rewriteModelsResourcesUrl(httpUrl)).toBe(rewrittenUrl);
+ });
+ });
});
diff --git a/src/utilities/activity-utils.ts b/src/utilities/activity-utils.ts
index 6102965b..779c1cf1 100644
--- a/src/utilities/activity-utils.ts
+++ b/src/utilities/activity-utils.ts
@@ -1,6 +1,7 @@
import { Page, Activity, EmbeddableWrapper } from "../types";
import { SidebarConfiguration } from "../components/page-sidebar/sidebar-wrapper";
import { isQuestion as isEmbeddableQuestion } from "./embeddable-utils";
+import { runningInCypress } from "./cypress";
export enum ActivityLayouts {
MultiplePages = 0,
@@ -42,6 +43,9 @@ export const isEmbeddableSectionHidden = (page: Page, section: string | null) =>
};
export const getVisibleEmbeddablesOnPage = (page: Page) => {
+ if(page.is_hidden) {
+ return { interactiveBox: [], headerBlock: [], infoAssessment: [] };
+ }
const headerEmbeddables = isEmbeddableSectionHidden(page, EmbeddableSections.Introduction)
? []
: page.embeddables.filter((e: any) => e.section === EmbeddableSections.Introduction && isVisibleEmbeddable(e));
@@ -163,3 +167,258 @@ export const getPagePositionFromQueryValue = (activity: Activity, pageQueryValue
// note that page is 1 based for the actual pages in the activity.
return Math.max(0, Math.min((parseInt(pageQueryValue, 10) || 0), activity.pages.length));
};
+
+// Look for Json structures (array, object) in value
+export const walkObject = (activityNode: any, stringCallback: (s: string, key?: string) => string) => {
+
+ const tryToWalkJsonString = (key:string) => {
+ const jsonRegex = /^\s*[{[]/;
+ const stringValue = activityNode[key];
+ if(jsonRegex.test(stringValue)) {
+ try {
+ const jsonData = JSON.parse(activityNode[key]);
+ walkObject(jsonData, stringCallback);
+ activityNode[key] = JSON.stringify(jsonData);
+ return true;
+ } catch (e) {} // eslint-disable-line no-empty
+ }
+ return false;
+ };
+
+ if (!activityNode) {
+ return;
+ }
+ if (activityNode instanceof Array) {
+ for (const i in activityNode) {
+ walkObject(activityNode[i], stringCallback);
+ }
+ } else if (typeof activityNode === "object" ) {
+ Object.keys(activityNode).forEach(key => {
+ switch (typeof activityNode[key]) {
+ case "string":
+ if(tryToWalkJsonString(key)) { break; }
+ // Its just a plain string:
+ activityNode[key] = stringCallback(activityNode[key], key);
+ break;
+ case "object":
+ walkObject(activityNode[key], stringCallback);
+ break;
+ }
+ });
+ } else if (typeof activityNode === "string") {
+ if(!tryToWalkJsonString(activityNode)) {
+ activityNode = stringCallback(activityNode);
+ }
+ }
+};
+
+export const rewriteModelsResourcesUrl = (oldUrl: string) => {
+ const httpRegex = /https?:\/\//;
+ if (httpRegex.test(oldUrl)) {
+ const serverRewrite = oldUrl
+ .replace(/https?:\/\/models-resources\.concord\.org/, "models-resources")
+ .replace(/https?:\/\/models-resources\.s3\.amazonaws\.com/, "models-resources");
+
+ // NP: 2021-03-29 S3 resources without terminal slashes seem to fail. regexr.com/5pkc0
+ // SC: 2021-04-02 Only do this if they have been modified to go through the proxy
+ if (serverRewrite !== oldUrl) {
+ const missingSlashRegex = /\/[^./"]+$/; // URLS with extensions are fine eg *.png
+ if(missingSlashRegex.test(serverRewrite)) {
+ return `${serverRewrite}/`; // Add a slash to URLs missing them.
+ }
+ }
+ return serverRewrite;
+ }
+ return oldUrl;
+};
+
+export const processIframeUrls = (activity: Activity, stringCallback: (s: string) => string) => {
+ activity.pages.forEach(page => {
+ page.embeddables.forEach(embeddableWrapper => {
+ const embeddable = embeddableWrapper.embeddable;
+ if (embeddable.type === "ManagedInteractive" && embeddable?.library_interactive?.data) {
+ const data = embeddable.library_interactive.data;
+ data.base_url = stringCallback(data.base_url);
+ }
+ if (embeddable.type === "MwInteractive" && embeddable.url) {
+ embeddable.url = stringCallback(embeddable.url);
+ }
+ });
+ });
+};
+
+export const rewriteProxiableIframeUrls = (activity: Activity) => {
+ // do not rewrite urls when running in Cypress, otherwise the sample activity iframes do not load causing timeouts
+ if (runningInCypress) { return activity;}
+
+ processIframeUrls(activity, rewriteModelsResourcesUrl);
+
+ return activity;
+};
+
+export const isExternalOrModelsResourcesUrl = (url: string) => /^(\s*https?:\/\/|models-resources\/)/.test(url);
+
+export const removeDuplicateUrls = (urls: string[]) => urls.filter((url, index) => urls.indexOf(url) === index);
+
+export const matchAllFirstGroup = (stringToSearch: string, regExp: RegExp): string[] => {
+ const results: string[] = [];
+ let match;
+
+ while ((match = regExp.exec(stringToSearch)) !== null) {
+ results.push(match[1]);
+ }
+ return results;
+};
+
+
+export const getUrlsInString = (stringToSearch: string): string[] => {
+ return matchAllFirstGroup(stringToSearch, /"(https?:\/\/[^"]*)"/g);
+};
+
+// Find nonCSS assets
+// These are heuristics based on our limited set of files
+export const getAssetsInHtml = (htmlString: string): string[] => {
+
+ //
+ {urlInfo.success ? "" : "❌"} {urlInfo.url}
+
+ );
+ });
+
+
+ const contentItems = installedContentUrls.map(urlInfo => {
+ return (
+
+ {urlInfo.success ? "" : "❌"} {urlInfo.url}
+
+ );
+ });
+
+ return (
+
+ this.addInstalledContentUrl(true, url)}
+ onUrlCacheFailed={(url: string, err: any) => this.addInstalledContentUrl(false, url)}
+ onClose={() => this.setState({loadingOfflineManifest: false})} />
+ : null
+ }
+
+ );
+ }
+}
diff --git a/src/components/modal-dialog.tsx b/src/components/modal-dialog.tsx
index 9a5afcd6..0ada5ad6 100644
--- a/src/components/modal-dialog.tsx
+++ b/src/components/modal-dialog.tsx
@@ -1,21 +1,39 @@
-import React from "react";
+import React, { Component } from "react";
import Modal from "react-modal";
import "./modal-dialog.scss";
+/**
+ * Modal can be a simple close or an OK / Cancel popup
+ * @param label can set the text on the modal or be used as a prompt for any child element input
+ * @param onAccept can be passed to change this to OK / Cancel style modal
+ * @param onClose can simple "close the modal"
+ * @param acceptButtonText change the text displayed for an accept condition (Save, OK, Accept, etc)
+ * @param closeButtonText sets the close modal button text (Close, Cancel, etc)
+ */
interface IProps {
title?: string;
label: string;
onClose: () => void;
showModal: boolean;
+ onAccept?: (result: any) => void;
+ acceptButtonText?: string;
+ closeButtonText?: string;
}
-export class ModalDialog extends React.PureComponent Installing Activity Player Offline
+
+ Application: {__VERSION_INFO__}
+ {serviceWorkerVersionInfo && ` | Service Worker: ${serviceWorkerVersionInfo}`}
+
+
+ { !shouldStartInstalling && "Waiting for service worker to update..." }
+
+ Application Files
+ {installedItems} +Content Files
+ { offlineManifestId ? + (contentItems.length > 0 ? contentItems : "waiting...") : + "No activities specified" } + { (offlineManifest && loadingOfflineManifest) ? +{title || "Alert"}
{label}
+ {this.props.children}
-
+ {onAccept && }
+
Sorry, no offline activities were found!
+ );
+ }
+
+ renderTable() {
+ const { offlineActivities } = this.state;
+ return (
+ | Class | + } +Activity | +
|---|
+
+ );
+ }
+}
diff --git a/src/components/offline-installing.tsx b/src/components/offline-installing.tsx
new file mode 100644
index 00000000..bfacaf64
--- /dev/null
+++ b/src/components/offline-installing.tsx
@@ -0,0 +1,37 @@
+import React from "react";
+import { ServiceWorkerStatus } from "../types";
+
+interface IProps {
+ serviceWorkerStatus: ServiceWorkerStatus;
+}
+
+interface IState {
+}
+
+export class OfflineInstalling extends React.Component
+ { loading ? "Loading..." : (offlineActivities.length === 0 ? this.renderNoActivitiesFound() : this.renderTable())}
+
+
+ Activity Player Offline is installing.
+ Current status is: {serviceWorkerStatus} +
+ );
+ } else {
+ return (
+ + Current status is: {serviceWorkerStatus} +
+ Activity Player Offline is installed.
+ Reload the page to continue. +
+ );
+ }
+ }
+}
diff --git a/src/components/offline-manifest-authoring-nav.scss b/src/components/offline-manifest-authoring-nav.scss
new file mode 100644
index 00000000..53954b59
--- /dev/null
+++ b/src/components/offline-manifest-authoring-nav.scss
@@ -0,0 +1,36 @@
+@import "./vars.scss";
+
+.offline-manifest-authoring-nav {
+ height: 60px;
+ width: 100%;
+ margin-bottom: 3px;
+ font-size: 18px;
+ font-weight: bold;
+
+ .inner {
+ display: flex;
+ flex-direction: row;
+ align-items: center;
+ height: 100%;
+ width: $content-width;
+ box-sizing: border-box;
+ margin: auto;
+ background-color: $cc-orange;
+ color: $cc-charcoal;
+
+ &.full {
+ width: 100%;
+ }
+
+ .nav-center {
+ flex: 1;
+ min-width: 0;
+ height: 20px;
+ padding: 8px 10px;
+ }
+
+ .nav-right {
+ margin-right: 10px;
+ }
+ }
+}
diff --git a/src/components/offline-manifest-authoring-nav.tsx b/src/components/offline-manifest-authoring-nav.tsx
new file mode 100644
index 00000000..4a0bbf1c
--- /dev/null
+++ b/src/components/offline-manifest-authoring-nav.tsx
@@ -0,0 +1,59 @@
+import React from "react";
+import { clearOfflineManifestAuthoringData, clearOfflineManifestAuthoringId, getOfflineManifestAuthoringDownloadJSON } from "../offline-manifest-api";
+import { OfflineManifest, OfflineManifestActivity } from "../types";
+import queryString from "query-string";
+
+import "./offline-manifest-authoring-nav.scss";
+
+interface IProps {
+ offlineManifest?: OfflineManifest;
+ offlineManifestAuthoringId: string;
+ offlineManifestAuthoringActivities: OfflineManifestActivity[],
+ offlineManifestAuthoringCacheList: string[],
+}
+
+export class OfflineManifestAuthoringNav extends React.PureComponent+ Reload the page to continue. +
+
+ );
+ }
+}
diff --git a/src/components/offline-manifest-loading-modal.scss b/src/components/offline-manifest-loading-modal.scss
new file mode 100644
index 00000000..377de3c9
--- /dev/null
+++ b/src/components/offline-manifest-loading-modal.scss
@@ -0,0 +1,47 @@
+@import "./vars.scss";
+.offline-manifest-loading-modal {
+ position: fixed;
+ top: 0;
+ right: 0;
+ bottom: 0;
+ left: 0;
+ display: flex;
+ justify-content: center;
+ align-items: center;
+
+ .background {
+ position: absolute;
+ top: 0;
+ right: 0;
+ bottom: 0;
+ left: 0;
+ background: rgba($color: #000000, $alpha: 0.75);
+ }
+
+ .dialog {
+ z-index: 1;
+ background-color: #fff;
+ color: #000;
+ width: 500px;
+ padding: 21px 22.5px 25px;
+ display: flex;
+ flex-direction: column;
+ justify-content: center;
+ align-items: center;
+ font-family: Arial;
+ font-size: 11.3pt;
+ font-weight: normal;
+ font-stretch: normal;
+ font-style: normal;
+ line-height: normal;
+ letter-spacing: normal;
+ color: #000000;
+
+ div {
+ border: solid 1px var(--cc-charcoal-light-1);
+ background-color: var(--white);
+ margin: 15px 28px 12px;
+ text-align: center;
+ }
+ }
+}
\ No newline at end of file
diff --git a/src/components/offline-manifest-loading-modal.tsx b/src/components/offline-manifest-loading-modal.tsx
new file mode 100644
index 00000000..e36a73c4
--- /dev/null
+++ b/src/components/offline-manifest-loading-modal.tsx
@@ -0,0 +1,146 @@
+import React from "react";
+import { cacheOfflineManifest } from "../offline-manifest-api";
+import { OfflineManifest } from "../types";
+import { Workbox } from "workbox-window/index";
+
+import "./offline-manifest-loading-modal.scss";
+
+interface IProps {
+ offlineManifest: OfflineManifest;
+ onClose: () => void;
+ workbox: Workbox;
+ onCachingStarted?: (urls: string[]) => void;
+ onUrlCached?: (url: string) => void;
+ onUrlCacheFailed?: (url: string, err: any) => void;
+ onCachingFinished?: () => void;
+}
+
+interface IState {
+ urlsToCache: string[];
+ urlsCached: string[];
+ urlsFailedToCache: string[];
+ caching: boolean;
+}
+
+export class OfflineManifestLoadingModal extends React.Component
+
+
+ Authoring: "{offlineManifestAuthoringId}" ({offlineManifestAuthoringActivities.length} activities / {offlineManifestAuthoringCacheList.length} cached items)
+
+
+ Download JSON
+
+
+
+
+ Loading {offlineManifest.name} assets...
+
+
+ {urlsCached.length + urlsFailedToCache.length} of {urlsToCache.length}
+
+ {urlsFailedToCache.length > 0 && {urlsFailedToCache.length} failed to load!
}
+
+ );
+ }
+
+ renderDoneCaching() {
+ const { offlineManifest } = this.props;
+ const numFailedUrls = this.state.urlsFailedToCache.length;
+ const message = numFailedUrls === 0 ? "loading" : "attempting to load";
+
+ return (
+ <>
+
+ Finished {message} {offlineManifest.name} assets.
+
+ {numFailedUrls > 0
+ ?
+ <>
+ Sorry, some files failed to install. Close the dialog to see the details.
+ {numFailedUrls} assets failed to load
+
+
+ : <>
+ All assets have been installed!
+
+ To access activities on a Mac, install the Activity Player app:
+
+ -
+
- + Click the Install icon to the right of your browser’s address bar. + +
-
+ In the prompt, click the Install button.
+
+ The Activity Player app window will open with these instructions. Also, the app icon — a light bulb — will be placed in the Dock. +
+
+ - + Find the light bulb icon in the Dock. + +
-
+ Right-click on the icon and select Options > Keep in Dock.
+
+ The Activity Player app can now be opened using this light bulb icon. +
+
+ -
+ To access activities: close this Activity Player app window and then re-open it using the light bulb icon in the Dock.
+
+ Note: upon re-opening the Activity Player app, these instructions will + be replaced with a list of activities. +
+
+
+
+
+ );
+ }
+}
diff --git a/src/components/offline-nav.scss b/src/components/offline-nav.scss
new file mode 100644
index 00000000..29d64660
--- /dev/null
+++ b/src/components/offline-nav.scss
@@ -0,0 +1,26 @@
+@import "./vars.scss";
+
+.offline-nav {
+ height: 60px;
+ width: 100%;
+ margin-bottom: 3px;
+ font-size: 18px;
+ font-weight: bold;
+
+ .inner {
+ display: flex;
+ flex-direction: row;
+ align-items: center;
+ height: 100%;
+ width: $content-width;
+ box-sizing: border-box;
+ margin: auto;
+ background-color: $cc-orange;
+ color: $cc-charcoal;
+ cursor: pointer;
+
+ svg {
+ margin: 0 5px 0 20px;
+ }
+ }
+}
diff --git a/src/components/offline-nav.tsx b/src/components/offline-nav.tsx
new file mode 100644
index 00000000..2bb7ec4a
--- /dev/null
+++ b/src/components/offline-nav.tsx
@@ -0,0 +1,21 @@
+import React from "react";
+import IconHome from "../assets/svg-icons/icon-home.svg";
+
+import "./offline-nav.scss";
+
+interface IProps {
+ onOfflineActivities: () => void;
+}
+
+export class OfflineNav extends React.PureComponent
+ {caching ? this.renderCaching() : this.renderDoneCaching()}
+
+
+
+ );
+ }
+}
diff --git a/src/components/single-page/single-page-content.test.tsx b/src/components/single-page/single-page-content.test.tsx
index 24932d5f..f6ba93b4 100644
--- a/src/components/single-page/single-page-content.test.tsx
+++ b/src/components/single-page/single-page-content.test.tsx
@@ -10,11 +10,11 @@ const activitySinglePage = _activitySinglePage as Activity;
describe("Single Page Content component", () => {
it("renders component", () => {
- const wrapper = shallow(
+
+
- WARNING: The activity player is storing data in a test database. Your data could be deleted at any time.
+
);
};
diff --git a/src/data/sample-activity-glossary-plugin.json b/src/data/sample-activity-glossary-plugin.json
index 761ee180..3e5fa2d7 100644
--- a/src/data/sample-activity-glossary-plugin.json
+++ b/src/data/sample-activity-glossary-plugin.json
@@ -127,7 +127,7 @@
"embeddable": {
"plugin": {
"description": null,
- "author_data": "{\"tipType\":\"windowShade\",\"windowShade\":{\"windowShadeType\":\"theoryAndBackground\",\"layout\":\"mediaLeft\",\"initialOpenState\":true,\"content\":\"This is test content\",\"content2\":\"\",\"mediaType\":\"none\",\"mediaCaption\":\"none\",\"mediaURL\":\"\"}}",
+ "author_data": "{\"tipType\":\"windowShade\",\"windowShade\":{\"windowShadeType\":\"theoryAndBackground\",\"layout\":\"mediaLeft\",\"initialOpenState\":true,\"content\":\"This is test content\",\"content2\":\"\",\"mediaType\":\"none\",\"mediaCaption\":\"none\",\"mediaURL\":\"https://example.com/fake.mp4\"}}",
"approved_script_label": "teacherEditionTips",
"component_label": "windowShade",
"approved_script": {
diff --git a/src/data/sample-activity-hidden-content.json b/src/data/sample-activity-hidden-content.json
index 5b223f74..be7a30e7 100644
--- a/src/data/sample-activity-hidden-content.json
+++ b/src/data/sample-activity-hidden-content.json
@@ -1,5 +1,5 @@
{
- "description": "
+
+ WARNING: The activity player is using a test database. Your data could be deleted at any time.
+
+ This activity contains a hidden page and a hidden question on each page. There are 4 total pages, but only 3 should be displayed. On the displayed pages, each contains 3 questions but only 2 should be shown (each contains a hidden question) and the interactive block section is hidden.
", + "description": "This activity contains a hidden page and a hidden question on each page. There are 4 total pages, but only 3 should be displayed. On the displayed pages, each contains 3 questions but only 2 should be shown (each contains a hidden question) and the interactive block section is hidden. There are no questions on the fourth page.
", "editor_mode": 0, "layout": 0, "name": "Hidden Content Activity", diff --git a/src/global.d.ts b/src/global.d.ts index b32f42c1..3b229a7f 100644 --- a/src/global.d.ts +++ b/src/global.d.ts @@ -2,3 +2,4 @@ declare module "*.png"; declare module "*.svg"; declare module "iframe-phone"; declare module "shutterbug"; +declare const __VERSION_INFO__: string; diff --git a/src/index.html b/src/index.html index 449ba7cb..3cb24233 100644 --- a/src/index.html +++ b/src/index.html @@ -7,9 +7,7 @@ - + diff --git a/src/index.tsx b/src/index.tsx index 7317b4f8..abb9acd6 100644 --- a/src/index.tsx +++ b/src/index.tsx @@ -1,3 +1,4 @@ +import "ts-polyfill"; import React from "react"; import ReactDOM from "react-dom"; import { App } from "./components/app"; diff --git a/src/install.html b/src/install.html new file mode 100644 index 00000000..3b063863 --- /dev/null +++ b/src/install.html @@ -0,0 +1,13 @@ + + + + +This is a test of some of the words in the AK glossary: precipitation, prediction, weather and air moisture.
", + "is_callout": true, + "is_full_width": false, + "is_hidden": false, + "name": "", + "type": "Embeddable::Xhtml", + "ref_id": "272828-Embeddable::Xhtml" + }, + "section": "interactive_box" + } + ] + }, + { + "additional_sections": {}, + "embeddable_display_mode": "stacked", + "is_completion": true, + "is_hidden": false, + "layout": "l-6040", + "name": null, + "position": 3, + "show_header": false, + "show_info_assessment": false, + "show_interactive": false, + "show_sidebar": false, + "sidebar": null, + "sidebar_title": "Did you know?", + "toggle_info_assessment": false, + "embeddables": [] + } + ], + "plugins": [ + { + "description": null, + "author_data": "{\"version\":\"1.0\",\"glossaryResourceId\":\"upZ83jqTZAZuoQqRAfAb\",\"s3Url\":\"https://models-resources.s3.amazonaws.com/glossary-resources/custom-apo/alaska-v1.json?__noUrlRewrite\"}", + "approved_script_label": "glossary", + "component_label": "glossary", + "approved_script": { + "name": "Glossary (test offline saves with language switcher)", + "url": "https://glossary-plugin.concord.org/branch/177305115-add-language-switcher/plugin.js", + "label": "glossary", + "description": "This plugin provides the glossary activity plugin", + "version": 3, + "json_url": "https://glossary-plugin.concord.org/branch/177305115-add-language-switcher/manifest.json", + "authoring_metadata": "{\"components\":[{\"label\":\"glossary\",\"name\":\"Activity\",\"scope\":\"activity\",\"guiAuthoring\":true}]}" + } + } + ], + "type": "LightweightActivity", + "export_site": "Lightweight Activities Runtime and Authoring" +} \ No newline at end of file diff --git a/src/public/offline-activities/precipitating-change-v1/interview.json b/src/public/offline-activities/precipitating-change-v1/interview.json new file mode 100644 index 00000000..658cda58 --- /dev/null +++ b/src/public/offline-activities/precipitating-change-v1/interview.json @@ -0,0 +1,429 @@ +{ + "description": "", + "editor_mode": 0, + "layout": 0, + "name": "Alaska 2021 - Interview - Predicting the Weather Without the Weather Channel", + "notes": "", + "project_id": 25, + "related": "", + "runtime": "Activity Player", + "show_submit_button": true, + "student_report_enabled": true, + "thumbnail_url": "", + "time_to_complete": null, + "version": 1, + "theme_name": "Precipitating Change", + "pages": [{ + "additional_sections": {}, + "embeddable_display_mode": "stacked", + "id": 143459, + "is_completion": false, + "is_hidden": false, + "layout": "l-6040", + "name": "Page 1", + "position": 1, + "show_header": true, + "show_info_assessment": false, + "show_interactive": false, + "show_sidebar": false, + "sidebar": null, + "sidebar_title": "Did you know?", + "toggle_info_assessment": false, + "embeddables": [{ + "embeddable": { + "name": "", + "url_fragment": null, + "authored_state": "{\"version\":1,\"scaling\":\"fitWidth\",\"url\":\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/Captioned_Videos/new_picts/SKy_MG_2.png\"}", + "is_hidden": true, + "is_full_width": false, + "show_in_featured_question_report": true, + "inherit_aspect_ratio_method": true, + "custom_aspect_ratio_method": "DEFAULT", + "inherit_native_width": true, + "custom_native_width": 576, + "inherit_native_height": true, + "custom_native_height": 435, + "inherit_click_to_play": true, + "custom_click_to_play": false, + "inherit_full_window": true, + "custom_full_window": false, + "inherit_click_to_play_prompt": true, + "custom_click_to_play_prompt": null, + "inherit_image_url": true, + "custom_image_url": null, + "library_interactive": { + "hash": "cbe15db2fbb4e78c7ad98f2b86ef9a9b99a2636f", + "data": { + "aspect_ratio_method": "DEFAULT", + "authoring_guidance": "", + "base_url": "https://models-resources.concord.org/question-interactives/version/v1.1.0/image/", + "click_to_play": false, + "click_to_play_prompt": null, + "description": "", + "enable_learner_state": false, + "full_window": false, + "has_report_url": false, + "image_url": null, + "name": "Image Interactive", + "native_height": 435, + "native_width": 576, + "no_snapshots": false, + "show_delete_data_button": false, + "thumbnail_url": "", + "customizable": true, + "authorable": true + } + }, + "type": "ManagedInteractive", + "ref_id": "1636-ManagedInteractive", + "linked_interactives": [] + }, + "section": "header_block" + }, { + "embeddable": { + "content": "\u003Cp\u003E\u003Cstrong\u003EPredicting the weather without the Weather Channel\u003C/strong\u003E\u003C/p\u003E\r\n\u003Cp\u003ETalk with an \u003Cstrong\u003Eadult family member or family friend\u003C/strong\u003E who you think might have experience predicting the weather (maybe even someone who is older who learned how to predict the weather when they were around your age).\u003C/p\u003E\r\n\u003Cp\u003EWhat if you needed a weather forecast and couldn\u0026rsquo;t use your usual ways of checking the weather? 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The students will make a computer model to predict\u0026nbsp;weather\u0026nbsp;in Alaska.\u003C/p\u003E\r\n\u003Cp\u003EFour students in Ms. Tevuk\u0026rsquo;s class are figuring out how to estimate the temperature of a location. The students are looking at the map below and have different ideas for estimating the temperature at the location marked X using the recorded temperatures of 31\u02da and 59\u02da.\u003C/p\u003E\r\n\u003Cp\u003E\u003Cimg class=\"\" style=\"display: block; margin-left: auto; margin-right: auto;\" src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/L2AssessmentQ.png\" alt=\"\" width=\"550\" height=\"62\" /\u003E\u003C/p\u003E\r\n\u003Cp\u003EHere are the students\u0026rsquo; ideas:\u003C/p\u003E\r\n\u003Ctable cellpadding=\"30\"\u003E\r\n\u003Ctbody\u003E\r\n\u003Ctr\u003E\r\n\u003Cth colspan=\"2\"\u003E\u003Cstrong\u003EAlex\u003C/strong\u003E\u003C/th\u003E\r\n\u003Cth colspan=\"2\"\u003E\u003Cstrong\u003EDelana\u003C/strong\u003E\u003C/th\u003E\r\n\u003C/tr\u003E\r\n\u003Ctr\u003E\r\n\u003Ctd width=\"88\"\u003E\u003Cimg src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/Alex1.png\" width=\"60\" height=\"88\" align=\"center\" hspace=\"10\" vspace=\"10\" /\u003E\u003C/td\u003E\r\n\u003Ctd style=\"padding: 10px;\" width=\"350\"\u003EWe should use the number that is exactly halfway in between 31\u02daand 59\u02da. That\u0026rsquo;s the most exact way to estimate.\u003C/td\u003E\r\n\u003Ctd width=\"88\"\u003E\u003Cimg src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/Delana1.png\" width=\"65\" height=\"92\" align=\"center\" hspace=\"10\" vspace=\"10\" /\u003E\u003C/td\u003E\r\n\u003Ctd style=\"padding: 10px;\" width=\"350\"\u003EWe should mark a number line along the map with the estimate in each square going up the same amount between 31\u02da and 59\u02da. That\u0026rsquo;d be the best estimate.\u003C/td\u003E\r\n\u003C/tr\u003E\r\n\u003C/tbody\u003E\r\n\u003Ctbody\u003E\r\n\u003Ctr\u003E\r\n\u003Cth colspan=\"2\"\u003E\u003Cstrong\u003EKalin\u003C/strong\u003E\u003C/th\u003E\r\n\u003Cth colspan=\"2\"\u003E\u003Cstrong\u003ESage\u003C/strong\u003E\u003C/th\u003E\r\n\u003C/tr\u003E\r\n\u003Ctr\u003E\r\n\u003Ctd width=\"88\"\u003E\r\n\u003Cp\u003E\u003Cimg src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/Kalin.png\" width=\"65\" height=\"88\" align=\"center\" hspace=\"10\" vspace=\"10\" /\u003E\u003C/p\u003E\r\n\u003C/td\u003E\r\n\u003Ctd style=\"padding: 10px;\" width=\"350\"\u003EIt doesn\u0026rsquo;t make sense to estimate the temperature at the X. We\u0026rsquo;d need to go there and measure the temperature. You can\u0026rsquo;t be confident unless you measure it.\u003C/td\u003E\r\n\u003Ctd width=\"88\"\u003E\r\n\u003Cp\u003E\u003Cimg src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/Sage1.png\" width=\"65\" height=\"92\" align=\"center\" hspace=\"8\" vspace=\"8\" /\u003E\u003C/p\u003E\r\n\u003C/td\u003E\r\n\u003Ctd style=\"padding: 10px;\" width=\"350\"\u003EThe X is closer to the 59\u02da than to the 31\u02da, so let\u0026rsquo;s choose a number closer to 59\u02da. 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Pre-Assessment*\\nDuring the pre-assessment, each student will view the probe and make an individual choice. The request for explanation will only be on the post-assessment. After students make an individual commitment for the pre-assessment, you can lead a discussion including, for example, a pair/share opportunity and/or full class discussion. \\n\\nAt this time, encourage students to share and discuss their ideas and reasons without indicating that any one answer is better or worse. Let the students know that they should keep thinking about this question and that the class will return to it at the end of the lesson.\\n\",\"content2\":\"\",\"mediaType\":\"none\",\"mediaCaption\":\"Last, First. \\\"Title of Work.\\\" Year created. Site Title [OR] Publisher. 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Review the information and consider ways to scaffold students toward developing knowledge and practice as appropriate for their classes. We also recommend during the first implementation of the probe, you scaffold students to focus on student ideas about this problem, rather than on vocabulary terms such as **interpolation**. By discussing the different options, students can engage in productive talk related to data sense making and computational thinking without using technical terminology. During the ensuing lesson and the second implementation of the probe, the term interpolation can be used, as appropriate.\\n\\nThis assessment probe is designed to assess and scaffold students in thinking and talking about **interpolation**. **Interpolation** means estimating a value between ones that are known or tabulated using surrounding points or values (that is, estimating an unknown value based on surrounding information). \\n\\nThe assessment is situated within the unit context to provide an opportunity for students to make sense about interpolation of a specific, tangible weather question (i.e., temperatures along a map transect). There is always uncertainty involved when interpolating across data. Also, depending on circumstances, different methods may be appropriate. For example, if the students were trying to figure out how to dress for the day at location X, then simply choosing a number somewhere between the two might be sufficient. 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It might be helpful to discuss that we can never collect all the data in the world; there\u2019s too much! Because of this, we need a way to fill in missing values using the data that we do have available. \\n\\n###Middle Level \\n\u2022\\t**Both Alex\u2019s response (choose the value half way between)** and **Sage\u2019s response (choose a number closer to 59)** might be reasonable estimates in certain circumstances (e.g., for picking out what clothes to wear if you were at location X at that time). These approaches are both better than just choosing a random value as an estimate for X. 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The students will make a computer model to predict\u0026nbsp;weather\u0026nbsp;in Alaska.\u003C/p\u003E\r\n\u003Cp\u003EFour students in Ms. Tevuk\u0026rsquo;s class are figuring out how to estimate the temperature of a location. The students are looking at the map below and have different ideas for estimating the temperature at the location marked X using the recorded temperatures of 31\u02da and 59\u02da.\u003C/p\u003E\r\n\u003Cp\u003E\u003Cimg class=\"\" style=\"display: block; margin-left: auto; margin-right: auto;\" src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/L2AssessmentQ.png\" alt=\"\" width=\"550\" height=\"62\" /\u003E\u003C/p\u003E\r\n\u003Cp\u003EHere are the students\u0026rsquo; ideas:\u003C/p\u003E\r\n\u003Ctable cellpadding=\"30\"\u003E\r\n\u003Ctbody\u003E\r\n\u003Ctr\u003E\r\n\u003Cth colspan=\"2\"\u003E\u003Cstrong\u003EAlex\u003C/strong\u003E\u003C/th\u003E\r\n\u003Cth colspan=\"2\"\u003E\u003Cstrong\u003EDelana\u003C/strong\u003E\u003C/th\u003E\r\n\u003C/tr\u003E\r\n\u003Ctr\u003E\r\n\u003Ctd width=\"88\"\u003E\u003Cimg src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/Alex1.png\" width=\"60\" height=\"88\" align=\"center\" hspace=\"10\" vspace=\"10\" /\u003E\u003C/td\u003E\r\n\u003Ctd style=\"padding: 10px;\" width=\"350\"\u003EWe should use the number that is exactly halfway in between 31\u02daand 59\u02da. That\u0026rsquo;s the most exact way to estimate.\u003C/td\u003E\r\n\u003Ctd width=\"88\"\u003E\u003Cimg src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/Delana1.png\" width=\"65\" height=\"92\" align=\"center\" hspace=\"10\" vspace=\"10\" /\u003E\u003C/td\u003E\r\n\u003Ctd style=\"padding: 10px;\" width=\"350\"\u003EWe should mark a number line along the map with the estimate in each square going up the same amount between 31\u02da and 59\u02da. That\u0026rsquo;d be the best estimate.\u003C/td\u003E\r\n\u003C/tr\u003E\r\n\u003C/tbody\u003E\r\n\u003Ctbody\u003E\r\n\u003Ctr\u003E\r\n\u003Cth colspan=\"2\"\u003E\u003Cstrong\u003EKalin\u003C/strong\u003E\u003C/th\u003E\r\n\u003Cth colspan=\"2\"\u003E\u003Cstrong\u003ESage\u003C/strong\u003E\u003C/th\u003E\r\n\u003C/tr\u003E\r\n\u003Ctr\u003E\r\n\u003Ctd width=\"88\"\u003E\r\n\u003Cp\u003E\u003Cimg src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/Kalin.png\" width=\"65\" height=\"88\" align=\"center\" hspace=\"10\" vspace=\"10\" /\u003E\u003C/p\u003E\r\n\u003C/td\u003E\r\n\u003Ctd style=\"padding: 10px;\" width=\"350\"\u003EIt doesn\u0026rsquo;t make sense to estimate the temperature at the X. We\u0026rsquo;d need to go there and measure the temperature. You can\u0026rsquo;t be confident unless you measure it.\u003C/td\u003E\r\n\u003Ctd width=\"88\"\u003E\r\n\u003Cp\u003E\u003Cimg src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/Sage1.png\" width=\"65\" height=\"92\" align=\"center\" hspace=\"8\" vspace=\"8\" /\u003E\u003C/p\u003E\r\n\u003C/td\u003E\r\n\u003Ctd style=\"padding: 10px;\" width=\"350\"\u003EThe X is closer to the 59\u02da than to the 31\u02da, so let\u0026rsquo;s choose a number closer to 59\u02da. That\u0026rsquo;s the best we can do because we don\u0026rsquo;t know what\u0026rsquo;s happening with the weather in those places.\u003C/td\u003E\r\n\u003C/tr\u003E\r\n\u003C/tbody\u003E\r\n\u003C/table\u003E", + "is_callout": false, + "is_full_width": true, + "is_hidden": false, + "name": "", + "type": "Embeddable::Xhtml", + "ref_id": "147795-Embeddable::Xhtml" + }, + "section": "header_block" + }, { + "embeddable": { + "name": "", + "url_fragment": null, + "authored_state": "{\"version\":1,\"questionType\":\"multiple_choice\",\"multipleAnswers\":false,\"layout\":\"vertical\",\"choices\":[{\"id\":\"1\",\"content\":\"Alex\",\"correct\":false},{\"id\":\"2\",\"content\":\"Delana\",\"correct\":false},{\"id\":\"3\",\"content\":\"Kalin\",\"correct\":false},{\"content\":\"Sage\",\"correct\":false,\"id\":\"48ed2c41-2f41-4d5e-b70c-89cc42e2eb72\"}],\"prompt\":\"\u003Cp\u003EWhich student\u2019s idea do you agree with the most?\u003C/p\u003E\"}", + "is_hidden": false, + "is_full_width": true, + "show_in_featured_question_report": true, + "inherit_aspect_ratio_method": true, + "custom_aspect_ratio_method": "DEFAULT", + "inherit_native_width": true, + "custom_native_width": 576, + "inherit_native_height": true, + "custom_native_height": 435, + "inherit_click_to_play": true, + "custom_click_to_play": false, + "inherit_full_window": true, + "custom_full_window": false, + "inherit_click_to_play_prompt": true, + "custom_click_to_play_prompt": null, + "inherit_image_url": true, + "custom_image_url": null, + "library_interactive": { + "hash": "98f3d10aa7f2fce6bdeb0ecda339fa56dc80b37c", + "data": { + "aspect_ratio_method": "DEFAULT", + "authoring_guidance": "", + "base_url": "https://models-resources.concord.org/question-interactives/version/v1.1.0/multiple-choice/", + "click_to_play": false, + "click_to_play_prompt": null, + "description": "", + "enable_learner_state": true, + "full_window": false, + "has_report_url": false, + "image_url": null, + "name": "Multiple Choice", + "native_height": 435, + "native_width": 576, + "no_snapshots": false, + "show_delete_data_button": false, + "thumbnail_url": "", + "customizable": true, + "authorable": true + } + }, + "type": "ManagedInteractive", + "ref_id": "1658-ManagedInteractive", + "linked_interactives": [] + }, + "section": "header_block" + }, { + "embeddable": { + "name": "", + "url_fragment": null, + "authored_state": "{\"version\":1,\"questionType\":\"open_response\",\"prompt\":\"\u003Cp\u003EWhy do you think the choice you picked is the best for estimating the temperature? 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Pre-Assessment*\\nDuring the pre-assessment, each student will view the probe and make an individual choice. The request for explanation will only be on the post-assessment. After students make an individual commitment for the pre-assessment, you can lead a discussion including, for example, a pair/share opportunity and/or full class discussion. \\n\\nAt this time, encourage students to share and discuss their ideas and reasons without indicating that any one answer is better or worse. Let the students know that they should keep thinking about this question and that the class will return to it at the end of the lesson.\\n\",\"content2\":\"\",\"mediaType\":\"none\",\"mediaCaption\":\"Last, First. \\\"Title of Work.\\\" Year created. Site Title [OR] Publisher. Gallery [OR] Location. http://www.url.com.\",\"mediaURL\":\"\"}}", + "approved_script_label": "teacherEditionTips", + "component_label": "windowShade", + "approved_script": { + "name": "Teacher Edition", + "url": "https://teacher-edition-tips-plugin.concord.org/version/v3.6.0/plugin.js", + "label": "teacherEditionTips", + "description": "This plugin provides Teacher Edition components", + "version": 3, + "json_url": "https://teacher-edition-tips-plugin.concord.org/version/v3.6.0/manifest.json", + "authoring_metadata": "{\"components\":[{\"label\":\"windowShade\",\"name\":\"Window Shades\",\"scope\":\"embeddable\",\"guiAuthoring\":true},{\"label\":\"sideTip\",\"name\":\"Side Tips\",\"scope\":\"embeddable\",\"guiAuthoring\":true},{\"label\":\"questionWrapper\",\"name\":\"Question Wrapper\",\"scope\":\"embeddable-decoration\",\"decorates\":[\"Embeddable::MultipleChoice\",\"Embeddable::OpenResponse\",\"Embeddable::ImageQuestion\",\"ManagedInteractive\",\"MwInteractive\",\"ImageInteractive\",\"VideoInteractive\"],\"guiAuthoring\":true,\"guiPreview\":true}]}" + } + }, + "is_hidden": false, + "is_full_width": true, + "type": "Embeddable::EmbeddablePlugin", + "ref_id": "10214-Embeddable::EmbeddablePlugin" + }, + "section": null + }, { + "embeddable": { + "plugin": { + "description": null, + "author_data": "{\"tipType\":\"windowShade\",\"windowShade\":{\"windowShadeType\":\"theoryAndBackground\",\"layout\":\"mediaLeft\",\"initialOpenState\":true,\"content\":\"###Computational Thinking Concept and Practice:\\n* Interpolation\\n\\n###What is the Purpose of this Assessment Probe?\\nThe following information provides background for **teachers** and is not necessarily representative of the learning goals for everything students should understand. Review the information and consider ways to scaffold students toward developing knowledge and practice as appropriate for their classes. We also recommend during the first implementation of the probe, you scaffold students to focus on student ideas about this problem, rather than on vocabulary terms such as **interpolation**. By discussing the different options, students can engage in productive talk related to data sense making and computational thinking without using technical terminology. During the ensuing lesson and the second implementation of the probe, the term interpolation can be used, as appropriate.\\n\\nThis assessment probe is designed to assess and scaffold students in thinking and talking about **interpolation**. **Interpolation** means estimating a value between ones that are known or tabulated using surrounding points or values (that is, estimating an unknown value based on surrounding information). \\n\\nThe assessment is situated within the unit context to provide an opportunity for students to make sense about interpolation of a specific, tangible weather question (i.e., temperatures along a map transect). There is always uncertainty involved when interpolating across data. Also, depending on circumstances, different methods may be appropriate. For example, if the students were trying to figure out how to dress for the day at location X, then simply choosing a number somewhere between the two might be sufficient. 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It might be helpful to discuss that we can never collect all the data in the world; there\u2019s too much! Because of this, we need a way to fill in missing values using the data that we do have available. \\n\\n###Middle Level \\n\u2022\\t**Both Alex\u2019s response (choose the value half way between)** and **Sage\u2019s response (choose a number closer to 59)** might be reasonable estimates in certain circumstances (e.g., for picking out what clothes to wear if you were at location X at that time). These approaches are both better than just choosing a random value as an estimate for X. However, for contexts in which more precision is called for (e.g., making a weather model), then there are ways that we can be more precise in our approaches to interpolation. \\n\\nStudents who choose Alex\u2019s and/or Sage\u2019s response could benefit from discussions of when and why we sometimes might need to be more precise in our estimation approaches. \\n\\n\\n###More Formal Idea\\n\u2022\\t**Delana\u2019s response (mark a number line with the estimate in each square going up the same amount between the two measured values)** suggests that she understands which mathematical interpolation approach will give the most precise value. Again, this level of precision will take more time and effort, and may not even be necessary in some circumstances, as discussed above. 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She will discuss how temperature plays an important part in predicting weather.\u003C/p\u003E", + "is_callout": true, + "is_full_width": true, + "is_hidden": false, + "name": "", + "type": "Embeddable::Xhtml", + "ref_id": "147936-Embeddable::Xhtml" + }, + "section": "header_block" + }, { + "embeddable": { + "name": "", + "url_fragment": null, + "authored_state": "{\"version\":1,\"questionType\":\"iframe_interactive\",\"videoUrl\":\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/Captioned_Videos/JackieLesson2_88_Captioned.mp4\",\"poster\":\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/Captioned_Videos/Posters/Poster_L2_Video.png\"}", + "is_hidden": false, + "is_full_width": true, + "show_in_featured_question_report": true, + "inherit_aspect_ratio_method": true, + "custom_aspect_ratio_method": null, + "inherit_native_width": true, + "custom_native_width": 576, + "inherit_native_height": true, + "custom_native_height": 435, + "inherit_click_to_play": true, + "custom_click_to_play": false, + "inherit_full_window": true, + "custom_full_window": false, + "inherit_click_to_play_prompt": true, + "custom_click_to_play_prompt": null, + "inherit_image_url": true, + "custom_image_url": null, + "library_interactive": { + "hash": "34e1a2a39c058da8ff4ffe5a09ad14af337c4a01", + "data": { + "aspect_ratio_method": "DEFAULT", + "authoring_guidance": "", + "base_url": "https://models-resources.concord.org/question-interactives/version/v1.1.0/video-player/", + "click_to_play": false, + "click_to_play_prompt": null, + "description": "This video player will not have the blue header bar above the interactive.\r\nIt does not save the students position in the video. \r\nIt will not show up in the teacher report.", + "enable_learner_state": false, + "full_window": false, + "has_report_url": false, + "image_url": null, + "name": "Video Player", + "native_height": 435, + "native_width": 576, + "no_snapshots": false, + "show_delete_data_button": false, + "thumbnail_url": "", + "customizable": false, + "authorable": true + } + }, + "type": "ManagedInteractive", + "ref_id": "1705-ManagedInteractive", + "linked_interactives": [] + }, + "section": "header_block" + }] + }, { + "additional_sections": null, + "embeddable_display_mode": "stacked", + "id": 143207, + "is_completion": false, + "is_hidden": false, + "layout": "l-full-width", + "name": "Lesson Opening", + "position": 2, + "show_header": true, + "show_info_assessment": true, + "show_interactive": false, + "show_sidebar": false, + "sidebar": null, + "sidebar_title": "Did you know?", + "toggle_info_assessment": false, + "embeddables": [{ + "embeddable": { + "content": "\u003Cp\u003EHave you ever wondered why some temperature displays are in color (for instance, television weather reports), but a thermometer displays temperature in numbers? Or how weather apps can tell you what the temperature is wherever you are? In this lesson, you are going to learn what it means to display temperature for mainland Alaska.\u003C/p\u003E\r\n\u003Cp\u003EAs\u0026nbsp; weather scientists (meteorologists), you will experience a virtual storm event in your classroom. As the virtual storm event occurs, you and your research team will collect and record temperature data.\u0026nbsp;\u003C/p\u003E\r\n\u003Cp\u003EAs part of your lesson challenge, you will need to determine how to capture the data, how to organize the data, and how the data should be displayed. Once you have developed a full picture of the virtual storm event, you will use this data to make a prediction of what the temperature will be at a later time.\u003C/p\u003E", + "is_callout": false, + "is_full_width": true, + "is_hidden": false, + "name": "", + "type": "Embeddable::Xhtml", + "ref_id": "147375-Embeddable::Xhtml" + }, + "section": "header_block" + }, { + "embeddable": { + "name": "Holder for Kevin's video", + "url_fragment": null, + "authored_state": "{\"version\":1,\"questionType\":\"iframe_interactive\"}", + "is_hidden": false, + "is_full_width": true, + "show_in_featured_question_report": true, + "inherit_aspect_ratio_method": true, + "custom_aspect_ratio_method": null, + "inherit_native_width": true, + "custom_native_width": 576, + "inherit_native_height": true, + "custom_native_height": 435, + "inherit_click_to_play": true, + "custom_click_to_play": false, + "inherit_full_window": true, + "custom_full_window": false, + "inherit_click_to_play_prompt": true, + "custom_click_to_play_prompt": null, + "inherit_image_url": true, + "custom_image_url": null, + "library_interactive": { + "hash": "34e1a2a39c058da8ff4ffe5a09ad14af337c4a01", + "data": { + "aspect_ratio_method": "DEFAULT", + "authoring_guidance": "", + "base_url": "https://models-resources.concord.org/question-interactives/version/v1.1.0/video-player/", + "click_to_play": false, + "click_to_play_prompt": null, + "description": "This video player will not have the blue header bar above the interactive.\r\nIt does not save the students position in the video. \r\nIt will not show up in the teacher report.", + "enable_learner_state": false, + "full_window": false, + "has_report_url": false, + "image_url": null, + "name": "Video Player", + "native_height": 435, + "native_width": 576, + "no_snapshots": false, + "show_delete_data_button": false, + "thumbnail_url": "", + "customizable": false, + "authorable": true + } + }, + "type": "ManagedInteractive", + "ref_id": "1706-ManagedInteractive", + "linked_interactives": [] + }, + "section": "header_block" + }, { + "embeddable": { + "plugin": { + "description": "", + "author_data": "{\"tipType\":\"windowShade\",\"questionWrapper\":{\"correctExplanation\":\"correct\",\"distractorsExplanation\":\"distractor\",\"exemplar\":\"exemplar\",\"teacherTip\":\"teacherTip\",\"teacherTipImageOverlay\":\"\"},\"windowShade\":{\"windowShadeType\":\"theoryAndBackground\",\"layout\":\"mediaLeft\",\"initialOpenState\":false,\"content\":\"### LESSON 2: DISPLAYING DATA:\\n\\n**HOW CAN WEATHER FROM THE PAST INFORM FUTURE WEATHER PREDICTIONS?**\\n\\nIn this lesson, students are introduced to the virtual storm technology by experiencing a weather event move through their classroom. A weather station collects data about the current weather at a specific location. The strategic placement of multiple stations and use of digital tools and mathematical concepts allows weather scientists to create a more accurate and complete model/visualization of the weather over a region and analyze it for patterns and trends. \\n\\n**LEARNING GOALS**\\n\\nStudents will be able to:\\n\\n* Take a limited amount of information and develop a more complete picture of the weather (create a weather visualization)\\n\\n* Explain a weather map using traditional weather symbols and codes (weather stations with temperature)\\n\\n* Make minimally informed predictions about future weather events\\n\\n* Explain that weather varies over time\\n\\nComputational Thinking (CT) Skills introduced in this lesson can be found in the table below:\\n\\n| CT Skill | Definition | Use in Lesson |\\n|---------------------|------------------------------------------------------------------------------------------------|-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|\\n| Data Aggregation | Describes the data collection and organization process you use to better understand the topic. | Students will collect temperature data from tablet/laptop and organize the data in charts on the wall. |\\n| Data Abstraction | Simplifying data to make it easier to interpret and find patterns. | Students will come up with a color scheme for temperature and change how the data is represented from numbers to temperature categories, and then to colors. |\\n| Interpolation | Estimating an unknown value based on surrounding information. | Students will make best guess estimates of the temperatures that are missing on the map. |\\n| Pattern Recognition | Recognizing that data or information is repeating in a logical (expected) way. | Students collect data in two rounds and see patterns of data moving across the charts. Before and after each data collection they will interpolate data. They will discover that warm and cold spots on the map are consistently on certain sides, and also see these spots change over time. |\\n| Extrapolation | Following a pattern beyond the known data points. | Students predict future weather based on patterns they observe in the changing temperatures they collected and visualized. |\\n \",\"content2\":\"\",\"mediaType\":\"none\",\"mediaCaption\":\"Last, First. \\\"Title of Work.\\\" Year created. Site Title [OR] Publisher. 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(10 mins)\\n\\n### MATERIALS AND SET-UP\\nActivity 1 - Virtual Storm: Displaying Temperature Data\\n \\nThis activity requires significant setup time and you may want to plan a few hours to transform the classroom into a 7x7 gridded space and to test and set up the iPads/laptops. \\n\\n**Per Research Team (2-4 students):**\\n\\n* Marker\\n* 3\\\" x 3\\\" sticky notes in the following colors: blue, green, yellow, red, purple, orange\\n* Fully charged and connected iPad/laptop that can display the online activity\\n* Set of colored pencils (for individual student sheets)\\n\\n**Per Class:**\\n\\n* Click [HERE](https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/GraphCoordinates_AK.pdf) and print \u201cA-G\u201d and \\\"1-7\\\" coordinates in the largest font possible.\\n\\n* Push desks to walls to get as much open space in your classroom as possible.\\n\\n* Tape labels to the classroom walls, evenly spaced. Make sure the letters are on opposite walls and the numbers on walls opposite, mirroring each other. See image below for an example:\\n\\n\\n\\n* Students should be able to stand in the grid. For example, the smiley face represents a student standing in G6. Adapt the grid points to what you have available in your learning space.\\n\\n**Weather maps:**\\n\\n* Place four large poster-sized sheets of gridded paper on a classroom wall, organizing the chart paper in a row. Each sheet will contain a 7 x 7 grid with axes labeled to match the room set-up. Click [HERE](https://youtu.be/HD_6BAHib1A) to watch a tutorial on how to create weather map grids for your classroom. \\n\\n* Label the top of each sheet with a different time: 7:00 am, 11:00 am, 3:00 pm, and 7:00 pm, and organize them on the wall in order of the time.\\n\\n* Have students track the virtual weather event and record their group's data on the tracking sheet in their Science Notebook.\\n\\n**City Markers:**\\n\\n* Print five city markers by clicking [HERE - PDF](https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/GraphCoordinates_AK.pdf)\\n\\n* Place \\\"City Markers\\\" on the floor in the appropriate classroom grid locations that correspond to the map shown in the image below:\\n\\n\",\"content2\":\"\",\"mediaType\":\"none\",\"mediaCaption\":\"Last, First. \\\"Title of Work.\\\" Year created. Site Title [OR] Publisher. 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Anchorage, AK. \",\"mediaURL\":\"https://precipitatingchange-resources.concord.org/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/JackieLesson2_88.mp4\"}}", + "approved_script_label": "teacherEditionTips", + "component_label": "windowShade", + "approved_script": { + "name": "Teacher Edition", + "url": "https://teacher-edition-tips-plugin.concord.org/version/v3.6.0/plugin.js", + "label": "teacherEditionTips", + "description": "This plugin provides Teacher Edition components", + "version": 3, + "json_url": "https://teacher-edition-tips-plugin.concord.org/version/v3.6.0/manifest.json", + "authoring_metadata": "{\"components\":[{\"label\":\"windowShade\",\"name\":\"Window Shades\",\"scope\":\"embeddable\",\"guiAuthoring\":true},{\"label\":\"sideTip\",\"name\":\"Side Tips\",\"scope\":\"embeddable\",\"guiAuthoring\":true},{\"label\":\"questionWrapper\",\"name\":\"Question Wrapper\",\"scope\":\"embeddable-decoration\",\"decorates\":[\"Embeddable::MultipleChoice\",\"Embeddable::OpenResponse\",\"Embeddable::ImageQuestion\",\"ManagedInteractive\",\"MwInteractive\",\"ImageInteractive\",\"VideoInteractive\"],\"guiAuthoring\":true,\"guiPreview\":true}]}" + } + }, + "is_hidden": true, + "is_full_width": true, + "type": "Embeddable::EmbeddablePlugin", + "ref_id": "9761-Embeddable::EmbeddablePlugin" + }, + "section": null + }] + }, { + "additional_sections": {}, + "embeddable_display_mode": "stacked", + "id": 143208, + "is_completion": false, + "is_hidden": false, + "layout": "l-6040", + "name": "Weather Station - Data", + "position": 3, + "show_header": false, + "show_info_assessment": true, + "show_interactive": true, + "show_sidebar": false, + "sidebar": null, + "sidebar_title": "Did you know?", + "toggle_info_assessment": false, + "embeddables": [{ + "embeddable": { + "content": "\u003Cp\u003EAs scientists, it is important to record temperature data for analysis and to predict future\u0026nbsp;weather\u0026nbsp;events.\u0026nbsp;\u003C/p\u003E", + "is_callout": true, + "is_full_width": true, + "is_hidden": false, + "name": "Displaying Temperature", + "type": "Embeddable::Xhtml", + "ref_id": "147376-Embeddable::Xhtml" + }, + "section": null + }, { + "embeddable": { + "content": "\u003Cp\u003EGather information from each weather station shown on the map above. Each community on the map has a weather station. Click on the box (also called a cell) the community is in to see the temperature information given.\u0026nbsp;\u003C/p\u003E", + "is_callout": true, + "is_full_width": true, + "is_hidden": false, + "name": "TASK ", + "type": "Embeddable::Xhtml", + "ref_id": "147377-Embeddable::Xhtml" + }, + "section": null + }, { + "embeddable": { + "plugin": { + "description": "", + "author_data": "{\"tipType\":\"windowShade\",\"questionWrapper\":{\"correctExplanation\":\"correct\",\"distractorsExplanation\":\"distractor\",\"exemplar\":\"exemplar\",\"teacherTip\":\"teacherTip\",\"teacherTipImageOverlay\":\"\"},\"windowShade\":{\"windowShadeType\":\"theoryAndBackground\",\"layout\":\"mediaLeft\",\"initialOpenState\":false,\"content\":\"### Activity 1 - Virtual Storm: Visualizing Temperature \\n\\nIn this activity, students simulate the experience of a weather scientist collecting weather data for a large area and organizing it into useful maps to predict a future weather event. Students collaboratively negotiate what the data means, as well as how to accurately record the data and represent it so they can use the emerging pattern to predict a future weather event. The specific computational thinking practices highlighted and practiced in this activity are **Data Aggregation**, **Abstraction**, and **Interpolation**.\\n\\n###Activity Breakdown\\n**1. Setting the stage for the virtual storm.** The grid in the classroom represents a smaller region in Alaska than the area covered in the Lesson 1 radar images. This area includes the following cities: Bettles, Gelena, Nome, Noorvik, and St. Mary\u2019s. In their research teams, students collect temperature data every four hours throughout the region for an eight-hour period of time. \\n\\n* Have a student stand in a square and ask the class to identify the coordinates of where they are standing. Repeat until clear.\\n\\n**2. Round 1 - Starting the Virtual Storm technology. **\\n\\n* Ask research teams to select a student from their team to move to an unoccupied grid cell. \\n\\n* Launch the Virtual Storm technology and have another student from the team record the temperature in the selected cell onto the poster sheet labeled \\\"7:00 am.\\\" \\n\\n* Click \\\"PLAY\\\" on the Virtual Storm technology. Instruct the students to watch the clock in the Weather Sensor, and every four hours record the temperature readings onto the corresponding poster sheets on the walls (7:00 am, 11:00 am, 3:00 pm). After this round, all posters should have eight squares filled in. \\n\\n**3. Round 2 - Students gaining practice by repeating the process.**\\n\\n* Click the \u201cRESET\u201d button. Ask research groups to choose new positions on the grid. \\n* Run the simulation and encourage students to collect and record the data on the three maps again. At the end of this round, each chart should have 16 squares filled in on each chart.\\n\\n**4. Round 3 - Be more strategic.**\\n\\n* Let the research teams rethink their position and either stay or move to a more strategically chosen position.\\n\\n* Run the simulation again, asking students to record the data on three charts. At the end of this round, 24 squares should be filled in with temperature data.\\n\\n** 5. Class Discussion - Emerging patterns \u0026 abstraction.**\\n\\n* Help students develop a color scheme of their choosing, and suggest colored sticky notes for the scheme. Honor the way students want to do it and post the scheme on the wall. For example, students might come up with six temperature categories:\\n * 10-19\u00b0F/-12.2 to -7.2\u00b0C: purple (extremely cold)\\n * 20-29\u00b0F/-6.7 to -1.7\u00b0C: blue (very cold)\\n * 30-39\u00b0F/-1.1 to 3.9\u00b0C: green (cold)\\n * 40-49\u00b0F/4.4 to 9.4\u00b0C: yellow (cool)\\n * 50-59\u00b0F/10 to 15\u00b0C: orange (warm)\\n * 60-69\u00b0F/15.6 to 20.6\u00b0C: red (very warm)\\n\\n* Before going on, have students place the colored sticky notes with the temperatures written on them over the original temperatures. Each team is responsible for their first three postings. \\n\\n** 6. Round 4 - Interpolation test.** \\n\\n* Direct the research teams to choose a new positions on the grid and ask them to take a **\\\"GUESS\\\"** of what the temperature will be for each of the charts.\\n\\n* Run the simulation. Students use the correct colored post-it note for the actual temperature and write **\u201cACTUAL\u201d** on the note and place it over their previous guesses. 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Scientists have many methods for constructing unknown data between known data points. This is called data\u0026nbsp;interpolation.\u003C/p\u003E\n\u003Cp\u003EThere are many different methods to interpolate data. Let\u0026rsquo;s look at the three\u0026nbsp;interpolation\u0026nbsp;methods used to make these maps.\u003C/p\u003E\n\u003Cp\u003E\u003Cimg class=\"\" src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/images/AKABCinterpolationtemp.jpg\" alt=\"\" width=\"484\" height=\"383\" /\u003E\u003C/p\u003E\n\u003Cp\u003E\u003Cstrong\u003ENearest Neighbor Interpolation\u003C/strong\u003E\u003C/p\u003E\n\u003Cp\u003EFor Square A, you may have guessed 54\u0026deg;F degrees or something very close to that. This is the simplest\u0026nbsp;interpolation\u0026nbsp;method. It is called\u0026nbsp;\u003Cstrong\u003ENearest Neighbor\u003C/strong\u003E. With this method, you find the nearest\u0026nbsp;weather station to the unknown point and assume it has a similar temperature.\u003C/p\u003E\n\u003Cp\u003E\u003Cbr /\u003E\u003Cstrong\u003ELinear Interpolation\u003C/strong\u003E\u003C/p\u003E\n\u003Cp\u003EFor Square B, you may have guessed between 38\u0026deg;F and 50\u0026deg;F, but closer to 50\u0026deg;F. Since this square is between two known temperatures, the unknown temperature is probably between 38\u0026deg;F and 50\u0026deg;F. To be even closer, you can think of it like a number line with temperature in each square increasing by four degrees.\u003C/p\u003E\n\u003Cp\u003E\u003Cimg class=\"\" src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/images/AKlinearinterpolation.jpg\" alt=\"\" width=\"310\" height=\"151\" /\u003E\u003C/p\u003E\n\u003Cp\u003EThis method is called\u003Cstrong\u003E Linear Interpolation\u003C/strong\u003E.\u003C/p\u003E\n\u003Cp\u003E\u003Cbr /\u003E\u003Cstrong\u003EWeighted Average Interpolation\u003C/strong\u003E\u003C/p\u003E\n\u003Cp\u003EFor Square C, the square is between other squares at 30\u0026deg;F, 48\u0026deg;F, and 50\u0026deg;F. You could average the three numbers and get approximately 43\u0026deg;F. Or you could try to be even more precise. The unknown square is closer to the 50\u0026deg;F square than to the others. Therefore, you can estimate the temperature to be a little higher than the average (maybe 45\u0026deg;F or 46\u0026deg;F). 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All five weather station observations were made at the same time on the same day. The map also shows some temperatures that were estimated using the weather station observation data (estimated temperatures are in parentheses).\u003C/p\u003E\r\n\u003Cp\u003E\u003Cimg style=\"display: block; margin-left: auto; margin-right: auto;\" src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/L3AssessmentProbeMap.png\" width=\"555\" height=\"444\" /\u003E\u003C/p\u003E\r\n\u003Cp\u003EMs. Tevuk asks the students which of the estimated temperatures they are LEAST CERTAIN (MOST UNSURE) about.\u003C/p\u003E\r\n\u003Cp\u003EHere are the students\u0026rsquo; ideas. (Each student\u0026rsquo;s estimated temperature choice is in \u003Cstrong\u003Ebold\u003C/strong\u003E to make it easier to find.)\u003C/p\u003E\r\n\u003Ctable cellpadding=\"30\"\u003E\r\n\u003Ctbody\u003E\r\n\u003Ctr\u003E\r\n\u003Cth colspan=\"2\"\u003E\u003Cstrong\u003EAlex\u003C/strong\u003E\u003C/th\u003E\r\n\u003Cth colspan=\"2\"\u003E\u003Cstrong\u003EDelana\u003C/strong\u003E\u003C/th\u003E\r\n\u003C/tr\u003E\r\n\u003Ctr\u003E\r\n\u003Ctd width=\"88\"\u003E\u003Cimg src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/Alex1-1.png\" width=\"80\" height=\"100\" align=\"center\" hspace=\"10\" vspace=\"10\" /\u003E\u003C/td\u003E\r\n\u003Ctd style=\"padding: 10px;\" width=\"350\"\u003E\r\n\u003Cp\u003EI\u0026rsquo;m least certain about the estimate of \u003Cstrong\u003E53\u02da\u003C/strong\u003E because it\u0026rsquo;s furthest outside of the temperatures that were actually measured at a weather station.\u003C/p\u003E\r\n\u003Cp\u003E\u003Cimg style=\"display: block; margin-left: auto; margin-right: auto;\" src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/Lesson3AlexsChoice.png\" width=\"223\" height=\"200\" /\u003E\u003C/p\u003E\r\n\u003C/td\u003E\r\n\u003Ctd width=\"88\"\u003E\u003Cimg src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/Delana2.png\" width=\"80\" height=\"100\" align=\"center\" hspace=\"10\" vspace=\"10\" /\u003E\u003C/td\u003E\r\n\u003Ctd style=\"padding: 10px;\" width=\"350\"\u003E\r\n\u003Cp\u003EI\u0026rsquo;m least certain about the estimate of \u003Cstrong\u003E43\u02da\u003C/strong\u003E because it\u0026rsquo;s far away from any temperatures measured at a weather station.\u0026nbsp;\u003C/p\u003E\r\n\u003Cp\u003E\u003Cimg style=\"display: block; margin-left: auto; margin-right: auto;\" src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/Lesson3DelanasChoice.png\" width=\"222\" height=\"200\" /\u003E\u003C/p\u003E\r\n\u003C/td\u003E\r\n\u003C/tr\u003E\r\n\u003C/tbody\u003E\r\n\u003Ctbody\u003E\r\n\u003Ctr\u003E\r\n\u003Cth colspan=\"2\"\u003E\u003Cstrong\u003EKalin\u003C/strong\u003E\u003C/th\u003E\r\n\u003Cth colspan=\"2\"\u003E\u003Cstrong\u003ESage\u003C/strong\u003E\u003C/th\u003E\r\n\u003C/tr\u003E\r\n\u003Ctr\u003E\r\n\u003Ctd width=\"88\"\u003E\r\n\u003Cp\u003E\u003Cimg src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/Kalin3.png\" width=\"80\" height=\"100\" align=\"center\" hspace=\"10\" vspace=\"10\" /\u003E\u003C/p\u003E\r\n\u003C/td\u003E\r\n\u003Ctd style=\"padding: 10px;\" width=\"350\"\u003E\r\n\u003Cp\u003EI\u0026rsquo;m least certain about the estimate of \u003Cstrong\u003E39\u02da\u003C/strong\u003E because there aren\u0026rsquo;t any other estimated temperatures near the 39\u02da estimate.\u003C/p\u003E\r\n\u003Cp\u003E\u003Cimg style=\"display: block; 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Pre-Assessment*\\nDuring the pre-assessment, each student will view the probe and make an individual choice. The request for explanation will only be on the post-assessment implementation. After students make an individual choice for the pre-assessment, you can lead discussion including, for example, a pair/share opportunity and/or full class discussion. \\n\\nAt this time, encourage students to share and discuss their ideas and reasons without indicating that any one answer is better or worse. Let the students know that they should keep thinking about this question and that the class will return to it at the end of the lesson.\",\"content2\":\"\",\"mediaType\":\"none\",\"mediaCaption\":\"Last, First. \\\"Title of Work.\\\" Year created. Site Title [OR] Publisher. 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Review the information below and think about ways to scaffold students toward developing knowledge and practice as appropriate for their classes. Also, we recommend that during the first implementation of the probe, that you scaffold students to focus on their own ideas about this problem, rather than on vocabulary terms such as **interpolation** and **extrapolation**. By discussing the different options, students can engage in productive talk related to these data sense making and computational thinking concepts without necessarily using technical terminology. During the ensuing lesson and the second implementation of the probe, the terms **interpolation** and **extrapolation** can be used, if appropriate.\\n\\nThis assessment probe is designed to assess and scaffold students in thinking and talking about **interpolation** and **extrapolation**. **Interpolation** means finding an estimation of a value between ones that are known or tabulated using surrounding points or values (that is, estimating an unknown value based on surrounding information). **Extrapolation** means finding or concluding something by assuming that existing trends will continue, or a current method will remain applicable beyond existing known values (that is, following a pattern beyond the known data points). \\n\\nInterpolation and extrapolation are similar, but because extrapolation involves estimating beyond the known data points, this approach is subject to greater uncertainty and has a higher risk of producing more imprecise or potentially even meaningless results compared with interpolation. \\n\\nThe assessment is situated in the unit context to provide an opportunity for students to make sense about extrapolation and interpolation of a specific, tangible weather problem (i.e., temperatures in a two-dimensional area at one point in time). While extrapolation is associated with higher levels of uncertainty, it\u2019s also sometimes necessary. This is true, for example, for forecasting (prediction). Prediction of future weather will always involve extrapolation (i.e., extending the pattern of weather data into the future given that observed data cannot be obtained for the future until time passes and the future becomes the present!). Uncertainty associated with extrapolation is why there\u2019s always some level of uncertainty in weather forecasts. Basically, this is why weather forecasts are sometimes wrong. There is always some uncertainty associated with interpolation too, though generally it is less so than with extrapolation.\\n\\nThis assessment also relates to **pattern recognition** and **data aggregation**. **Pattern recognition** involves identifying patterns and trends within and across groups of data/information as seen in the observable world. Students employ **pattern recognition** in this assessment as they view the distribution of temperatures in the map grid and make sense of patterns and trends across the grid (in both observed and estimated values) to think about the question. **Data aggregation** involves determining the appropriate data to collect or generate in order to study the identified phenomenon. Students should consider more and less appropriate ways to aggregate data in the map grid as they figure out which response they think is best. For example, students should be think about which cells in the grid have enough data to estimate temperatures for from collected data, and which temperatures might be problematic to estimate \u2013 meaning we might need to collect more data to generate a good estimate for temperatures in those cells. \\n\\nWhile one of the responses makes the most sense from a practical standpoint for this particular problem, there\u2019s no absolutely correct answer. Using an indefinite problem provides space for students to think and talk about how much confidence we can have in different interpolated and extrapolated values. \",\"content2\":\"\",\"mediaType\":\"none\",\"mediaCaption\":\"Last, First. \\\"Title of Work.\\\" Year created. Site Title [OR] Publisher. 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The values in parentheses are all estimated, so having other estimated values near the value that Kalin chooses would not necessarily make us more confident about Kalin\u2019s choice. If there were additional observed values near the cell that Kalin chose, that would help boost our confidence. We can feel more confident about interpolated values for data the more observed data values we have for a given area. \\n\\nStudents who choose 39\u00b0 as the most uncertain value could benefit from discussions about the difference between observed data points and estimated data points. Students can think about which types of values are more trustworthy and why (e.g., local conditions like elevation changes or water bodies could affect local values, making estimated temperatures less reliable than observed values). Students may come up with potential problems with observed values too (e.g., a faulty thermometer), which is fine. \\n\\n\\n###Middle Level\\n\u2022\\t**Sage\u2019s response (37\u00b0)** suggests that she may be thinking beyond interpolation to also consider weather processes (e.g., movement of air masses across Alaska). While that shows some good thinking, the values on the assessment probe map all represent one point in time, so we would be less concerned about air movement over time and issues like east versus west in Alaska for this particular problem. \\n\\nLater in the unit, students who chose 37\u00b0 may benefit from discussions that emphasize the difference between interpolating data from known values at one point in time versus doing things like making predictions into the future across a two-dimensional area based on known information such as wind speed, wind direction, etc. \\n\\n\\n###Upper Middle Level\\n\u2022\\t**Delana\u2019s response (43\u00b0)** suggests that she understands that we can be more confident about estimates when we have observed values nearby. We should be less confident about interpolated data (there are many estimated values near the 43\u00b0 cell) nearby in comparison with nearby observed data.\\n\\nWhile students who choose Delana\u2019s response have useful ideas about confidence and interpolation, they could also benefit from some scaffolding to reason more deeply about interpolation versus extrapolation. Moving beyond the area of known data points (i.e., extrapolation) is generally associated with higher uncertainty compared with interpolation. For example, if there is a weather front just to the east of the 46\u00b0 and 51\u00b0 measured temperature values, the 53\u00b0 estimated value could be quite different from what an actual observed measurement taken at that location would be. \\n\\n\\n###More Formal Idea\\n\u2022\\t**Alex\u2019s response (53\u00b0)** and rationale recognizes the problems associated with extrapolation beyond known data points. 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All five weather station observations were made at the same time on the same day. The map also shows some temperatures that were estimated using the weather station observation data (estimated temperatures are in parentheses).\u003C/p\u003E\r\n\u003Cp\u003E\u003Cimg style=\"display: block; margin-left: auto; margin-right: auto;\" src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/L3AssessmentProbeMap.png\" width=\"555\" height=\"444\" /\u003E\u003C/p\u003E\r\n\u003Cp\u003EMs. Tevuk asks the students which of the estimated temperatures they are LEAST CERTAIN (MOST UNSURE) about.\u003C/p\u003E\r\n\u003Cp\u003EHere are the students\u0026rsquo; ideas. (Each student\u0026rsquo;s estimated temperature choice is in \u003Cstrong\u003Ebold\u003C/strong\u003E to make it easier to find.)\u003C/p\u003E\r\n\u003Ctable cellpadding=\"30\"\u003E\r\n\u003Ctbody\u003E\r\n\u003Ctr\u003E\r\n\u003Cth colspan=\"2\"\u003E\u003Cstrong\u003EAlex\u003C/strong\u003E\u003C/th\u003E\r\n\u003Cth colspan=\"2\"\u003E\u003Cstrong\u003EDelana\u003C/strong\u003E\u003C/th\u003E\r\n\u003C/tr\u003E\r\n\u003Ctr\u003E\r\n\u003Ctd width=\"88\"\u003E\u003Cimg src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/Alex1-1.png\" width=\"80\" height=\"100\" align=\"center\" hspace=\"10\" vspace=\"10\" /\u003E\u003C/td\u003E\r\n\u003Ctd style=\"padding: 10px;\" width=\"350\"\u003E\r\n\u003Cp\u003EI\u0026rsquo;m least certain about the estimate of \u003Cstrong\u003E53\u02da\u003C/strong\u003E because it\u0026rsquo;s furthest outside of the temperatures that were actually measured at a weather station.\u003C/p\u003E\r\n\u003Cp\u003E\u003Cimg style=\"display: block; margin-left: auto; margin-right: auto;\" src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/Lesson3AlexsChoice.png\" width=\"223\" height=\"200\" /\u003E\u003C/p\u003E\r\n\u003C/td\u003E\r\n\u003Ctd width=\"88\"\u003E\u003Cimg src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/Delana2.png\" width=\"80\" height=\"100\" align=\"center\" hspace=\"10\" vspace=\"10\" /\u003E\u003C/td\u003E\r\n\u003Ctd style=\"padding: 10px;\" width=\"350\"\u003E\r\n\u003Cp\u003EI\u0026rsquo;m least certain about the estimate of \u003Cstrong\u003E43\u02da\u003C/strong\u003E because it\u0026rsquo;s far away from any temperatures measured at a weather station.\u0026nbsp;\u003C/p\u003E\r\n\u003Cp\u003E\u003Cimg style=\"display: block; margin-left: auto; margin-right: auto;\" src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/Lesson3DelanasChoice.png\" width=\"222\" height=\"200\" /\u003E\u003C/p\u003E\r\n\u003C/td\u003E\r\n\u003C/tr\u003E\r\n\u003C/tbody\u003E\r\n\u003Ctbody\u003E\r\n\u003Ctr\u003E\r\n\u003Cth colspan=\"2\"\u003E\u003Cstrong\u003EKalin\u003C/strong\u003E\u003C/th\u003E\r\n\u003Cth colspan=\"2\"\u003E\u003Cstrong\u003ESage\u003C/strong\u003E\u003C/th\u003E\r\n\u003C/tr\u003E\r\n\u003Ctr\u003E\r\n\u003Ctd width=\"88\"\u003E\r\n\u003Cp\u003E\u003Cimg src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/Kalin3.png\" width=\"80\" height=\"100\" align=\"center\" hspace=\"10\" vspace=\"10\" /\u003E\u003C/p\u003E\r\n\u003C/td\u003E\r\n\u003Ctd style=\"padding: 10px;\" width=\"350\"\u003E\r\n\u003Cp\u003EI\u0026rsquo;m least certain about the estimate of \u003Cstrong\u003E39\u02da\u003C/strong\u003E because there aren\u0026rsquo;t any other estimated temperatures near the 39\u02da estimate.\u003C/p\u003E\r\n\u003Cp\u003E\u003Cimg style=\"display: block; margin-left: auto; margin-right: auto;\" src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/Lesson3KalinsChoice.png\" width=\"230\" height=\"204\" /\u003E\u003C/p\u003E\r\n\u003C/td\u003E\r\n\u003Ctd width=\"88\"\u003E\r\n\u003Cp\u003E\u003Cimg src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/Lesson3SageAvatar.png\" width=\"80\" height=\"100\" align=\"center\" hspace=\"8\" vspace=\"8\" /\u003E\u003C/p\u003E\r\n\u003C/td\u003E\r\n\u003Ctd style=\"padding: 10px;\" width=\"350\"\u003E\r\n\u003Cp\u003EI\u0026rsquo;m least certain about the estimate of \u003Cstrong\u003E37\u02da\u003C/strong\u003E because weather usually moves from west to east, so I\u0026rsquo;m unsure about estimates on the west side of the map.\u003C/p\u003E\r\n\u003Cp\u003E\u003Cimg class=\"\" style=\"display: block; margin-left: auto; margin-right: auto;\" src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/Lesson3SagesChoice.png\" alt=\"\" width=\"230\" height=\"206\" /\u003E\u003C/p\u003E\r\n\u003C/td\u003E\r\n\u003C/tr\u003E\r\n\u003C/tbody\u003E\r\n\u003C/table\u003E", + "is_callout": false, + "is_full_width": true, + "is_hidden": false, + "name": "", + "type": "Embeddable::Xhtml", + "ref_id": "147895-Embeddable::Xhtml" + }, + "section": "header_block" + }, { + "embeddable": { + "plugin": { + "description": null, + "author_data": "{\"tipType\":\"windowShade\",\"windowShade\":{\"windowShadeType\":\"teacherTip\",\"layout\":\"mediaLeft\",\"initialOpenState\":true,\"content\":\"###Pre-Assessment Implementation\\n*Lesson 3, Opening: Which Estimates Should We Trust? Pre-Assessment*\\nDuring the pre-assessment, each student will view the probe and make an individual choice. The request for explanation will only be on the post-assessment implementation. After students make an individual choice for the pre-assessment, you can lead discussion including, for example, a pair/share opportunity and/or full class discussion. \\n\\nAt this time, encourage students to share and discuss their ideas and reasons without indicating that any one answer is better or worse. Let the students know that they should keep thinking about this question and that the class will return to it at the end of the lesson.\",\"content2\":\"\",\"mediaType\":\"none\",\"mediaCaption\":\"Last, First. \\\"Title of Work.\\\" Year created. Site Title [OR] Publisher. 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Review the information below and think about ways to scaffold students toward developing knowledge and practice as appropriate for their classes. Also, we recommend that during the first implementation of the probe, that you scaffold students to focus on their own ideas about this problem, rather than on vocabulary terms such as **interpolation** and **extrapolation**. By discussing the different options, students can engage in productive talk related to these data sense making and computational thinking concepts without necessarily using technical terminology. During the ensuing lesson and the second implementation of the probe, the terms **interpolation** and **extrapolation** can be used, if appropriate.\\n\\nThis assessment probe is designed to assess and scaffold students in thinking and talking about **interpolation** and **extrapolation**. **Interpolation** means finding an estimation of a value between ones that are known or tabulated using surrounding points or values (that is, estimating an unknown value based on surrounding information). **Extrapolation** means finding or concluding something by assuming that existing trends will continue, or a current method will remain applicable beyond existing known values (that is, following a pattern beyond the known data points). \\n\\nInterpolation and extrapolation are similar, but because extrapolation involves estimating beyond the known data points, this approach is subject to greater uncertainty and has a higher risk of producing more imprecise or potentially even meaningless results compared with interpolation. \\n\\nThe assessment is situated in the unit context to provide an opportunity for students to make sense about extrapolation and interpolation of a specific, tangible weather problem (i.e., temperatures in a two-dimensional area at one point in time). While extrapolation is associated with higher levels of uncertainty, it\u2019s also sometimes necessary. This is true, for example, for forecasting (prediction). Prediction of future weather will always involve extrapolation (i.e., extending the pattern of weather data into the future given that observed data cannot be obtained for the future until time passes and the future becomes the present!). Uncertainty associated with extrapolation is why there\u2019s always some level of uncertainty in weather forecasts. Basically, this is why weather forecasts are sometimes wrong. There is always some uncertainty associated with interpolation too, though generally it is less so than with extrapolation.\\n\\nThis assessment also relates to **pattern recognition** and **data aggregation**. **Pattern recognition** involves identifying patterns and trends within and across groups of data/information as seen in the observable world. Students employ **pattern recognition** in this assessment as they view the distribution of temperatures in the map grid and make sense of patterns and trends across the grid (in both observed and estimated values) to think about the question. **Data aggregation** involves determining the appropriate data to collect or generate in order to study the identified phenomenon. Students should consider more and less appropriate ways to aggregate data in the map grid as they figure out which response they think is best. For example, students should be think about which cells in the grid have enough data to estimate temperatures for from collected data, and which temperatures might be problematic to estimate \u2013 meaning we might need to collect more data to generate a good estimate for temperatures in those cells. \\n\\nWhile one of the responses makes the most sense from a practical standpoint for this particular problem, there\u2019s no absolutely correct answer. Using an indefinite problem provides space for students to think and talk about how much confidence we can have in different interpolated and extrapolated values. \",\"content2\":\"\",\"mediaType\":\"none\",\"mediaCaption\":\"Last, First. \\\"Title of Work.\\\" Year created. Site Title [OR] Publisher. 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The values in parentheses are all estimated, so having other estimated values near the value that Kalin chooses would not necessarily make us more confident about Kalin\u2019s choice. If there were additional observed values near the cell that Kalin chose, that would help boost our confidence. We can feel more confident about interpolated values for data the more observed data values we have for a given area. \\n\\nStudents who choose 39\u00b0 as the most uncertain value could benefit from discussions about the difference between observed data points and estimated data points. Students can think about which types of values are more trustworthy and why (e.g., local conditions like elevation changes or water bodies could affect local values, making estimated temperatures less reliable than observed values). Students may come up with potential problems with observed values too (e.g., a faulty thermometer), which is fine. \\n\\n\\n###Middle Level\\n\u2022\\t**Sage\u2019s response (37\u00b0)** suggests that she may be thinking beyond interpolation to also consider weather processes (e.g., movement of air masses across Alaska). While that shows some good thinking, the values on the assessment probe map all represent one point in time, so we would be less concerned about air movement over time and issues like east versus west in Alaska for this particular problem. \\n\\nLater in the unit, students who chose 37\u00b0 may benefit from discussions that emphasize the difference between interpolating data from known values at one point in time versus doing things like making predictions into the future across a two-dimensional area based on known information such as wind speed, wind direction, etc. \\n\\n\\n###Upper Middle Level\\n\u2022\\t**Delana\u2019s response (43\u00b0)** suggests that she understands that we can be more confident about estimates when we have observed values nearby. We should be less confident about interpolated data (there are many estimated values near the 43\u00b0 cell) nearby in comparison with nearby observed data.\\n\\nWhile students who choose Delana\u2019s response have useful ideas about confidence and interpolation, they could also benefit from some scaffolding to reason more deeply about interpolation versus extrapolation. Moving beyond the area of known data points (i.e., extrapolation) is generally associated with higher uncertainty compared with interpolation. For example, if there is a weather front just to the east of the 46\u00b0 and 51\u00b0 measured temperature values, the 53\u00b0 estimated value could be quite different from what an actual observed measurement taken at that location would be. \\n\\n\\n###More Formal Idea\\n\u2022\\t**Alex\u2019s response (53\u00b0)** and rationale recognizes the problems associated with extrapolation beyond known data points. 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She will discuss how air moisture plays an important part in forming precipitation.\u003C/p\u003E", + "is_callout": true, + "is_full_width": true, + "is_hidden": false, + "name": "", + "type": "Embeddable::Xhtml", + "ref_id": "148013-Embeddable::Xhtml" + }, + "section": "header_block" + }, { + "embeddable": { + "name": "", + "url_fragment": null, + "authored_state": "{\"version\":1,\"questionType\":\"iframe_interactive\",\"videoUrl\":\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/Captioned_Videos/JackieLesson3_88_Captioned.mp4\",\"poster\":\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/Captioned_Videos/Posters/Poster_L3_Video.png\"}", + "is_hidden": false, + "is_full_width": true, + "show_in_featured_question_report": true, + "inherit_aspect_ratio_method": true, + "custom_aspect_ratio_method": null, + "inherit_native_width": true, + "custom_native_width": 576, + "inherit_native_height": true, + "custom_native_height": 435, + "inherit_click_to_play": true, + "custom_click_to_play": false, + "inherit_full_window": true, + "custom_full_window": false, + "inherit_click_to_play_prompt": true, + "custom_click_to_play_prompt": null, + "inherit_image_url": true, + "custom_image_url": null, + "library_interactive": { + "hash": "34e1a2a39c058da8ff4ffe5a09ad14af337c4a01", + "data": { + "aspect_ratio_method": "DEFAULT", + "authoring_guidance": "", + "base_url": "https://models-resources.concord.org/question-interactives/version/v1.1.0/video-player/", + "click_to_play": false, + "click_to_play_prompt": null, + "description": "This video player will not have the blue header bar above the interactive.\r\nIt does not save the students position in the video. \r\nIt will not show up in the teacher report.", + "enable_learner_state": false, + "full_window": false, + "has_report_url": false, + "image_url": null, + "name": "Video Player", + "native_height": 435, + "native_width": 576, + "no_snapshots": false, + "show_delete_data_button": false, + "thumbnail_url": "", + "customizable": false, + "authorable": true + } + }, + "type": "ManagedInteractive", + "ref_id": "1765-ManagedInteractive", + "linked_interactives": [] + }, + "section": "header_block" + }] + }, { + "additional_sections": {}, + "embeddable_display_mode": "stacked", + "id": 143588, + "is_completion": false, + "is_hidden": false, + "layout": "l-full-width", + "name": "Opening", + "position": 2, + "show_header": true, + "show_info_assessment": true, + "show_interactive": false, + "show_sidebar": false, + "sidebar": null, + "sidebar_title": "Did you know?", + "toggle_info_assessment": false, + "embeddables": [{ + "embeddable": { + "content": "\u003Cp\u003EEXPLORING PRECIPITATION, AIR MOISTURE AND TEMPERATURE\u003C/p\u003E\n\u003Cp\u003EHave you ever been caught without your parka or boots when you needed them? Predicting rain or snow\u0026nbsp;is a special challenge for weather scientists. Watch the video below to learn more about forecasting the weather in Alaska.\u003C/p\u003E\n\u003Cp\u003EAs weather scientists, you will continue to explore the weather maps. This time you will add two additional pieces of information to each square: precipitation (a symbol) and air moisture content (a number).\u003C/p\u003E\n\u003Cp\u003E\u0026nbsp;\u003C/p\u003E\n\u003Cp style=\"text-align: center;\"\u003E\u003Cstrong\u003EPrecipitation symbol = raindrops\u003C/strong\u003E\u0026nbsp;\u0026nbsp;\u003Cimg class=\"\" src=\"https://precipitatingchange-resources.concord.org/images/3-drop-black-staggered.png\" alt=\"\" width=\"48\" height=\"48\" /\u003E\u0026nbsp;\u003C/p\u003E\n\u003Cp\u003E\u0026nbsp;\u003C/p\u003E\n\u003Cp\u003E\u003Cimg class=\"\" style=\"display: block; margin-left: auto; margin-right: auto;\" src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/Air%20Moisture.jpg\" alt=\"\" width=\"588\" height=\"141\" /\u003E\u003C/p\u003E\n\u003Cp\u003E\u0026nbsp;\u003C/p\u003E", + "is_callout": false, + "is_full_width": true, + "is_hidden": false, + "name": "", + "type": "Embeddable::Xhtml", + "ref_id": "147890-Embeddable::Xhtml" + }, + "section": "header_block" + }, { + "embeddable": { + "plugin": { + "description": "", + "author_data": "{\"tipType\":\"windowShade\",\"questionWrapper\":{\"correctExplanation\":\"correct\",\"distractorsExplanation\":\"distractor\",\"exemplar\":\"exemplar\",\"teacherTip\":\"teacherTip\",\"teacherTipImageOverlay\":\"\"},\"windowShade\":{\"windowShadeType\":\"theoryAndBackground\",\"layout\":\"mediaLeft\",\"initialOpenState\":false,\"content\":\"### LESSON 3: BUILDING RULES:\\n**WHERE DOES IT RAIN?**\\n\\nIn this lesson, students revisit the weather maps they constructed in Lesson 2 and add precipitation and air moisture data for additional time stamps to the weather maps to answer the question \\\"Where does it rain?\\\" Precipitation is a result of the complex interactions between temperature and moisture. Atmospheric scientists construct graphical displays of temperature and moisture content data to help them come up with rules to identify where precipitation occurs. \\n\\nThis lesson introduces a new way of utilizing the virtual simulation that allows students to start recognizing patterns and formalizing their rule statements with the data set they have been exploring in Lesson 2.\\n\\n**LEARNING GOALS**\\n\\nStudents will be able to:\\n\\n* Describe the relationship between moisture content and temperature by identifying key patterns in weather data\\n\\n* Develop a rule for where precipitation will occur using precise language\\n\\n* Explain the current weather conditions in their local context\\n\\n* Read weather maps using traditional symbols and codes (adding precipitation)\\n\\n* Use CT strategies (rule abstraction, rule development and rule testing) to develop a better understanding of how to model weather\\n\\nComputational Thinking (CT) skills introduced in this lesson can be found in the table below:\\n\\n| CT Skill | Definition | Use in Lesson |\\n|---------------------|---------------------------------------------------------------------------------------------------|------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|\\n| Pattern Recognition | Recognizing that data or information is repeating in a logical (expected) way. Students develop a general statement to answer the question \\\"Where does it rain?\\\"|\\n| Rule Abstraction | Developing a statement of how things work based on observed patterns. | Students make a generic statement to answer \\\"Where does it rain?\\\" |\\n| Rule Testing | Investigating whether a rule will still be true in different situations. | Virtual model activity |\\n| Rule Refinement | Modifying a rule to be more precise (exact, careful about details) to work in the model.| The virtual model allows students to be able to test their rule statements and make changes based on the model. |\\t\",\"content2\":\"\",\"mediaType\":\"none\",\"mediaCaption\":\"Last, First. \\\"Title of Work.\\\" Year created. Site Title [OR] Publisher. 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Yes or No\u003C/p\u003E\n\u003Cp\u003EIf yes, what would you change and why?\u003C/p\u003E", + "sidebar_title": "Did you know?", + "toggle_info_assessment": false, + "embeddables": [{ + "embeddable": { + "content": "\u003Cp\u003EEXPLORING PRECIPITATION, AIR MOISTURE, AND TEMPERATURE\u003C/p\u003E\n\u003Cp\u003EPretend your classroom represents mainland Alaska and the same virtual storm will move through your classroom. As expert weather scientists, you already know how to combine the data (also known as data aggregation) from this event. This time you are going to focus on collecting precipitation data.\u003C/p\u003E", + "is_callout": false, + "is_full_width": true, + "is_hidden": false, + "name": "", + "type": "Embeddable::Xhtml", + "ref_id": "147891-Embeddable::Xhtml" + }, + "section": "header_block" + }, { + "embeddable": { + "content": "\u003Cp\u003EMap where it is raining at 3 pm. Work in teams to collect data to fill in the map. Look for relationships between rain and temperature.\u003C/p\u003E\r\n\u003Cp\u003EYou will see precipitation as the following symbol on your weather station.\u003C/p\u003E\r\n\u003Cp\u003EPrecipitation = raindrops\u0026nbsp;\u0026nbsp;\u003Cimg class=\"\" src=\"https://precipitatingchange-resources.concord.org/images/3-drop-black-staggered.png\" alt=\"\" width=\"48\" height=\"48\" /\u003E\u0026nbsp;\u003C/p\u003E", + "is_callout": true, + "is_full_width": true, + "is_hidden": false, + "name": "TASK ", + "type": "Embeddable::Xhtml", + "ref_id": "147892-Embeddable::Xhtml" + }, + "section": null + }, { + "embeddable": { + "default_text": "", + "give_prediction_feedback": false, + "hint": "\u003Cp\u003E\u0026bull; Where is it raining?\u003C/p\u003E\r\n\u003Cp\u003E\u0026bull; Where is it not raining?\u003C/p\u003E\r\n\u003Cp\u003E\u003Cbr /\u003E\u0026bull; Describe what the shape of the rain area looks like.\u003C/p\u003E\r\n\u003Cp\u003E\u003Cbr /\u003E\u0026bull; Where on the map is there light (1 raindrop), moderate (2 raindrops) or heavy (3 raindrops) precipitation?\u003C/p\u003E", + "is_full_width": true, + "is_hidden": false, + "is_prediction": false, + "name": "", + "prediction_feedback": "", + "prompt": "\u003Cp\u003ELook at your classroom weather map for 3 pm. What patterns do you see when looking at both precipitation and temperature?\u003C/p\u003E", + "show_in_featured_question_report": true, + "type": "Embeddable::OpenResponse", + "ref_id": "208877-Embeddable::OpenResponse" + }, + "section": null + }, { + "embeddable": { + "plugin": { + "description": "", + "author_data": "{\"tipType\":\"windowShade\",\"questionWrapper\":{\"correctExplanation\":\"correct\",\"distractorsExplanation\":\"distractor\",\"exemplar\":\"exemplar\",\"teacherTip\":\"teacherTip\",\"teacherTipImageOverlay\":\"\"},\"windowShade\":{\"windowShadeType\":\"theoryAndBackground\",\"layout\":\"mediaLeft\",\"initialOpenState\":false,\"content\":\"###Activity 1- Virtual Storm: Exploring Precipitation, Air Moisture, and Temperature\\nThis activity is a continuation of the Virtual Storm simulation and has a similar set-up to the Lesson 2 - Virtual Storm. \\n\\nKey additions in this activity include:\\n\\n* Reusing the 7 am, 11 am, and 3 pm weather map created in Lesson 2.\\n\\n* Pausing the simulation at 3 pm and completely filling in each square. \\n\\nAdditionally, this lesson provides students with an opportunity to explore and explain why it rains in some areas and not others. 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Can you determine at night what the\u0026nbsp;weather\u0026nbsp;will be the following morning? What kind of information goes into a\u0026nbsp;weather\u0026nbsp;prediction?\u003C/p\u003E", + "is_callout": false, + "is_full_width": true, + "is_hidden": false, + "name": "", + "type": "Embeddable::Xhtml", + "ref_id": "147893-Embeddable::Xhtml" + }, + "section": "header_block" + }, { + "embeddable": { + "content": "\u003Cp\u003EAdd air moisture content to your classroom weather maps. Work in teams to collect data to fill in the map.\u003C/p\u003E", + "is_callout": true, + "is_full_width": true, + "is_hidden": false, + "name": "TASK", + "type": "Embeddable::Xhtml", + "ref_id": "147894-Embeddable::Xhtml" + }, + "section": null + }, { + "embeddable": { + "default_text": "", + "give_prediction_feedback": false, + "hint": "\u003Cp\u003E\u0026bull; Where is it the air most wet?\u003C/p\u003E\r\n\u003Cp\u003E\u0026bull; Where is the air most dry?\u003C/p\u003E\r\n\u003Cp\u003E\u0026bull; Is there a relationship between air moisture and temperature?\u003C/p\u003E\r\n\u003Cp\u003E\u0026bull; Is there a relationship between air moisture and precipitation?\u003C/p\u003E\r\n\u003Cp\u003E\u0026bull; Is there a relationship between air moisture and where there is light (1 raindrop), moderate (2 raindrops) or heavy (3 raindrops) precipitation?\u003C/p\u003E", + "is_full_width": true, + "is_hidden": false, + "is_prediction": false, + "name": "", + "prediction_feedback": "", + "prompt": "\u003Cp\u003ELook at your classroom weather map for 3 pm. What relationships do you see between temperature, air moisture, and rain?\u003C/p\u003E", + "show_in_featured_question_report": true, + "type": "Embeddable::OpenResponse", + "ref_id": "208878-Embeddable::OpenResponse" + }, + "section": null + }, { + "embeddable": { + "plugin": { + "description": "", + "author_data": "{\"tipType\":\"windowShade\",\"questionWrapper\":{\"correctExplanation\":\"correct\",\"distractorsExplanation\":\"distractor\",\"exemplar\":\"exemplar\",\"teacherTip\":\"teacherTip\",\"teacherTipImageOverlay\":\"\"},\"windowShade\":{\"windowShadeType\":\"theoryAndBackground\",\"layout\":\"mediaLeft\",\"initialOpenState\":false,\"content\":\"###Activity 1: Virtual Storm: Exploring Precipitation, Air Moisture and Temperature (Continued)\\n\\n###Activity Breakdown\\n\\n**1. Set up Round 2 by leaving the Virtual Storm at 3 pm.** Explain to students that their new question is: \\\"Why is it raining in some locations and not others? Where does it rain?\\\"\\n\\n**2. 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Where does it rain?\\\" Another variable, such as air moisture content, is needed. \\n\\n* Briefly introduce the concept of air moisture content. Explain to the students that air contains microscopic water particles, called water vapor. Air moisture content refers to how much water vapor is in the air.\\n\\n* Reference possible students\u2019 past experiences with very moist air (e.g., in the shower or steam room) and/or very dry air (e.g., in a sauna or in the winter). The amount of water vapor is illustrated by an air moisture content number where 0 = very dry air and 10 = very moist air. Students may remember this concept from the data tables they received in Lesson 1.\\n\\n**Teacher Note**: The air moisture data students receive will already be abstracted, so no further abstraction is needed. It is expressed as a single number on a scale of 0 to 10, with 10 having the most water. 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00000000..f30b308c --- /dev/null +++ b/src/public/offline-activities/precipitating-change-v1/lesson-4-post.json @@ -0,0 +1,248 @@ +{ + "description": "\u003Cp\u003EBuilding Rules: Where does it rain?\u003C/p\u003E", + "editor_mode": 0, + "layout": 0, + "name": "Alaska 2021 - Lesson 4: Post-thoughts - What Do You Think?", + "notes": "", + "project_id": 25, + "related": "", + "runtime": "Activity Player", + "show_submit_button": true, + "student_report_enabled": true, + "thumbnail_url": "https://learn-resources.concord.org/images/stem-resources/icons/pc-lesson3.png", + "time_to_complete": null, + "version": 1, + "theme_name": "Precipitating Change", + "pages": [{ + "additional_sections": {}, + "embeddable_display_mode": "stacked", + "id": 143598, + "is_completion": false, + "is_hidden": false, + "layout": "l-full-width", + "name": "Page 1", + "position": 1, + "show_header": true, + "show_info_assessment": true, + "show_interactive": false, + "show_sidebar": false, + "sidebar": null, + "sidebar_title": "Did you know?", + "toggle_info_assessment": false, + "embeddables": [{ + "embeddable": { + "content": "\u003Cp\u003E\u003Cstrong\u003EWhat Are the Rules for Fronts and Precipitation?\u003C/strong\u003E\u003C/p\u003E\r\n\u003Cp\u003EMs. Tevuk\u0026rsquo;s students need to write a rule for their computer model to predict areas of precipitation on a map showing weather fronts. They have different ideas for what the rule should be.\u003C/p\u003E\r\n\u003Cp\u003EHere are the students\u0026rsquo; ideas: The rule should be that precipitation happens\u0026hellip;\u003C/p\u003E\r\n\u003Ctable cellpadding=\"30\"\u003E\r\n\u003Ctbody\u003E\r\n\u003Ctr\u003E\r\n\u003Cth colspan=\"2\"\u003E\u003Cstrong\u003EAlex\u003C/strong\u003E\u003C/th\u003E\r\n\u003Cth colspan=\"2\"\u003E\u003Cstrong\u003EDelana\u003C/strong\u003E\u003C/th\u003E\r\n\u003C/tr\u003E\r\n\u003Ctr\u003E\r\n\u003Ctd width=\"88\"\u003E\u003Cimg src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/Alex4.png\" width=\"72\" height=\"90\" align=\"center\" hspace=\"10\" vspace=\"10\" /\u003E\u003C/td\u003E\r\n\u003Ctd style=\"padding: 10px;\" width=\"350\"\u003E\u003Cstrong\u003Ewith a warm front coming in\u003C/strong\u003E because warm air moves in and mixes with cold air, which leads to precipitation. You don\u0026rsquo;t get precipitation with a cold front because cold air is dry.\u003C/td\u003E\r\n\u003Ctd width=\"88\"\u003E\u003Cimg src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/Delana4.png\" width=\"70\" height=\"90\" align=\"center\" hspace=\"10\" vspace=\"10\" /\u003E\u003C/td\u003E\r\n\u003Ctd style=\"padding: 10px;\" width=\"350\"\u003E\u003Cstrong\u003Ewith both cold fronts and warm fronts coming in\u003C/strong\u003E because in both cases warm air and cold air meet, leading to condensation and precipitation.\u003C/td\u003E\r\n\u003C/tr\u003E\r\n\u003C/tbody\u003E\r\n\u003Ctbody\u003E\r\n\u003Ctr\u003E\r\n\u003Cth colspan=\"2\"\u003E\u003Cstrong\u003EKalin\u003C/strong\u003E\u003C/th\u003E\r\n\u003Cth colspan=\"2\"\u003E\u003Cstrong\u003ESage\u003C/strong\u003E\u003C/th\u003E\r\n\u003C/tr\u003E\r\n\u003Ctr\u003E\r\n\u003Ctd width=\"88\"\u003E\r\n\u003Cp\u003E\u003Cimg src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/Kalin6.png\" width=\"72\" height=\"90\" align=\"center\" hspace=\"10\" vspace=\"10\" /\u003E\u003C/p\u003E\r\n\u003C/td\u003E\r\n\u003Ctd style=\"padding: 10px;\" width=\"350\"\u003E\u003Cstrong\u003Ewith a cold front coming in\u003C/strong\u003E because it\u0026rsquo;s usually rainy or snowy when it\u0026rsquo;s cold out. You don\u0026rsquo;t get precipitation with a warm front because it\u0026rsquo;s warm when the sun is shining.\u003C/td\u003E\r\n\u003Ctd width=\"88\"\u003E\r\n\u003Cp\u003E\u003Cimg src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/Sage2.png\" width=\"72\" height=\"90\" align=\"center\" hspace=\"8\" vspace=\"8\" /\u003E\u003C/p\u003E\r\n\u003C/td\u003E\r\n\u003Ctd style=\"padding: 10px;\" width=\"350\"\u003E\u003Cstrong\u003Eafter a cold front has passed by\u003C/strong\u003E because the cold air the front leaves behind is humid, which leads to precipitation.\u003C/td\u003E\r\n\u003C/tr\u003E\r\n\u003C/tbody\u003E\r\n\u003C/table\u003E", + "is_callout": false, + "is_full_width": true, + "is_hidden": false, + "name": "", + "type": "Embeddable::Xhtml", + "ref_id": "147904-Embeddable::Xhtml" + }, + "section": "header_block" + }, { + "embeddable": { + "plugin": { + "description": null, + "author_data": "{\"tipType\":\"windowShade\",\"windowShade\":{\"windowShadeType\":\"teacherTip\",\"layout\":\"mediaLeft\",\"initialOpenState\":true,\"content\":\"###Pre-Assessment Implementation\\n*Lesson 4, Opening: What Are the Rules for Fronts and Precipitation? Pre-Assessment*\\nDuring the pre-assessment, each student will view the probe and make an individual choice. The request for explanation will only be on the post-assessment. After students make an individual choice for the pre-assessment, the teacher can lead discussion including, for example, a pair/share opportunity and/or full class discussion. \\n\\nAt this time, encourage students to share and discuss their ideas and reasons without indicating that any one answer is better or worse. Let the students know that they should keep thinking about this question and that the class will return to it at the end of the next lesson (Lesson 5).\",\"content2\":\"\",\"mediaType\":\"none\",\"mediaCaption\":\"Last, First. \\\"Title of Work.\\\" Year created. Site Title [OR] Publisher. Gallery [OR] Location. http://www.url.com.\",\"mediaURL\":\"\"}}", + "approved_script_label": "teacherEditionTips", + "component_label": "windowShade", + "approved_script": { + "name": "Teacher Edition", + "url": "https://teacher-edition-tips-plugin.concord.org/version/v3.6.0/plugin.js", + "label": "teacherEditionTips", + "description": "This plugin provides Teacher Edition components", + "version": 3, + "json_url": "https://teacher-edition-tips-plugin.concord.org/version/v3.6.0/manifest.json", + "authoring_metadata": "{\"components\":[{\"label\":\"windowShade\",\"name\":\"Window Shades\",\"scope\":\"embeddable\",\"guiAuthoring\":true},{\"label\":\"sideTip\",\"name\":\"Side Tips\",\"scope\":\"embeddable\",\"guiAuthoring\":true},{\"label\":\"questionWrapper\",\"name\":\"Question Wrapper\",\"scope\":\"embeddable-decoration\",\"decorates\":[\"Embeddable::MultipleChoice\",\"Embeddable::OpenResponse\",\"Embeddable::ImageQuestion\",\"ManagedInteractive\",\"MwInteractive\",\"ImageInteractive\",\"VideoInteractive\"],\"guiAuthoring\":true,\"guiPreview\":true}]}" + } + }, + "is_hidden": false, + "is_full_width": true, + "type": "Embeddable::EmbeddablePlugin", + "ref_id": "10256-Embeddable::EmbeddablePlugin" + }, + "section": null + }, { + "embeddable": { + "plugin": { + "description": null, + "author_data": "{\"tipType\":\"windowShade\",\"windowShade\":{\"windowShadeType\":\"theoryAndBackground\",\"layout\":\"mediaLeft\",\"initialOpenState\":true,\"content\":\"###Computational Thinking Concepts and Practices:\\n* Pattern Recognition\\n* Data-based Prediction\\n* Rule Abstraction\\n\\n###What is the Purpose of this Assessment Probe?\\nThe following information provides background for teachers. We suggest teachers review the information below and think about ways to scaffold students toward developing knowledge and practice as appropriate for their classes. Also, we recommend that during the first implementation of the probe, teachers scaffold students to focus on students\u2019 own ideas about this problem. By discussing the different options, students can engage in productive talk related to the different response patterns, priming them to look for productive patterns to associate with precipitation in the upcoming lessons. \\n\\nDuring the ensuing two lessons and the second implementation of the probe, students should be able to use the data from the virtual storm to identify the patterns of temperature, humidity, and movement that are associated with precipitation.\\n\\nThis assessment probe is designed to assess and scaffold students in thinking and talking about how patterns of data (i.e., temperature, humidity, and air movement) are associated with precipitation in a location. To keep things simple, we only focus on two types of fronts: cold fronts and warm fronts. Both types of fronts can be associated with precipitation. Identifying patterns associated with precipitation is an example of the computational thinking practice of **Pattern Recognition**. Once patterns associated with precipitation are identified, they can be used in conjunction with data to make a **Data-based Prediction**, which is what Ms. Tevuk\u2019s students are trying to do in the scenario for this assessment probe. **Data-based Prediction** involves identifying patterns and trends within and across groups of data/information as seen in the observable world. The patterns of data associated with precipitation in turn can be used to create rules for the computer model in a process of **Rule Abstraction**. **Rule abstraction** involves creating a general statement derived from exploring patterns in data in order to establish rule(s) or principles. In other words, if you know the patterns of variable values associated with precipitation, you can use those patterns to write rules for predicting precipitation.\\n\\nAs a **cold front** moves into an area, the heavier cool air pushes under the lighter warm air. The air behind a cold front is colder and usually drier than the warm air in front. The warm air in front becomes cooler as it is pushed upward by the entering cold air. If the warm air is humid enough, the water vapor it contains will condense into clouds as it rises, and precipitation may fall. \\n\u003Cimg src=\\\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/L4L5AssessmentTeacherGuideImage2.png\\\" width=\\\"850\\\" height=\\\"180\\\" /\u003E\\n \\n\\nWhen a **warm front** moves into an area, warm air moves above a cool air mass. As the warm air rises, it condenses, often forming clouds and precipitation. \\n\u003Cimg src=\\\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/L4L5AssessmentTeacherGuideImage1.png\\\" width=\\\"850\\\" height=\\\"180\\\" /\u003E\\n\\nThe assessment is situated in the unit context to provide an opportunity for students to make sense about patterns when reasoning about air masses, fronts, and precipitation. In this assessment, one of the responses is scientifically correct while the other responses that relate to some informal ideas about weather that students may hold. \",\"content2\":\"\",\"mediaType\":\"none\",\"mediaCaption\":\"Last, First. \\\"Title of Work.\\\" Year created. Site Title [OR] Publisher. Gallery [OR] Location. http://www.url.com.\",\"mediaURL\":\"\"}}", + "approved_script_label": "teacherEditionTips", + "component_label": "windowShade", + "approved_script": { + "name": "Teacher Edition", + "url": "https://teacher-edition-tips-plugin.concord.org/version/v3.6.0/plugin.js", + "label": "teacherEditionTips", + "description": "This plugin provides Teacher Edition components", + "version": 3, + "json_url": "https://teacher-edition-tips-plugin.concord.org/version/v3.6.0/manifest.json", + "authoring_metadata": "{\"components\":[{\"label\":\"windowShade\",\"name\":\"Window Shades\",\"scope\":\"embeddable\",\"guiAuthoring\":true},{\"label\":\"sideTip\",\"name\":\"Side Tips\",\"scope\":\"embeddable\",\"guiAuthoring\":true},{\"label\":\"questionWrapper\",\"name\":\"Question Wrapper\",\"scope\":\"embeddable-decoration\",\"decorates\":[\"Embeddable::MultipleChoice\",\"Embeddable::OpenResponse\",\"Embeddable::ImageQuestion\",\"ManagedInteractive\",\"MwInteractive\",\"ImageInteractive\",\"VideoInteractive\"],\"guiAuthoring\":true,\"guiPreview\":true}]}" + } + }, + "is_hidden": false, + "is_full_width": true, + "type": "Embeddable::EmbeddablePlugin", + "ref_id": "10257-Embeddable::EmbeddablePlugin" + }, + "section": null + }, { + "embeddable": { + "plugin": { + "description": null, + "author_data": "{\"tipType\":\"windowShade\",\"windowShade\":{\"windowShadeType\":\"discussionPoints\",\"layout\":\"mediaLeft\",\"initialOpenState\":true,\"content\":\"###What Are Common Student Ideas and What Supports Could Help Students?\\nBelow are some issues to consider in assessing students\u2019 ideas, and some suggestions of ways to support students in developing more formal reasoning about patterns associated with fronts and precipitation.\\n\\n###Less Formal Ideas\\n\u2022\\t**Kalin\u2019s response (precipitation with a cold front coming in)** suggests that Kalin may just be thinking about patterns of familiar things going together (cold and wet, warm and sunny) rather than thinking about patterns associated with different types of air masses interacting with one another. Students may associate sun with warm, and rain and snow with cold. Based on that experience, they may think that a cold front is connected to precipitation.\\n\\nStudents who choose Kalin\u2019s response could benefit from having experiences that challenge their simple association idea. For example, looking at weather maps that show warmer air often has more moisture in it and colder air is often drier can help these students develop understanding that relationships might not be as simple as they think. Students who choose Kalin\u2019s response may not think about weather as something that happens with matter. Instead, they may just think of weather in terms of the actions of natural \\\"actors\\\" (e.g., the sun makes it warm, the wind makes it cold). These students could use help in learning that air masses are matter (they are made up of molecules and have mass). If we didn\u2019t have air masses made of matter on Earth, then we wouldn\u2019t have weather. You might talk with students about concrete examples that they can extend to think about air masses as entities made of stuff \u2013 for example, they could compare an empty balloon, a balloon filled with warm air, and a balloon filled with cold air. There is very little stuff (matter or molecules of air) in the empty balloon, while there is more stuff (matter) in the balloons filled with warm and cold air.\\n\\n###Middle Level \\n\u2022\\t**Both Alex\u2019s response (precipitation occurs with a warm front coming in)** and **Sage\u2019s response (precipitation occurs after a cold front has passed by an area)** suggest that they are aware that precipitation is associated with bodies of air moving and with the different conditions in those bodies of air (i.e., temperature, levels of humidity). However, both Sage\u2019s and Alex\u2019s ideas include some incorrect patterns that lead to problematic rules. \\n\\n\u2022\\t**Alex** thinks that cold air and warm air mixing causes precipitation. However, warm and cold air masses don\u2019t mix very readily, and it is instead actually warm air rising, expanding, and condensing that generally leads to precipitation. In addition, while Alex knows that cold fronts can be drier than warm fronts, that doesn\u2019t mean that there won\u2019t be any precipitation with cold fronts. Precipitation can occur with a cold front when warm air is pushed up, expands, and condenses.\\n\\nStudents who choose Alex\u2019s response could benefit from working with data to observe the following patterns: (1) precipitation can occur with a cold front and (2) fronts do not necessarily mix.\\n\\n\u2022\\t**Sage** thinks that cold air is humid, which leads to condensation and precipitation. However, warm air masses often have a higher level of humidity compared with cold air masses. It can be confusing that condensation occurs with rising, expanding, and cooling. The unit does not go into this in depth, however. For students who choose Sage\u2019s response, it is probably sufficient here to scaffold experiences with data and virtual storm showing the general pattern of warm air masses having higher levels of humidity than cool air masses.\\n\\n\u2022\\tStudents who choose Alex or Sage\u2019s response can also benefit from discussion and emphasis on the importance of getting the rule right (enough) in order to create a computational model that works. The students working on their weather model will not be able to predict weather with any consistency or accuracy if there is a big problem with the rule (algorithm) they have written into their computer model. \\n\\n###More Formal Idea\\n\u2022\\t**Delana\u2019s response (precipitation occurs with both cold fronts and warm fronts coming in)** is the best answer. Delana\u2019s explanation does not include a more complete mechanistic sequence involving cold air pushing warm air up; warm air rising, expanding, and condensing; and precipitation occurring as a result. This is because the Precipitating Change curriculum simplifies weather phenomena by emphasizing important patterns and de-emphasizing complicated mechanisms. This focus allows the curriculum to scaffold students in connecting observed patterns with rules that can be used to create predictive weather forecasting computer models. Delana\u2019s response both recognizes that weather fronts are made of air (matter) and demonstrates recognition of the correct pattern of conditions in air masses (temperatures, levels of humidity) associated with precipitation forming. \",\"content2\":\"\",\"mediaType\":\"none\",\"mediaCaption\":\"Last, First. \\\"Title of Work.\\\" Year created. Site Title [OR] Publisher. 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They have different ideas for what the rule should be.\u003C/p\u003E\r\n\u003Cp\u003EHere are the students\u0026rsquo; ideas: The rule should be that precipitation happens\u0026hellip;\u003C/p\u003E\r\n\u003Ctable cellpadding=\"30\"\u003E\r\n\u003Ctbody\u003E\r\n\u003Ctr\u003E\r\n\u003Cth colspan=\"2\"\u003E\u003Cstrong\u003EAlex\u003C/strong\u003E\u003C/th\u003E\r\n\u003Cth colspan=\"2\"\u003E\u003Cstrong\u003EDelana\u003C/strong\u003E\u003C/th\u003E\r\n\u003C/tr\u003E\r\n\u003Ctr\u003E\r\n\u003Ctd width=\"88\"\u003E\u003Cimg src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/Alex4.png\" width=\"72\" height=\"90\" align=\"center\" hspace=\"10\" vspace=\"10\" /\u003E\u003C/td\u003E\r\n\u003Ctd style=\"padding: 10px;\" width=\"350\"\u003E\u003Cstrong\u003Ewith a warm front coming in\u003C/strong\u003E because warm air moves in and mixes with cold air, which leads to precipitation. You don\u0026rsquo;t get precipitation with a cold front because cold air is dry.\u003C/td\u003E\r\n\u003Ctd width=\"88\"\u003E\u003Cimg src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/Delana4.png\" width=\"70\" height=\"90\" align=\"center\" hspace=\"10\" vspace=\"10\" /\u003E\u003C/td\u003E\r\n\u003Ctd style=\"padding: 10px;\" width=\"350\"\u003E\u003Cstrong\u003Ewith both cold fronts and warm fronts coming in\u003C/strong\u003E because in both cases warm air and cold air meet, leading to condensation and precipitation.\u003C/td\u003E\r\n\u003C/tr\u003E\r\n\u003C/tbody\u003E\r\n\u003Ctbody\u003E\r\n\u003Ctr\u003E\r\n\u003Cth colspan=\"2\"\u003E\u003Cstrong\u003EKalin\u003C/strong\u003E\u003C/th\u003E\r\n\u003Cth colspan=\"2\"\u003E\u003Cstrong\u003ESage\u003C/strong\u003E\u003C/th\u003E\r\n\u003C/tr\u003E\r\n\u003Ctr\u003E\r\n\u003Ctd width=\"88\"\u003E\r\n\u003Cp\u003E\u003Cimg src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/Kalin6.png\" width=\"72\" height=\"90\" align=\"center\" hspace=\"10\" vspace=\"10\" /\u003E\u003C/p\u003E\r\n\u003C/td\u003E\r\n\u003Ctd style=\"padding: 10px;\" width=\"350\"\u003E\u003Cstrong\u003Ewith a cold front coming in\u003C/strong\u003E because it\u0026rsquo;s usually rainy or snowy when it\u0026rsquo;s cold out. You don\u0026rsquo;t get precipitation with a warm front because it\u0026rsquo;s warm when the sun is shining.\u003C/td\u003E\r\n\u003Ctd width=\"88\"\u003E\r\n\u003Cp\u003E\u003Cimg src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/Sage2.png\" width=\"72\" height=\"90\" align=\"center\" hspace=\"8\" vspace=\"8\" /\u003E\u003C/p\u003E\r\n\u003C/td\u003E\r\n\u003Ctd style=\"padding: 10px;\" width=\"350\"\u003E\u003Cstrong\u003Eafter a cold front has passed by\u003C/strong\u003E because the cold air the front leaves behind is humid, which leads to precipitation.\u003C/td\u003E\r\n\u003C/tr\u003E\r\n\u003C/tbody\u003E\r\n\u003C/table\u003E", + "is_callout": false, + "is_full_width": true, + "is_hidden": false, + "name": "", + "type": "Embeddable::Xhtml", + "ref_id": "147903-Embeddable::Xhtml" + }, + "section": "header_block" + }, { + "embeddable": { + "plugin": { + "description": null, + "author_data": "{\"tipType\":\"windowShade\",\"windowShade\":{\"windowShadeType\":\"teacherTip\",\"layout\":\"mediaLeft\",\"initialOpenState\":true,\"content\":\"###Pre-Assessment Implementation\\n*Lesson 4, Opening: What Are the Rules for Fronts and Precipitation? Pre-Assessment*\\nDuring the pre-assessment, each student will view the probe and make an individual choice. The request for explanation will only be on the post-assessment. After students make an individual choice for the pre-assessment, the teacher can lead discussion including, for example, a pair/share opportunity and/or full class discussion. \\n\\nAt this time, encourage students to share and discuss their ideas and reasons without indicating that any one answer is better or worse. Let the students know that they should keep thinking about this question and that the class will return to it at the end of the next lesson (Lesson 5).\",\"content2\":\"\",\"mediaType\":\"none\",\"mediaCaption\":\"Last, First. \\\"Title of Work.\\\" Year created. Site Title [OR] Publisher. Gallery [OR] Location. http://www.url.com.\",\"mediaURL\":\"\"}}", + "approved_script_label": "teacherEditionTips", + "component_label": "windowShade", + "approved_script": { + "name": "Teacher Edition", + "url": "https://teacher-edition-tips-plugin.concord.org/version/v3.6.0/plugin.js", + "label": "teacherEditionTips", + "description": "This plugin provides Teacher Edition components", + "version": 3, + "json_url": "https://teacher-edition-tips-plugin.concord.org/version/v3.6.0/manifest.json", + "authoring_metadata": "{\"components\":[{\"label\":\"windowShade\",\"name\":\"Window Shades\",\"scope\":\"embeddable\",\"guiAuthoring\":true},{\"label\":\"sideTip\",\"name\":\"Side Tips\",\"scope\":\"embeddable\",\"guiAuthoring\":true},{\"label\":\"questionWrapper\",\"name\":\"Question Wrapper\",\"scope\":\"embeddable-decoration\",\"decorates\":[\"Embeddable::MultipleChoice\",\"Embeddable::OpenResponse\",\"Embeddable::ImageQuestion\",\"ManagedInteractive\",\"MwInteractive\",\"ImageInteractive\",\"VideoInteractive\"],\"guiAuthoring\":true,\"guiPreview\":true}]}" + } + }, + "is_hidden": false, + "is_full_width": true, + "type": "Embeddable::EmbeddablePlugin", + "ref_id": "10253-Embeddable::EmbeddablePlugin" + }, + "section": null + }, { + "embeddable": { + "plugin": { + "description": null, + "author_data": "{\"tipType\":\"windowShade\",\"windowShade\":{\"windowShadeType\":\"theoryAndBackground\",\"layout\":\"mediaLeft\",\"initialOpenState\":true,\"content\":\"###Computational Thinking Concepts and Practices:\\n* Pattern Recognition\\n* Data-based Prediction\\n* Rule Abstraction\\n\\n###What is the Purpose of this Assessment Probe?\\nThe following information provides background for teachers. We suggest teachers review the information below and think about ways to scaffold students toward developing knowledge and practice as appropriate for their classes. Also, we recommend that during the first implementation of the probe, teachers scaffold students to focus on students\u2019 own ideas about this problem. By discussing the different options, students can engage in productive talk related to the different response patterns, priming them to look for productive patterns to associate with precipitation in the upcoming lessons. \\n\\nDuring the ensuing two lessons and the second implementation of the probe, students should be able to use the data from the virtual storm to identify the patterns of temperature, humidity, and movement that are associated with precipitation.\\n\\nThis assessment probe is designed to assess and scaffold students in thinking and talking about how patterns of data (i.e., temperature, humidity, and air movement) are associated with precipitation in a location. To keep things simple, we only focus on two types of fronts: cold fronts and warm fronts. Both types of fronts can be associated with precipitation. Identifying patterns associated with precipitation is an example of the computational thinking practice of **Pattern Recognition**. Once patterns associated with precipitation are identified, they can be used in conjunction with data to make a **Data-based Prediction**, which is what Ms. Tevuk\u2019s students are trying to do in the scenario for this assessment probe. **Data-based Prediction** involves identifying patterns and trends within and across groups of data/information as seen in the observable world. The patterns of data associated with precipitation in turn can be used to create rules for the computer model in a process of **Rule Abstraction**. **Rule abstraction** involves creating a general statement derived from exploring patterns in data in order to establish rule(s) or principles. In other words, if you know the patterns of variable values associated with precipitation, you can use those patterns to write rules for predicting precipitation.\\n\\nAs a **cold front** moves into an area, the heavier cool air pushes under the lighter warm air. The air behind a cold front is colder and usually drier than the warm air in front. The warm air in front becomes cooler as it is pushed upward by the entering cold air. If the warm air is humid enough, the water vapor it contains will condense into clouds as it rises, and precipitation may fall. \\n\u003Cimg src=\\\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/L4L5AssessmentTeacherGuideImage2.png\\\" width=\\\"850\\\" height=\\\"180\\\" /\u003E\\n \\n\\nWhen a **warm front** moves into an area, warm air moves above a cool air mass. As the warm air rises, it condenses, often forming clouds and precipitation. \\n\u003Cimg src=\\\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/L4L5AssessmentTeacherGuideImage1.png\\\" width=\\\"850\\\" height=\\\"180\\\" /\u003E\\n\\nThe assessment is situated in the unit context to provide an opportunity for students to make sense about patterns when reasoning about air masses, fronts, and precipitation. In this assessment, one of the responses is scientifically correct while the other responses that relate to some informal ideas about weather that students may hold. \",\"content2\":\"\",\"mediaType\":\"none\",\"mediaCaption\":\"Last, First. \\\"Title of Work.\\\" Year created. Site Title [OR] Publisher. 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Students may associate sun with warm, and rain and snow with cold. Based on that experience, they may think that a cold front is connected to precipitation.\\n\\nStudents who choose Kalin\u2019s response could benefit from having experiences that challenge their simple association idea. For example, looking at weather maps that show warmer air often has more moisture in it and colder air is often drier can help these students develop understanding that relationships might not be as simple as they think. Students who choose Kalin\u2019s response may not think about weather as something that happens with matter. Instead, they may just think of weather in terms of the actions of natural \\\"actors\\\" (e.g., the sun makes it warm, the wind makes it cold). These students could use help in learning that air masses are matter (they are made up of molecules and have mass). If we didn\u2019t have air masses made of matter on Earth, then we wouldn\u2019t have weather. 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However, both Sage\u2019s and Alex\u2019s ideas include some incorrect patterns that lead to problematic rules. \\n\\n\u2022\\t**Alex** thinks that cold air and warm air mixing causes precipitation. However, warm and cold air masses don\u2019t mix very readily, and it is instead actually warm air rising, expanding, and condensing that generally leads to precipitation. In addition, while Alex knows that cold fronts can be drier than warm fronts, that doesn\u2019t mean that there won\u2019t be any precipitation with cold fronts. Precipitation can occur with a cold front when warm air is pushed up, expands, and condenses.\\n\\nStudents who choose Alex\u2019s response could benefit from working with data to observe the following patterns: (1) precipitation can occur with a cold front and (2) fronts do not necessarily mix.\\n\\n\u2022\\t**Sage** thinks that cold air is humid, which leads to condensation and precipitation. However, warm air masses often have a higher level of humidity compared with cold air masses. It can be confusing that condensation occurs with rising, expanding, and cooling. The unit does not go into this in depth, however. For students who choose Sage\u2019s response, it is probably sufficient here to scaffold experiences with data and virtual storm showing the general pattern of warm air masses having higher levels of humidity than cool air masses.\\n\\n\u2022\\tStudents who choose Alex or Sage\u2019s response can also benefit from discussion and emphasis on the importance of getting the rule right (enough) in order to create a computational model that works. The students working on their weather model will not be able to predict weather with any consistency or accuracy if there is a big problem with the rule (algorithm) they have written into their computer model. \\n\\n###More Formal Idea\\n\u2022\\t**Delana\u2019s response (precipitation occurs with both cold fronts and warm fronts coming in)** is the best answer. Delana\u2019s explanation does not include a more complete mechanistic sequence involving cold air pushing warm air up; warm air rising, expanding, and condensing; and precipitation occurring as a result. This is because the Precipitating Change curriculum simplifies weather phenomena by emphasizing important patterns and de-emphasizing complicated mechanisms. This focus allows the curriculum to scaffold students in connecting observed patterns with rules that can be used to create predictive weather forecasting computer models. 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She will discuss how\u0026nbsp;making sense of the weather data helps in predicting\u0026nbsp;weather.\u003C/p\u003E", + "is_callout": true, + "is_full_width": true, + "is_hidden": false, + "name": "", + "type": "Embeddable::Xhtml", + "ref_id": "148014-Embeddable::Xhtml" + }, + "section": "header_block" + }, { + "embeddable": { + "name": "", + "url_fragment": null, + "authored_state": "{\"version\":1,\"questionType\":\"iframe_interactive\",\"poster\":\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/Captioned_Videos/Posters/Poster_L4_Video.png\",\"videoUrl\":\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/Captioned_Videos/JackieLesson4_88_Captioned.mp4\"}", + "is_hidden": false, + "is_full_width": true, + "show_in_featured_question_report": true, + "inherit_aspect_ratio_method": true, + "custom_aspect_ratio_method": null, + "inherit_native_width": true, + "custom_native_width": 576, + "inherit_native_height": true, + "custom_native_height": 435, + "inherit_click_to_play": true, + "custom_click_to_play": false, + "inherit_full_window": true, + "custom_full_window": false, + "inherit_click_to_play_prompt": true, + "custom_click_to_play_prompt": null, + "inherit_image_url": true, + "custom_image_url": null, + "library_interactive": { + "hash": "34e1a2a39c058da8ff4ffe5a09ad14af337c4a01", + "data": { + "aspect_ratio_method": "DEFAULT", + "authoring_guidance": "", + "base_url": "https://models-resources.concord.org/question-interactives/version/v1.1.0/video-player/", + "click_to_play": false, + "click_to_play_prompt": null, + "description": "This video player will not have the blue header bar above the interactive.\r\nIt does not save the students position in the video. \r\nIt will not show up in the teacher report.", + "enable_learner_state": false, + "full_window": false, + "has_report_url": false, + "image_url": null, + "name": "Video Player", + "native_height": 435, + "native_width": 576, + "no_snapshots": false, + "show_delete_data_button": false, + "thumbnail_url": "", + "customizable": false, + "authorable": true + } + }, + "type": "ManagedInteractive", + "ref_id": "1766-ManagedInteractive", + "linked_interactives": [] + }, + "section": "header_block" + }] + }, { + "additional_sections": {}, + "embeddable_display_mode": "stacked", + "id": 143593, + "is_completion": false, + "is_hidden": false, + "layout": "l-full-width", + "name": "Opening", + "position": 2, + "show_header": true, + "show_info_assessment": true, + "show_interactive": false, + "show_sidebar": false, + "sidebar": null, + "sidebar_title": "Did you know?", + "toggle_info_assessment": false, + "embeddables": [{ + "embeddable": { + "content": "\u003Cp\u003EAs weather scientists, your job is not only to collect and organize data, but also to make sense of the data you collected. One way to make sense of the data is to develop a rule, generalized statements of patterns you see again and again.\u003C/p\u003E\n\u003Cp\u003EExample: This rule has two parts that must happen to have a certain result. If it was a [ \u003Cstrong\u003Every nice summer\u003C/strong\u003E ] and if it is [ \u003Cstrong\u003EAugust\u003C/strong\u003E ], then there will be [ \u003Cstrong\u003Elots of berries to pick\u003C/strong\u003E ].\u0026nbsp;\u003C/p\u003E\n\u003Cp style=\"text-align: justify;\"\u003E\u003Cimg class=\"\" src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/RuleStatement.jpg\" alt=\"\" width=\"472\" height=\"221\" /\u003E\u003C/p\u003E\n\u003Cp\u003EThink about developing a similar statement that could be used to determine where it will rain.\u003C/p\u003E", + "is_callout": false, + "is_full_width": true, + "is_hidden": false, + "name": "", + "type": "Embeddable::Xhtml", + "ref_id": "147899-Embeddable::Xhtml" + }, + "section": "header_block" + }, { + "embeddable": { + "plugin": { + "description": "", + "author_data": "{\"tipType\":\"windowShade\",\"questionWrapper\":{\"correctExplanation\":\"correct\",\"distractorsExplanation\":\"distractor\",\"exemplar\":\"exemplar\",\"teacherTip\":\"teacherTip\",\"teacherTipImageOverlay\":\"\"},\"windowShade\":{\"windowShadeType\":\"theoryAndBackground\",\"layout\":\"mediaLeft\",\"initialOpenState\":false,\"content\":\"### LESSON 4: BUILDING RULES\\n**WHERE DOES IT RAIN?**\\n\\nIn this lesson, students develop a rule for where it will rain and test their rule using a Virtual Model. 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Precise (exact, careful about details) | The Virtual Model allows students to be able to test their rule statements and make changes based on the model. |\\t\",\"content2\":\"\",\"mediaType\":\"none\",\"mediaCaption\":\"Last, First. \\\"Title of Work.\\\" Year created. Site Title [OR] Publisher. 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Good Life Productions. Anchorage, AK. \",\"mediaURL\":\"https://precipitatingchange-resources.concord.org/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/JackieLesson4_88.mp4\"}}", + "approved_script_label": "teacherEditionTips", + "component_label": "windowShade", + "approved_script": { + "name": "Teacher Edition", + "url": "https://teacher-edition-tips-plugin.concord.org/version/v3.6.0/plugin.js", + "label": "teacherEditionTips", + "description": "This plugin provides Teacher Edition components", + "version": 3, + "json_url": "https://teacher-edition-tips-plugin.concord.org/version/v3.6.0/manifest.json", + "authoring_metadata": "{\"components\":[{\"label\":\"windowShade\",\"name\":\"Window Shades\",\"scope\":\"embeddable\",\"guiAuthoring\":true},{\"label\":\"sideTip\",\"name\":\"Side Tips\",\"scope\":\"embeddable\",\"guiAuthoring\":true},{\"label\":\"questionWrapper\",\"name\":\"Question Wrapper\",\"scope\":\"embeddable-decoration\",\"decorates\":[\"Embeddable::MultipleChoice\",\"Embeddable::OpenResponse\",\"Embeddable::ImageQuestion\",\"ManagedInteractive\",\"MwInteractive\",\"ImageInteractive\",\"VideoInteractive\"],\"guiAuthoring\":true,\"guiPreview\":true}]}" + } + }, + "is_hidden": false, + "is_full_width": true, + "type": "Embeddable::EmbeddablePlugin", + "ref_id": "10245-Embeddable::EmbeddablePlugin" + }, + "section": null + }] + }, { + "additional_sections": {}, + "embeddable_display_mode": "stacked", + "id": 143594, + "is_completion": false, + "is_hidden": false, + "layout": "l-full-width", + "name": "Rule Abstraction", + "position": 3, + "show_header": true, + "show_info_assessment": true, + "show_interactive": false, + "show_sidebar": false, + "sidebar": null, + "sidebar_title": "Did you know?", + "toggle_info_assessment": false, + "embeddables": [{ + "embeddable": { + "content": "\u003Cp\u003EVIRTUAL STORM: RULE ABSTRACTION CONVERSATION\u003C/p\u003E\n\u003Cp\u003EYour task is to take a deeper look at your data and start summarizing the patterns that you see with the goal of writing a one-sentence statement that brings together the most important patterns to answer the question, \u0026ldquo;Where does it rain?\u0026rdquo;.\u003C/p\u003E\n\u003Cp\u003ELet's start by looking at the data you recorded on your Storm Tracker sheet for 3pm in your Science Notebook (page 12).\u003C/p\u003E\n\u003Cp\u003EWork within your research team and circle the areas where you think it will rain based on temperature data.\u0026nbsp;\u003C/p\u003E\n\u003Cp\u003E\u003Cimg style=\"display: block; margin-left: auto; margin-right: auto;\" src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/Lesson4StormTracker7pm.png\" width=\"444\" height=\"444\" /\u003E\u003C/p\u003E\n\u003Cp\u003ENow let's look at the Weather Map of the Alaska area at 7pm (see below). Work with your research team to find patterns that could help you identify where it will rain.\u003C/p\u003E\n\u003Cp\u003E\u003Cimg class=\"\" style=\"display: block; margin-left: auto; margin-right: auto;\" src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/WeatherMAPB.jpg\" alt=\"\" width=\"750\" height=\"583\" /\u003E\u003C/p\u003E", + "is_callout": false, + "is_full_width": true, + "is_hidden": false, + "name": "", + "type": "Embeddable::Xhtml", + "ref_id": "147900-Embeddable::Xhtml" + }, + "section": "header_block" + }, { + "embeddable": { + "default_text": "", + "give_prediction_feedback": false, + "hint": "", + "is_full_width": true, + "is_hidden": false, + "is_prediction": false, + "name": "", + "prediction_feedback": "", + "prompt": "\u003Cp\u003EDiscuss with your research team where you expect it will rain at 7 pm on the Weather Map based on the patterns that you saw for 3 pm. Describe below where you think it will rain.\u003C/p\u003E", + "show_in_featured_question_report": true, + "type": "Embeddable::OpenResponse", + "ref_id": "208879-Embeddable::OpenResponse" + }, + "section": null + }, { + "embeddable": { + "default_text": "", + "give_prediction_feedback": false, + "hint": "", + "is_full_width": true, + "is_hidden": false, + "is_prediction": false, + "name": "", + "prediction_feedback": "", + "prompt": "\u003Cp\u003EWrite a general statement that answers the question, \u0026ldquo;Where does it rain?\u0026rdquo; Use the pattern charts and your weather map to create your statement.\u003C/p\u003E", + "show_in_featured_question_report": true, + "type": "Embeddable::OpenResponse", + "ref_id": "208880-Embeddable::OpenResponse" + }, + "section": null + }, { + "embeddable": { + "plugin": { + "description": "", + "author_data": "{\"tipType\":\"windowShade\",\"questionWrapper\":{\"correctExplanation\":\"correct\",\"distractorsExplanation\":\"distractor\",\"exemplar\":\"exemplar\",\"teacherTip\":\"teacherTip\",\"teacherTipImageOverlay\":\"\"},\"windowShade\":{\"windowShadeType\":\"theoryAndBackground\",\"layout\":\"mediaLeft\",\"initialOpenState\":false,\"content\":\"###Activity 1 - Rule Abstraction\\n\\nStudents create a relational statement explaining where it is raining. The specific computational thinking practices highlighted and practiced in this activity are **Rule Abstraction**, **Rule Testing**, and **Rule Refinement**. We anticipate that this conversation is going to require heavy scaffolding to get students acquainted and comfortable with writing rules. Efforts here will pay off later in Lessons 5 when students must write additional rules for other weather phenomena.\\n\\n**1. Abstracting a rule.**\\n\\n* Introduce the task of writing a one-sentence statement that brings together the most important patterns to answer the question, \u201cWhere does it rain?\u201d \\n\\n**2. Gathering more information.**\\n\\n* Have students look at their Virtual Storm Tracker in their Science Notebook on page 12 and circle where they think it will rain at \\n 7 pm, using temperature only.\\n\\n* Have students look at the Weather Map 7 pm with Precipitation \u0026 Air Moisture Content in their Science Notebook on page 17 and discuss with their research teams where you think it will rain with this new information. \\n\\n* Once they have decided on where they think it will rain, direct students to enter their answer to the question in the appropriate place on this page. \\n\\n**3. Introduce rule abstraction.** Rule Abstraction is creating a general statement derived from exploring patterns in data in order to establish rule(s), principles, or insights that may be generalized to other contexts. This is the first step in creating a rule in order to make a simulation on a computer. \\n\",\"content2\":\"\",\"mediaType\":\"none\",\"mediaCaption\":\"Last, First. \\\"Title of Work.\\\" Year created. Site Title [OR] Publisher. 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To help students develop a stronger voice and build a statement, they are asked to apply their understandings to another time step (7 pm). By applying their thinking at two different time steps, students validate their ideas and develop more formalized ideas on how they think the weather variables relate to each other. \\n\\n* Advise students to try to merge ideas from what they learned in Lessons 2 and 3. \\n\\n* Ask students to be selective in what patterns they think are strongest in explaining precipitation. \\n\\n* Explain to students that they just did something that weather scientists do called Rule Abstraction (creating a general statement derived from exploring patterns in data in order to establish rule(s), principles or insights that may be generalized to other contexts). This is the first step in creating a rule in order to make a simulation on a computer. \\n\\n\\n**Teacher Note**: While statements will vary in construction, level of detail, and even correctness, check in with teams to ensure that statements include some notion of both air moisture content AND temperature being important drivers of whether it will rain. If a team is stuck on one variable or the other, you might point out to them places on the Weather Map posters where their statement fails to hold true. For example, if students are ignoring air moisture, draw their attention to a place on the map where the temperature is warm but it\u2019s not raining.\",\"content2\":\"\",\"mediaType\":\"none\",\"mediaCaption\":\"Last, First. \\\"Title of Work.\\\" Year created. Site Title [OR] Publisher. Gallery [OR] Location. http://www.url.com.\",\"mediaURL\":\"\"}}", + "approved_script_label": "teacherEditionTips", + "component_label": "windowShade", + "approved_script": { + "name": "Teacher Edition", + "url": "https://teacher-edition-tips-plugin.concord.org/version/v3.6.0/plugin.js", + "label": "teacherEditionTips", + "description": "This plugin provides Teacher Edition components", + "version": 3, + "json_url": "https://teacher-edition-tips-plugin.concord.org/version/v3.6.0/manifest.json", + "authoring_metadata": "{\"components\":[{\"label\":\"windowShade\",\"name\":\"Window Shades\",\"scope\":\"embeddable\",\"guiAuthoring\":true},{\"label\":\"sideTip\",\"name\":\"Side Tips\",\"scope\":\"embeddable\",\"guiAuthoring\":true},{\"label\":\"questionWrapper\",\"name\":\"Question Wrapper\",\"scope\":\"embeddable-decoration\",\"decorates\":[\"Embeddable::MultipleChoice\",\"Embeddable::OpenResponse\",\"Embeddable::ImageQuestion\",\"ManagedInteractive\",\"MwInteractive\",\"ImageInteractive\",\"VideoInteractive\"],\"guiAuthoring\":true,\"guiPreview\":true}]}" + } + }, + "is_hidden": false, + "is_full_width": true, + "type": "Embeddable::EmbeddablePlugin", + "ref_id": "10247-Embeddable::EmbeddablePlugin" + }, + "section": null + }] + }, { + "additional_sections": {}, + "embeddable_display_mode": "stacked", + "id": 143595, + "is_completion": false, + "is_hidden": false, + "layout": "l-full-width", + "name": "Rule Abstraction (cont.)", + "position": 4, + "show_header": true, + "show_info_assessment": true, + "show_interactive": false, + "show_sidebar": false, + "sidebar": null, + "sidebar_title": "Did you know?", + "toggle_info_assessment": false, + "embeddables": [{ + "embeddable": { + "content": "\u003Cp\u003EAs weather scientists, you have been identifying patterns, specifically relationships between temperature and air moisture values, to determine where it will rain. Analyzing and collecting data by hand can be a lot of work and take a lot of time. Weather scientists use models that can collect and analyze the data for them.\u003C/p\u003E\n\u003Cp\u003ETo make computational models, we need to create rules that are very specific for a computer to run. In this activity, you are going to refine the rule statement you made by testing it within a Virtual Model.\u003C/p\u003E\n\u003Cp\u003EYou can practice making more specific rule statements by answering the questions below and testing them using the model.\u0026nbsp;\u003C/p\u003E", + "is_callout": false, + "is_full_width": true, + "is_hidden": false, + "name": "", + "type": "Embeddable::Xhtml", + "ref_id": "147901-Embeddable::Xhtml" + }, + "section": "header_block" + }, { + "embeddable": { + "custom": false, + "enable_check_answer": true, + "give_prediction_feedback": false, + "hint": "", + "is_full_width": true, + "is_hidden": false, + "is_prediction": false, + "layout": "vertical", + "multi_answer": false, + "name": "Multiple Choice Question element", + "prediction_feedback": "", + "prompt": "\u003Cp\u003EUsing the following rule, which pair of grid squares (A, B, or C) will produce rain?\u0026nbsp;\u003C/p\u003E\r\n\u003Cp\u003E\u003Cimg class=\"\" style=\"display: block; margin-left: auto; margin-right: auto;\" src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/Lesson4NWImage.png\" alt=\"\" width=\"70\" height=\"72\" /\u003E\u003Cbr /\u003EIF the upper square (the northwest square)\u0026nbsp;\u0026nbsp;is colder than the lower square by at least [ \u003Cstrong\u003E\u003Cspan style=\"text-decoration: underline;\"\u003E5 degrees\u003C/span\u003E\u003C/strong\u003E ] AND IF the moisture of the lower square is at least [ \u003Cstrong\u003E\u003Cspan style=\"text-decoration: underline;\"\u003E7\u003C/span\u003E\u003C/strong\u003E ] THEN it rains in the lower square.\u003C/p\u003E\r\n\u003Cp\u003E\u0026nbsp;\u003C/p\u003E\r\n\u003Cp\u003E\u003Cimg src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/Lesson4RuleRefinementABCquestionRVSD\" width=\"424\" height=\"182\" /\u003E\u003C/p\u003E\r\n\u003Cp\u003EWhich square will have rain according to this rule?\u003C/p\u003E", + "show_as_menu": false, + "show_in_featured_question_report": true, + "choices": [{ + "choice": "A", + "is_correct": false, + "prompt": "" + }, { + "choice": "B", + "is_correct": true, + "prompt": "" + }, { + "choice": "C", + "is_correct": false, + "prompt": "" + }], + "type": "Embeddable::MultipleChoice", + "ref_id": "17138-Embeddable::MultipleChoice" + }, + "section": null + }] + }, { + "additional_sections": {}, + "embeddable_display_mode": "stacked", + "id": 143596, + "is_completion": false, + "is_hidden": false, + "layout": "l-full-width", + "name": "Testing the Rules with a Model ", + "position": 5, + "show_header": false, + "show_info_assessment": true, + "show_interactive": true, + "show_sidebar": false, + "sidebar": null, + "sidebar_title": "Did you know?", + "toggle_info_assessment": false, + "embeddables": [{ + "embeddable": { + "content": "\u003Cp\u003EPress \u003Cstrong\u003ESetup\u003C/strong\u003E and then \u003Cstrong\u003ERun\u003C/strong\u003E. Explore all the features of this model. Discuss with your research team what each feature shows you.\u0026nbsp;\u003C/p\u003E\r\n\u003Cp\u003E\u003Cbr /\u003EAfter you have explored the model, refine your precipitation rule until you have found the best fit between the actual precipitation and the precipitation predicted by the rule. Test your rule with all of the data sets.\u003C/p\u003E", + "is_callout": true, + "is_full_width": true, + "is_hidden": false, + "name": "TASK", + "type": "Embeddable::Xhtml", + "ref_id": "147902-Embeddable::Xhtml" + }, + "section": null + }, { + "embeddable": { + "default_text": "", + "give_prediction_feedback": false, + "hint": "", + "is_full_width": true, + "is_hidden": false, + "is_prediction": false, + "name": "", + "prediction_feedback": "", + "prompt": "\u003Cp\u003EWhat\u0026rsquo;s the best rule to fit the actual precipitation?\u003C/p\u003E", + "show_in_featured_question_report": true, + "type": "Embeddable::OpenResponse", + "ref_id": "208881-Embeddable::OpenResponse" + }, + "section": null + }, { + "embeddable": { + "default_text": "", + "give_prediction_feedback": false, + "hint": "", + "is_full_width": true, + "is_hidden": false, + "is_prediction": false, + "name": "", + "prediction_feedback": "", + "prompt": "\u003Cp\u003EDid your rule fit the actual precipitation perfectly for all data sets?\u0026nbsp; Please explain why or why not.\u003C/p\u003E", + "show_in_featured_question_report": true, + "type": "Embeddable::OpenResponse", + "ref_id": "208882-Embeddable::OpenResponse" + }, + "section": null + }, { + "embeddable": { + "default_text": "", + "give_prediction_feedback": false, + "hint": "", + "is_full_width": true, + "is_hidden": false, + "is_prediction": false, + "name": "", + "prediction_feedback": "", + "prompt": "\u003Cp\u003EFor a weather model, list as many reasons as you can think of for why a rule might not predict the actual data perfectly.\u003C/p\u003E", + "show_in_featured_question_report": true, + "type": "Embeddable::OpenResponse", + "ref_id": "208883-Embeddable::OpenResponse" + }, + "section": null + }, { + "embeddable": { + "default_text": "", + "give_prediction_feedback": false, + "hint": "", + "is_full_width": true, + "is_hidden": false, + "is_prediction": false, + "name": "", + "prediction_feedback": "", + "prompt": "\u003Cp\u003EWhat is your final rule statement that answers the question, \"Where does it rain?\"\u003C/p\u003E", + "show_in_featured_question_report": true, + "type": "Embeddable::OpenResponse", + "ref_id": "208884-Embeddable::OpenResponse" + }, + "section": null + }, { + "embeddable": { + "plugin": { + "description": "", + "author_data": "{\"tipType\":\"windowShade\",\"questionWrapper\":{\"correctExplanation\":\"correct\",\"distractorsExplanation\":\"distractor\",\"exemplar\":\"exemplar\",\"teacherTip\":\"teacherTip\",\"teacherTipImageOverlay\":\"\"},\"windowShade\":{\"windowShadeType\":\"theoryAndBackground\",\"layout\":\"mediaLeft\",\"initialOpenState\":false,\"content\":\"###Activity 2 - Refining and Testing a Rule with a Virtual Model\\n\\n**Objective:** To deepen students\u2019 understanding of rule refinement with a virtual model that makes it easy to experiment with two varying quantities -- temperature difference and air moisture content. Students use this understanding to solve the challenge of finding the best rule that predicts where precipitation occurs.\\n \\n**1. Encourage students to explore the model.** Ask students to explore all the features of the model. When experimenting with setting rule values, they should try the extreme settings (maximums and minimums) as well as more moderate settings. After 5 to 10 minutes of independent work, let them **tell you** what they have discovered. They might find: \\n\\n* Weather data for five different times with each data set separated by four hours. \\n* Grid squares showing moisture in the upper right corner and temperature in the lower left. \\n* Actual rainfall indicated with the light blue drops. \\n* When \\\"show-results-of-the-rules?\\\" is selected, check marks show which parts of the rule are true. \\n* Check marks appear for each part of the rule when true: orange check for the temperature difference rule and green checks for the moisture rule.\\n* The \\\"Show Rain with these Rules\\\" button displays dark blue drops only where both the temperature difference rule and the moisture rule are true. \\n\\nA short discussion about the following, might be valuable before students go on to the challenge.\\n* Why are there no check marks on the top and left side of the grid? (The temperature rule can\u2019t be calculated because there is no square to the northwest in those rows.)\\n* Is there a rule that makes it rain everywhere (not counting the top and left rows)? Or nowhere?\\n* How did you explore the rules? \\n* How did you test them? \\n* What did you learn? (See if students found a technique for exploring the model. Students might benefit from hearing each other\u2019s strategies.)\\n\\n**2. Challenge: Find the best rule.** Remind students that they are pursuing this question, \\\"Where does it rain?\\\" Or more specifically, \\\"What conditions of temperature and moisture result in rain?\\\" \\n\\nHave students test their rule to find the best fit between the real data (light blue) and the data produced by the rule (dark blue) for the five different times (7 am, 11 am, 3 pm, 7 pm, and 11 pm). They will record their findings in the questions that follow the model.\\n\\nNotes: Try to let students discover that there is no perfect rule. That is, even the best rule may make rain in a square or two that had none or produce rain where there was none. Students will have to work through this. If they find it frustrating, let them know the rule doesn\u2019t need to be perfect. \",\"content2\":\"\",\"mediaType\":\"none\",\"mediaCaption\":\"Last, First. \\\"Title of Work.\\\" Year created. Site Title [OR] Publisher. Gallery [OR] Location. http://www.url.com.\",\"mediaURL\":\"\"}}", + "approved_script_label": "teacherEditionTips", + "component_label": "windowShade", + "approved_script": { + "name": "Teacher Edition", + "url": "https://teacher-edition-tips-plugin.concord.org/version/v3.6.0/plugin.js", + "label": "teacherEditionTips", + "description": "This plugin provides Teacher Edition components", + "version": 3, + "json_url": "https://teacher-edition-tips-plugin.concord.org/version/v3.6.0/manifest.json", + "authoring_metadata": "{\"components\":[{\"label\":\"windowShade\",\"name\":\"Window Shades\",\"scope\":\"embeddable\",\"guiAuthoring\":true},{\"label\":\"sideTip\",\"name\":\"Side Tips\",\"scope\":\"embeddable\",\"guiAuthoring\":true},{\"label\":\"questionWrapper\",\"name\":\"Question Wrapper\",\"scope\":\"embeddable-decoration\",\"decorates\":[\"Embeddable::MultipleChoice\",\"Embeddable::OpenResponse\",\"Embeddable::ImageQuestion\",\"ManagedInteractive\",\"MwInteractive\",\"ImageInteractive\",\"VideoInteractive\"],\"guiAuthoring\":true,\"guiPreview\":true}]}" + } + }, + "is_hidden": false, + "is_full_width": true, + "type": "Embeddable::EmbeddablePlugin", + "ref_id": "10248-Embeddable::EmbeddablePlugin" + }, + "section": null + }, { + "embeddable": { + "plugin": { + "description": null, + "author_data": "{\"tipType\":\"windowShade\",\"windowShade\":{\"windowShadeType\":\"discussionPoints\",\"layout\":\"mediaLeft\",\"initialOpenState\":true,\"content\":\"Lead a class discussion at the end of the activity. Please see possible discussion points below:\\n\\n* Did working with the model help you understand what a rule for predicting weather is? What did you find out? (e.g., Did students notice that rain only occurs when the checkmarks for both the temperature difference and moisture appear in a square?)\\n\\n* Would the rule you developed work for all weather systems? Why or why not? (See if students realize that this rule depends on the front moving from the northwest which will not always happen.)\\n\\n* Do you think there are perfect rules for weather prediction? Why or why not? (Prediction attempts to do the best it can with the data available. There may be many factors that with the data input or with the rules that we don\u2019t know.)\\n\\n* Even if prediction rules are not perfect, why are they still important? (Predicting the weather is an evolving science, so prediction is not perfect. 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"is_completion": false, + "is_hidden": false, + "layout": "l-full-width", + "name": "Page 1", + "position": 1, + "show_header": true, + "show_info_assessment": false, + "show_interactive": false, + "show_sidebar": false, + "sidebar": null, + "sidebar_title": "Did you know?", + "toggle_info_assessment": false, + "embeddables": [{ + "embeddable": { + "content": "\u003Cp\u003E\u003Cstrong\u003EHow Should We Represent Wind Direction?\u003C/strong\u003E\u003C/p\u003E\r\n\u003Cp\u003EThe word represent means to let one thing stand for another. For example, some people use the symbol of a\u003C/p\u003E\r\n\u003Cp\u003Eheart [\u003Cimg src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/Captioned_Videos/new_picts/heart2.png\" width=\"27\" height=\"23\" /\u003E] to represent (or stand for) love. \u0026nbsp;\u003C/p\u003E\r\n\u003Cp\u003EFour students in Ms. Tevuk\u0026rsquo;s class are figuring out how to represent wind direction both (1) in their computer model that does calculations to predict the weather and (2) on a map the computer model produces to show the weather prediction. The students have different ideas about how to represent wind direction for these two purposes.\u003C/p\u003E\r\n\u003Cp\u003EHere are some different options Ms. Tevuk\u0026rsquo;s students are considering for representing wind direction.\u003C/p\u003E\r\n\u003Cp\u003E\u0026bull;\u0026nbsp;\u003Cstrong\u003EWind direction represented with degree number (between 0 and 360) based on the compass\u0026nbsp;\u003C/strong\u003E\u003C/p\u003E\r\n\u003Cp\u003E\u003Cimg src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/Captioned_Videos/new_picts/Lesson_5_new_Embedded_assessment/Version2_wind_direction_with_degrees.png\" width=\"503\" height=\"230\" /\u003E\u003C/p\u003E\r\n\u003Cp\u003E\u003Cstrong\u003E\u0026bull;\u0026nbsp;Wind direction represented with letters based on the compass\u0026nbsp;\u003C/strong\u003E\u003C/p\u003E\r\n\u003Cp\u003E\u003Cstrong\u003E\u003Cimg src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/Captioned_Videos/new_picts/Lesson_5_new_Embedded_assessment/Version2_wind_direction_with_letters.png\" width=\"509\" height=\"234\" /\u003E\u003C/strong\u003E\u003C/p\u003E\r\n\u003Cp\u003E\u003Cstrong\u003E\u0026bull;\u0026nbsp;Wind direction represented with arrows\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u003C/strong\u003E\u003C/p\u003E\r\n\u003Cp\u003E\u003Cstrong\u003E\u003Cimg class=\"\" src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/Captioned_Videos/new_picts/Lesson_5_new_Embedded_assessment/Wind_direction_based_arrows.png\" alt=\"\" width=\"177\" height=\"181\" /\u003E\u003C/strong\u003E\u003C/p\u003E\r\n\u003Cp\u003E\u003Cstrong\u003E\u0026bull;\u0026nbsp;Wind direction represented with different colors\u003C/strong\u003E\u003C/p\u003E\r\n\u003Cp\u003E\u003Cstrong\u003E\u003Cimg class=\"\" src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/Captioned_Videos/new_picts/Lesson_5_new_Embedded_assessment/Wind_direction_different_colors.png\" alt=\"\" width=\"173\" height=\"177\" /\u003E\u003C/strong\u003E\u003C/p\u003E\r\n\u003Cp\u003EHere are the students\u0026rsquo; ideas:\u003C/p\u003E\r\n\u003Ctable style=\"border: solid 1px #000;\" cellpadding=\"30\"\u003E\r\n\u003Ctbody\u003E\r\n\u003Ctr\u003E\r\n\u003Cth style=\"border-right: solid 1px #000;\" colspan=\"2\"\u003E\u003Cstrong\u003EAlex\u003C/strong\u003E\u003C/th\u003E\r\n\u003Cth colspan=\"2\"\u003E\u003Cstrong\u003EDelana\u003C/strong\u003E\u003C/th\u003E\r\n\u003C/tr\u003E\r\n\u003Ctr\u003E\r\n\u003Ctd style=\"border-bottom: solid 1px #000;\" width=\"88\"\u003E\u003Cimg src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/Alex1.png\" width=\"60\" height=\"88\" align=\"center\" hspace=\"10\" vspace=\"10\" /\u003E\u003C/td\u003E\r\n\u003Ctd style=\"border-right: solid 1px #000; border-bottom: solid 1px #000; padding: 10px;\" width=\"350\"\u003E\r\n\u003Cp\u003EI think we should use the \u003Cstrong\u003Eletters for the computer model\u003C/strong\u003E because there are only 8 options, so the computer will have simple information to calculate with and it won\u0026rsquo;t get stuck computing. We can use the \u003Cstrong\u003Earrows on the map\u003C/strong\u003E because that way you can see which way the wind is going.\u003C/p\u003E\r\n\u003Cp\u003E\u003Cimg src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/Captioned_Videos/new_picts/Lesson_5_new_Embedded_assessment/Version2_letters_for_computer_model_Alex.png\" width=\"267\" height=\"183\" /\u003E\u003C/p\u003E\r\n\u003Cp\u003E\u003Cimg class=\"\" src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/Captioned_Videos/new_picts/Lesson_5_new_Embedded_assessment/Parts/Alex_Part2.png\" alt=\"\" width=\"270\" height=\"185\" /\u003E\u003C/p\u003E\r\n\u003C/td\u003E\r\n\u003Ctd style=\"border-bottom: solid 1px #000;\" width=\"88\"\u003E\u003Cimg src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/Delana1.png\" width=\"65\" height=\"92\" align=\"center\" hspace=\"10\" vspace=\"10\" /\u003E\u003C/td\u003E\r\n\u003Ctd style=\"border-bottom: solid 1px #000; padding: 10px;\" width=\"350\"\u003E\r\n\u003Cp\u003ELet\u0026rsquo;s use \u003Cstrong\u003Enumber of degrees on the computer model\u003C/strong\u003E because computers do calculations with numbers. I think we should use \u003Cstrong\u003Earrows on the map\u003C/strong\u003E because they make the pattern of wind direction easy to see.\u003C/p\u003E\r\n\u003Cp\u003E\u003Cimg src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/Captioned_Videos/new_picts/Lesson_5_new_Embedded_assessment/Version2_compass_degrees_for_computer_model_Delana.png\" width=\"269\" height=\"181\" /\u003E\u003C/p\u003E\r\n\u003Cp\u003E\u003Cimg class=\"\" src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/Captioned_Videos/new_picts/Lesson_5_new_Embedded_assessment/Parts/Delana_Part2.png\" alt=\"\" width=\"271\" height=\"180\" /\u003E\u003C/p\u003E\r\n\u003C/td\u003E\r\n\u003C/tr\u003E\r\n\u003Ctr\u003E\r\n\u003Cth style=\"border-right: solid 1px #000;\" colspan=\"2\"\u003E\u003Cstrong\u003EKalin\u003C/strong\u003E\u003C/th\u003E\r\n\u003Cth colspan=\"2\"\u003E\u003Cstrong\u003ESage\u003C/strong\u003E\u003C/th\u003E\r\n\u003C/tr\u003E\r\n\u003Ctr\u003E\r\n\u003Ctd width=\"88\"\u003E\r\n\u003Cp\u003E\u003Cimg src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/Kalin.png\" width=\"65\" height=\"88\" align=\"center\" hspace=\"10\" vspace=\"10\" /\u003E\u003C/p\u003E\r\n\u003C/td\u003E\r\n\u003Ctd style=\"border-right: solid 1px #000; padding: 10px;\" width=\"350\"\u003E\r\n\u003Cp\u003EI think we should use \u003Cstrong\u003Enumber of degrees for both the computer model and the map\u003C/strong\u003E because computers do calculations with numbers and our map should show what the computer calculated.\u003C/p\u003E\r\n\u003Cp\u003E\u003Cimg src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/Captioned_Videos/new_picts/Lesson_5_new_Embedded_assessment/Version2_compass_degrees_for_computer_model_Kalin.png\" width=\"257\" height=\"185\" /\u003E\u003C/p\u003E\r\n\u003Cp\u003E\u003Cimg src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/Captioned_Videos/new_picts/Lesson_5_new_Embedded_assessment/Version2_compass_degree_numbers_for_map_Kalin.png\" width=\"253\" height=\"181\" /\u003E\u003C/p\u003E\r\n\u003C/td\u003E\r\n\u003Ctd width=\"88\"\u003E\r\n\u003Cp\u003E\u003Cimg src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/Sage1.png\" width=\"65\" height=\"92\" align=\"center\" hspace=\"8\" vspace=\"8\" /\u003E\u003C/p\u003E\r\n\u003C/td\u003E\r\n\u003Ctd style=\"padding: 10px;\" width=\"350\"\u003E\r\n\u003Cp\u003EI think we should use \u003Cstrong\u003Ecolors for both the computer model and the map.\u003C/strong\u003E Colors are good for the map because it\u0026rsquo;s easy to see patterns in different colors. Then it helps to have your computer model and map match, so it makes sense to use colors for the computer model too.\u003C/p\u003E\r\n\u003Cp\u003E\u003Cimg class=\"\" src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/Captioned_Videos/new_picts/Lesson_5_new_Embedded_assessment/Parts/Sage_Part1.png\" alt=\"\" width=\"275\" height=\"193\" /\u003E\u003C/p\u003E\r\n\u003Cp\u003E\u003Cimg class=\"\" src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/Captioned_Videos/new_picts/Lesson_5_new_Embedded_assessment/Parts/Sage_Part2.png\" alt=\"\" width=\"275\" height=\"190\" /\u003E\u003C/p\u003E\r\n\u003C/td\u003E\r\n\u003C/tr\u003E\r\n\u003C/tbody\u003E\r\n\u003C/table\u003E", + "is_callout": false, + "is_full_width": true, + "is_hidden": false, + "name": "", + "type": "Embeddable::Xhtml", + "ref_id": "147932-Embeddable::Xhtml" + }, + "section": "header_block" + }, { + "embeddable": { + "name": "", + "url_fragment": null, + "authored_state": "{\"version\":1,\"questionType\":\"multiple_choice\",\"multipleAnswers\":false,\"layout\":\"vertical\",\"choices\":[{\"id\":\"1\",\"content\":\"Alex\",\"correct\":false},{\"id\":\"2\",\"content\":\"Delana\",\"correct\":false},{\"id\":\"3\",\"content\":\"Kalin\",\"correct\":false},{\"content\":\"Sage\",\"correct\":false,\"id\":\"48ed2c41-2f41-4d5e-b70c-89cc42e2eb72\"}],\"prompt\":\"\u003Cp\u003EWhich student\u2019s idea do you agree with the most?\u003C/p\u003E\"}", + "is_hidden": false, + "is_full_width": true, + "show_in_featured_question_report": true, + "inherit_aspect_ratio_method": true, + "custom_aspect_ratio_method": "DEFAULT", + "inherit_native_width": true, + "custom_native_width": 576, + "inherit_native_height": true, + "custom_native_height": 435, + "inherit_click_to_play": true, + "custom_click_to_play": false, + "inherit_full_window": true, + "custom_full_window": false, + "inherit_click_to_play_prompt": true, + "custom_click_to_play_prompt": null, + "inherit_image_url": true, + "custom_image_url": null, + "library_interactive": { + "hash": "98f3d10aa7f2fce6bdeb0ecda339fa56dc80b37c", + "data": { + "aspect_ratio_method": "DEFAULT", + "authoring_guidance": "", + "base_url": "https://models-resources.concord.org/question-interactives/version/v1.1.0/multiple-choice/", + "click_to_play": false, + "click_to_play_prompt": null, + "description": "", + "enable_learner_state": true, + "full_window": false, + "has_report_url": false, + "image_url": null, + "name": "Multiple Choice", + "native_height": 435, + "native_width": 576, + "no_snapshots": false, + "show_delete_data_button": false, + "thumbnail_url": "", + "customizable": true, + "authorable": true + } + }, + "type": "ManagedInteractive", + "ref_id": "1702-ManagedInteractive", + "linked_interactives": [] + }, + "section": "header_block" + }, { + "embeddable": { + "name": "", + "url_fragment": null, + "authored_state": "{\"version\":1,\"questionType\":\"open_response\",\"prompt\":\"\u003Cp\u003EWhy do you think the choice you picked is the best for representing wind direction in the computer model and on the map? Please explain your reasoning. \u003C/p\u003E\"}", + "is_hidden": false, + "is_full_width": true, + "show_in_featured_question_report": true, + "inherit_aspect_ratio_method": true, + "custom_aspect_ratio_method": "DEFAULT", + "inherit_native_width": true, + "custom_native_width": 576, + "inherit_native_height": true, + "custom_native_height": 435, + "inherit_click_to_play": true, + "custom_click_to_play": false, + "inherit_full_window": true, + "custom_full_window": false, + "inherit_click_to_play_prompt": true, + "custom_click_to_play_prompt": null, + "inherit_image_url": true, + "custom_image_url": null, + "library_interactive": { + "hash": "512e0a0a74a0e1cd6247a8ec98fa94dabb8a6132", + "data": { + "aspect_ratio_method": "DEFAULT", + "authoring_guidance": "", + "base_url": "https://models-resources.concord.org/question-interactives/version/v1.1.0/open-response/", + "click_to_play": false, + "click_to_play_prompt": null, + "description": "", + "enable_learner_state": true, + "full_window": false, + "has_report_url": false, + "image_url": null, + "name": "Open Response", + "native_height": 435, + "native_width": 576, + "no_snapshots": false, + "show_delete_data_button": false, + "thumbnail_url": "", + "customizable": true, + "authorable": true + } + }, + "type": "ManagedInteractive", + "ref_id": "1703-ManagedInteractive", + "linked_interactives": [] + }, + "section": "header_block" + }, { + "embeddable": { + "custom": false, + "enable_check_answer": false, + "give_prediction_feedback": false, + "hint": "", + "is_full_width": true, + "is_hidden": false, + "is_prediction": false, + "layout": "vertical", + "multi_answer": false, + "name": "Multiple Choice Question element", + "prediction_feedback": "", + "prompt": "\u003Cp\u003EWhich student\u0026rsquo;s idea do you agree with the most?\u003C/p\u003E", + "show_as_menu": false, + "show_in_featured_question_report": true, + "choices": [{ + "choice": "Alex", + "is_correct": false, + "prompt": "" + }, { + "choice": "Delana", + "is_correct": false, + "prompt": "" + }, { + "choice": "Kalin", + "is_correct": false, + "prompt": "" + }, { + "choice": "Sage", + "is_correct": false, + "prompt": "" + }], + "type": "Embeddable::MultipleChoice", + "ref_id": "17148-Embeddable::MultipleChoice" + }, + "section": null + }, { + "embeddable": { + "plugin": { + "description": null, + "author_data": "{\"tipType\":\"windowShade\",\"windowShade\":{\"windowShadeType\":\"teacherTip\",\"layout\":\"mediaLeft\",\"initialOpenState\":true,\"content\":\"###Pre-Assessment Implementation\\n*Lesson 2, Opening: How Should We Estimate the Temperature? Pre-Assessment*\\nDuring the pre-assessment, each student will view the probe and make an individual choice. The request for explanation will only be on the post-assessment. After students make an individual commitment for the pre-assessment, you can lead a discussion including, for example, a pair/share opportunity and/or full class discussion. \\n\\nAt this time, encourage students to share and discuss their ideas and reasons without indicating that any one answer is better or worse. Let the students know that they should keep thinking about this question and that the class will return to it at the end of the lesson.\\n\",\"content2\":\"\",\"mediaType\":\"none\",\"mediaCaption\":\"Last, First. \\\"Title of Work.\\\" Year created. Site Title [OR] Publisher. Gallery [OR] Location. http://www.url.com.\",\"mediaURL\":\"\"}}", + "approved_script_label": "teacherEditionTips", + "component_label": "windowShade", + "approved_script": { + "name": "Teacher Edition", + "url": "https://teacher-edition-tips-plugin.concord.org/version/v3.6.0/plugin.js", + "label": "teacherEditionTips", + "description": "This plugin provides Teacher Edition components", + "version": 3, + "json_url": "https://teacher-edition-tips-plugin.concord.org/version/v3.6.0/manifest.json", + "authoring_metadata": "{\"components\":[{\"label\":\"windowShade\",\"name\":\"Window Shades\",\"scope\":\"embeddable\",\"guiAuthoring\":true},{\"label\":\"sideTip\",\"name\":\"Side Tips\",\"scope\":\"embeddable\",\"guiAuthoring\":true},{\"label\":\"questionWrapper\",\"name\":\"Question Wrapper\",\"scope\":\"embeddable-decoration\",\"decorates\":[\"Embeddable::MultipleChoice\",\"Embeddable::OpenResponse\",\"Embeddable::ImageQuestion\",\"ManagedInteractive\",\"MwInteractive\",\"ImageInteractive\",\"VideoInteractive\"],\"guiAuthoring\":true,\"guiPreview\":true}]}" + } + }, + "is_hidden": false, + "is_full_width": true, + "type": "Embeddable::EmbeddablePlugin", + "ref_id": "10301-Embeddable::EmbeddablePlugin" + }, + "section": null + }, { + "embeddable": { + "plugin": { + "description": null, + "author_data": "{\"tipType\":\"windowShade\",\"windowShade\":{\"windowShadeType\":\"theoryAndBackground\",\"layout\":\"mediaLeft\",\"initialOpenState\":true,\"content\":\"###Computational Thinking Concept and Practice:\\n* Interpolation\\n\\n###What is the Purpose of this Assessment Probe?\\nThe following information provides background for **teachers** and is not necessarily representative of the learning goals for everything students should understand. Review the information and consider ways to scaffold students toward developing knowledge and practice as appropriate for their classes. We also recommend during the first implementation of the probe, you scaffold students to focus on student ideas about this problem, rather than on vocabulary terms such as **interpolation**. By discussing the different options, students can engage in productive talk related to data sense making and computational thinking without using technical terminology. During the ensuing lesson and the second implementation of the probe, the term interpolation can be used, as appropriate.\\n\\nThis assessment probe is designed to assess and scaffold students in thinking and talking about **interpolation**. **Interpolation** means estimating a value between ones that are known or tabulated using surrounding points or values (that is, estimating an unknown value based on surrounding information). \\n\\nThe assessment is situated within the unit context to provide an opportunity for students to make sense about interpolation of a specific, tangible weather question (i.e., temperatures along a map transect). There is always uncertainty involved when interpolating across data. Also, depending on circumstances, different methods may be appropriate. For example, if the students were trying to figure out how to dress for the day at location X, then simply choosing a number somewhere between the two might be sufficient. 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Gallery [OR] Location. http://www.url.com.\",\"mediaURL\":\"\"}}", + "approved_script_label": "teacherEditionTips", + "component_label": "windowShade", + "approved_script": { + "name": "Teacher Edition", + "url": "https://teacher-edition-tips-plugin.concord.org/version/v3.6.0/plugin.js", + "label": "teacherEditionTips", + "description": "This plugin provides Teacher Edition components", + "version": 3, + "json_url": "https://teacher-edition-tips-plugin.concord.org/version/v3.6.0/manifest.json", + "authoring_metadata": "{\"components\":[{\"label\":\"windowShade\",\"name\":\"Window Shades\",\"scope\":\"embeddable\",\"guiAuthoring\":true},{\"label\":\"sideTip\",\"name\":\"Side Tips\",\"scope\":\"embeddable\",\"guiAuthoring\":true},{\"label\":\"questionWrapper\",\"name\":\"Question Wrapper\",\"scope\":\"embeddable-decoration\",\"decorates\":[\"Embeddable::MultipleChoice\",\"Embeddable::OpenResponse\",\"Embeddable::ImageQuestion\",\"ManagedInteractive\",\"MwInteractive\",\"ImageInteractive\",\"VideoInteractive\"],\"guiAuthoring\":true,\"guiPreview\":true}]}" + } + }, + "is_hidden": false, + "is_full_width": true, + "type": "Embeddable::EmbeddablePlugin", + "ref_id": "10302-Embeddable::EmbeddablePlugin" + }, + "section": null + }, { + "embeddable": { + "plugin": { + "description": null, + "author_data": "{\"tipType\":\"windowShade\",\"windowShade\":{\"windowShadeType\":\"discussionPoints\",\"layout\":\"mediaLeft\",\"initialOpenState\":true,\"content\":\"###What Are Common Student Ideas and What Supports Could Help Students?\\nBelow are some issues to consider in assessing students\u2019 ideas, and some suggestions of ways to support students in developing more formal reasoning.\\n\\n###Less Formal Ideas\\n\u2022\\t**Kalin\u2019s response (It doesn\u2019t make sense to estimate; you need to go there and measure.)** suggests a very concrete thinking approach consistent with the idea that \u201cyou\u2019ve got to see it to believe it.\u201d \\n\\nStudents who choose Kalin\u2019s response could benefit from discussions about how while estimates and interpolations may not be perfect, they can still give us a sense of what\u2019s going on in a system when we have limited data. It might be helpful to discuss that we can never collect all the data in the world; there\u2019s too much! Because of this, we need a way to fill in missing values using the data that we do have available. \\n\\n###Middle Level \\n\u2022\\t**Both Alex\u2019s response (choose the value half way between)** and **Sage\u2019s response (choose a number closer to 59)** might be reasonable estimates in certain circumstances (e.g., for picking out what clothes to wear if you were at location X at that time). These approaches are both better than just choosing a random value as an estimate for X. However, for contexts in which more precision is called for (e.g., making a weather model), then there are ways that we can be more precise in our approaches to interpolation. \\n\\nStudents who choose Alex\u2019s and/or Sage\u2019s response could benefit from discussions of when and why we sometimes might need to be more precise in our estimation approaches. \\n\\n\\n###More Formal Idea\\n\u2022\\t**Delana\u2019s response (mark a number line with the estimate in each square going up the same amount between the two measured values)** suggests that she understands which mathematical interpolation approach will give the most precise value. Again, this level of precision will take more time and effort, and may not even be necessary in some circumstances, as discussed above. 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For example, some people use the symbol of a\u003C/p\u003E\r\n\u003Cp\u003Eheart [\u003Cimg src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/Captioned_Videos/new_picts/heart2.png\" width=\"27\" height=\"23\" /\u003E] to represent (or stand for) love. \u0026nbsp;\u003C/p\u003E\r\n\u003Cp\u003EFour students in Ms. Tevuk\u0026rsquo;s class are figuring out how to represent wind direction both (1) in their computer model that does calculations to predict the weather and (2) on a map the computer model produces to show the weather prediction. The students have different ideas about how to represent wind direction for these two purposes.\u003C/p\u003E\r\n\u003Cp\u003EHere are some different options Ms. Tevuk\u0026rsquo;s students are considering for representing wind direction.\u003C/p\u003E\r\n\u003Cp\u003E\u0026bull;\u0026nbsp;\u003Cstrong\u003EWind direction represented with degree number (between 0 and 360) based on the compass\u0026nbsp;\u003C/strong\u003E\u003C/p\u003E\r\n\u003Cp\u003E\u003Cimg src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/Captioned_Videos/new_picts/Lesson_5_new_Embedded_assessment/Version2_wind_direction_with_degrees.png\" width=\"503\" height=\"230\" /\u003E\u003C/p\u003E\r\n\u003Cp\u003E\u003Cstrong\u003E\u0026bull;\u0026nbsp;Wind direction represented with letters based on the compass\u0026nbsp;\u003C/strong\u003E\u003C/p\u003E\r\n\u003Cp\u003E\u003Cstrong\u003E\u003Cimg src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/Captioned_Videos/new_picts/Lesson_5_new_Embedded_assessment/Version2_wind_direction_with_letters.png\" width=\"509\" height=\"234\" /\u003E\u003C/strong\u003E\u003C/p\u003E\r\n\u003Cp\u003E\u003Cstrong\u003E\u0026bull;\u0026nbsp;Wind direction represented with arrows\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u003C/strong\u003E\u003C/p\u003E\r\n\u003Cp\u003E\u003Cstrong\u003E\u003Cimg class=\"\" src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/Captioned_Videos/new_picts/Lesson_5_new_Embedded_assessment/Wind_direction_based_arrows.png\" alt=\"\" width=\"177\" height=\"181\" /\u003E\u003C/strong\u003E\u003C/p\u003E\r\n\u003Cp\u003E\u003Cstrong\u003E\u0026bull;\u0026nbsp;Wind direction represented with different colors\u003C/strong\u003E\u003C/p\u003E\r\n\u003Cp\u003E\u003Cstrong\u003E\u003Cimg class=\"\" src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/Captioned_Videos/new_picts/Lesson_5_new_Embedded_assessment/Wind_direction_different_colors.png\" alt=\"\" width=\"173\" height=\"177\" /\u003E\u003C/strong\u003E\u003C/p\u003E\r\n\u003Cp\u003EHere are the students\u0026rsquo; ideas:\u003C/p\u003E\r\n\u003Ctable style=\"border: solid 1px #000;\" cellpadding=\"30\"\u003E\r\n\u003Ctbody\u003E\r\n\u003Ctr\u003E\r\n\u003Cth style=\"border-right: solid 1px #000;\" colspan=\"2\"\u003E\u003Cstrong\u003EAlex\u003C/strong\u003E\u003C/th\u003E\r\n\u003Cth colspan=\"2\"\u003E\u003Cstrong\u003EDelana\u003C/strong\u003E\u003C/th\u003E\r\n\u003C/tr\u003E\r\n\u003Ctr\u003E\r\n\u003Ctd style=\"border-bottom: solid 1px #000;\" width=\"88\"\u003E\u003Cimg src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/Alex1.png\" width=\"60\" height=\"88\" align=\"center\" hspace=\"10\" vspace=\"10\" /\u003E\u003C/td\u003E\r\n\u003Ctd style=\"border-right: solid 1px #000; border-bottom: solid 1px #000; padding: 10px;\" width=\"350\"\u003E\r\n\u003Cp\u003EI think we should use the \u003Cstrong\u003Eletters for the computer model\u003C/strong\u003E because there are only 8 options, so the computer will have simple information to calculate with and it won\u0026rsquo;t get stuck computing. We can use the \u003Cstrong\u003Earrows on the map\u003C/strong\u003E because that way you can see which way the wind is going.\u003C/p\u003E\r\n\u003Cp\u003E\u003Cimg src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/Captioned_Videos/new_picts/Lesson_5_new_Embedded_assessment/Version2_letters_for_computer_model_Alex.png\" width=\"267\" height=\"183\" /\u003E\u003C/p\u003E\r\n\u003Cp\u003E\u003Cimg class=\"\" src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/Captioned_Videos/new_picts/Lesson_5_new_Embedded_assessment/Parts/Alex_Part2.png\" alt=\"\" width=\"270\" height=\"185\" /\u003E\u003C/p\u003E\r\n\u003C/td\u003E\r\n\u003Ctd style=\"border-bottom: solid 1px #000;\" width=\"88\"\u003E\u003Cimg src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/Delana1.png\" width=\"65\" height=\"92\" align=\"center\" hspace=\"10\" vspace=\"10\" /\u003E\u003C/td\u003E\r\n\u003Ctd style=\"border-bottom: solid 1px #000; padding: 10px;\" width=\"350\"\u003E\r\n\u003Cp\u003ELet\u0026rsquo;s use \u003Cstrong\u003Enumber of degrees on the computer model\u003C/strong\u003E because computers do calculations with numbers. I think we should use \u003Cstrong\u003Earrows on the map\u003C/strong\u003E because they make the pattern of wind direction easy to see.\u003C/p\u003E\r\n\u003Cp\u003E\u003Cimg src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/Captioned_Videos/new_picts/Lesson_5_new_Embedded_assessment/Version2_compass_degrees_for_computer_model_Delana.png\" width=\"269\" height=\"181\" /\u003E\u003C/p\u003E\r\n\u003Cp\u003E\u003Cimg class=\"\" src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/Captioned_Videos/new_picts/Lesson_5_new_Embedded_assessment/Parts/Delana_Part2.png\" alt=\"\" width=\"271\" height=\"180\" /\u003E\u003C/p\u003E\r\n\u003C/td\u003E\r\n\u003C/tr\u003E\r\n\u003Ctr\u003E\r\n\u003Cth style=\"border-right: solid 1px #000;\" colspan=\"2\"\u003E\u003Cstrong\u003EKalin\u003C/strong\u003E\u003C/th\u003E\r\n\u003Cth colspan=\"2\"\u003E\u003Cstrong\u003ESage\u003C/strong\u003E\u003C/th\u003E\r\n\u003C/tr\u003E\r\n\u003Ctr\u003E\r\n\u003Ctd style=\"border-bottom: solid 1px #000;\" width=\"88\"\u003E\r\n\u003Cp\u003E\u003Cimg src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/Kalin.png\" width=\"65\" height=\"88\" align=\"center\" hspace=\"10\" vspace=\"10\" /\u003E\u003C/p\u003E\r\n\u003C/td\u003E\r\n\u003Ctd style=\"border-right: solid 1px #000; border-bottom: solid 1px #000; padding: 10px;\" width=\"350\"\u003E\r\n\u003Cp\u003EI think we should use \u003Cstrong\u003Enumber of degrees for both the computer model and the map\u003C/strong\u003E because computers do calculations with numbers and our map should show what the computer calculated.\u003C/p\u003E\r\n\u003Cp\u003E\u003Cimg src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/Captioned_Videos/new_picts/Lesson_5_new_Embedded_assessment/Version2_compass_degrees_for_computer_model_Kalin.png\" width=\"257\" height=\"185\" /\u003E\u003C/p\u003E\r\n\u003Cp\u003E\u003Cimg src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/Captioned_Videos/new_picts/Lesson_5_new_Embedded_assessment/Version2_compass_degree_numbers_for_map_Kalin.png\" width=\"253\" height=\"181\" /\u003E\u003C/p\u003E\r\n\u003C/td\u003E\r\n\u003Ctd style=\"border-bottom: solid 1px #000;\" width=\"88\"\u003E\r\n\u003Cp\u003E\u003Cimg src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/Sage1.png\" width=\"65\" height=\"92\" align=\"center\" hspace=\"8\" vspace=\"8\" /\u003E\u003C/p\u003E\r\n\u003C/td\u003E\r\n\u003Ctd style=\"border-bottom: solid 1px #000; padding: 10px;\" width=\"350\"\u003E\r\n\u003Cp\u003EI think we should use \u003Cstrong\u003Ecolors for both the computer model and the map.\u003C/strong\u003E Colors are good for the map because it\u0026rsquo;s easy to see patterns in different colors. 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Review the information and consider ways to scaffold students toward developing knowledge and practice as appropriate for their classes. We also recommend during the first implementation of the probe, you scaffold students to focus on student ideas about this problem, rather than on vocabulary terms such as **interpolation**. By discussing the different options, students can engage in productive talk related to data sense making and computational thinking without using technical terminology. During the ensuing lesson and the second implementation of the probe, the term interpolation can be used, as appropriate.\\n\\nThis assessment probe is designed to assess and scaffold students in thinking and talking about **interpolation**. **Interpolation** means estimating a value between ones that are known or tabulated using surrounding points or values (that is, estimating an unknown value based on surrounding information). \\n\\nThe assessment is situated within the unit context to provide an opportunity for students to make sense about interpolation of a specific, tangible weather question (i.e., temperatures along a map transect). There is always uncertainty involved when interpolating across data. Also, depending on circumstances, different methods may be appropriate. For example, if the students were trying to figure out how to dress for the day at location X, then simply choosing a number somewhere between the two might be sufficient. 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It might be helpful to discuss that we can never collect all the data in the world; there\u2019s too much! Because of this, we need a way to fill in missing values using the data that we do have available. \\n\\n###Middle Level \\n\u2022\\t**Both Alex\u2019s response (choose the value half way between)** and **Sage\u2019s response (choose a number closer to 59)** might be reasonable estimates in certain circumstances (e.g., for picking out what clothes to wear if you were at location X at that time). These approaches are both better than just choosing a random value as an estimate for X. 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She will discuss how wind direction\u0026nbsp;impacts different air masses.\u003C/p\u003E", + "is_callout": true, + "is_full_width": true, + "is_hidden": false, + "name": "", + "type": "Embeddable::Xhtml", + "ref_id": "148015-Embeddable::Xhtml" + }, + "section": "header_block" + }, { + "embeddable": { + "name": "", + "url_fragment": null, + "authored_state": "{\"version\":1,\"questionType\":\"iframe_interactive\",\"videoUrl\":\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/Captioned_Videos/JackieLesson5_88_Captioned.mp4\",\"poster\":\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/Captioned_Videos/Posters/Poster_L5_Video.png\"}", + "is_hidden": false, + "is_full_width": true, + "show_in_featured_question_report": true, + "inherit_aspect_ratio_method": true, + "custom_aspect_ratio_method": null, + "inherit_native_width": true, + "custom_native_width": 576, + "inherit_native_height": true, + "custom_native_height": 435, + "inherit_click_to_play": true, + "custom_click_to_play": false, + "inherit_full_window": true, + "custom_full_window": false, + "inherit_click_to_play_prompt": true, + "custom_click_to_play_prompt": null, + "inherit_image_url": true, + "custom_image_url": null, + "library_interactive": { + "hash": "34e1a2a39c058da8ff4ffe5a09ad14af337c4a01", + "data": { + "aspect_ratio_method": "DEFAULT", + "authoring_guidance": "", + "base_url": "https://models-resources.concord.org/question-interactives/version/v1.1.0/video-player/", + "click_to_play": false, + "click_to_play_prompt": null, + "description": "This video player will not have the blue header bar above the interactive.\r\nIt does not save the students position in the video. \r\nIt will not show up in the teacher report.", + "enable_learner_state": false, + "full_window": false, + "has_report_url": false, + "image_url": null, + "name": "Video Player", + "native_height": 435, + "native_width": 576, + "no_snapshots": false, + "show_delete_data_button": false, + "thumbnail_url": "", + "customizable": false, + "authorable": true + } + }, + "type": "ManagedInteractive", + "ref_id": "1767-ManagedInteractive", + "linked_interactives": [] + }, + "section": "header_block" + }] + }, { + "additional_sections": {}, + "embeddable_display_mode": "stacked", + "id": 143599, + "is_completion": false, + "is_hidden": false, + "layout": "l-full-width", + "name": "Opening", + "position": 2, + "show_header": true, + "show_info_assessment": true, + "show_interactive": false, + "show_sidebar": false, + "sidebar": null, + "sidebar_title": "Did you know?", + "toggle_info_assessment": false, + "embeddables": [{ + "embeddable": { + "content": "\u003Cp\u003EHave you ever noticed that the wind can come from one direction and then a few hours later a different direction? As weather scientists, you will explore a new component of the\u0026nbsp;weather\u0026nbsp;- wind! The direction of the wind can give you clues about what\u0026nbsp;weather\u0026nbsp;to expect. And when the wind changes its direction drastically, interesting\u0026nbsp;weather\u0026nbsp;events can happen.\u003C/p\u003E\n\u003Cp\u003E\u003Cbr /\u003EIn this lesson you will explore how air masses interact by\u0026nbsp;setting up a wind table. You will also revisit weather station data and radar maps you used in Lesson 1 with some additions: wind data and five more\u0026nbsp;weather\u0026nbsp;stations. In your Science Notebook, go to Lesson 5 to locate the following information:\u0026nbsp;\u003Cbr /\u003E\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; 0 Map with Additional Weather Stations and Data Tables\u0026nbsp;\u003Cbr /\u003E\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; 0 Alaskan Stations 7 pm Readings \u003Cbr /\u003E\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; 0 Alaskan Stations 7 pm Interpolated Map\u003Cbr /\u003E\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;0 Alaskan Stations 7 am Interpolated Map\u003Cbr /\u003E\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u003C/p\u003E", + "is_callout": false, + "is_full_width": true, + "is_hidden": false, + "name": "", + "type": "Embeddable::Xhtml", + "ref_id": "147905-Embeddable::Xhtml" + }, + "section": "header_block" + }, { + "embeddable": { + "plugin": { + "description": "", + "author_data": "{\"tipType\":\"windowShade\",\"questionWrapper\":{\"correctExplanation\":\"correct\",\"distractorsExplanation\":\"distractor\",\"exemplar\":\"exemplar\",\"teacherTip\":\"teacherTip\",\"teacherTipImageOverlay\":\"\"},\"windowShade\":{\"windowShadeType\":\"theoryAndBackground\",\"layout\":\"mediaLeft\",\"initialOpenState\":false,\"content\":\"###LESSON 5: IDENTIFYING AIR MASSES\\n\\n**WHERE DOES THE AIR COME FROM?**\\n\\nIn this lesson, students investigate the role that wind plays in determining the weather and are introduced to ways to identify and define an air mass. Air masses have a similar range of weather variables (temperature and moisture), have indistinct boundaries, and are categorized by the range of weather variables within them. The air within an air mass is constantly moving and precipitation can occur where air from different air masses mixes/interacts. Scientists use models to predict where precipitation will occur based on where different air masses interact, the type of air in each, and the movement of that air.\\n\\nTo begin to identify air masses, students will do a hands-on wind table activity, and get new temperature, air moisture content, and wind direction data for five additional weather stations. As in Lesson 4, the students once again construct a set of rules through a series of activities that allow them to uncover patterns in the data, investigate the mechanisms for these patterns, and abstract a rule that describes the relationship between wind direction, its associated air mass, and the resulting precipitation. \\n\\n###LEARNING GOALS\\nStudents will be able to:\\n\\n* Identify and define an air mass\\n\\n* Explain that air masses are defined by where they come from\\n\\n* Explain the role of wind in weather events\\n\\n* Identify where on a map two different masses are interacting/mixing\\n\\n* Develop a rule for how wind moves and test the rule with multiple kinds of air masses\\n\\n* Develop a rule to express the relationship between weather components (temperature and moisture) and air masses\\n\\nComputational Thinking (CT) skills introduced in this lessons can be found in the table below:\\n\\n| CT Skill | Definition |\\n|---------------------|---------------------------------------------------------------------------------------------------|------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|\\n| Pattern Recognition | Recognizing that data or information is repeating in a logical (expected) way |\\n| Rule Abstraction | Developing a statement of how things work based on the patterns you observed |\\n| Rule Testing | Investigating whether a rule will still be true in different situations |\\n| Rule Refinement | Modifying a rule to be more precise (exact, careful about details) to work in the model |\",\"content2\":\"\",\"mediaType\":\"none\",\"mediaCaption\":\"Last, First. \\\"Title of Work.\\\" Year created. 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(25 mins)\\n\\n* Post-Assessment - What Are the Rules for Fronts and Precipitation? (10 mins)\\n\\n###MATERIALS AND SET-UP\\n\\nActivity 1 - What is an Air Mass?\\n\\nPer Research Team:\\n\\n* Direct students to Lesson 5 in their Science Notebooks to find the following information:\\n * Lesson 5, Activity 1: Wind Table Instructions and Questions\\n * Lesson 5, Activity 2: Additional Weather Station Data\\n * Lesson 5, Activity 2: Weather Stations 7 pm Readings\\n * Lesson 5, Activity 2: Weather Stations 7 pm Interpolated\\n * Lesson 5, Activity 2: 7 pm Weather Station Data and 7 pm Radar Map\\n * Lesson 5, Activity 2: 7 am Weather Station Data \\n\\nPer Class:\\n\\n* Set up on one demonstration table that students can gather around: a wind fan, a piece of paper with a wind rose taped to the table, and a single weather vane. See below for a top-down view. \\n\\n\u003Cimg src=\\\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/Lesson5WIndTablesTopDownView1.jpg\\\" width=\\\"400\\\" height=\\\"350\\\"\u003E\\n\\n* To print the wind rose, click [here](https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/WindCompass.jpg) to download. \",\"content2\":\"\",\"mediaType\":\"none\",\"mediaCaption\":\"Last, First. \\\"Title of Work.\\\" Year created. Site Title [OR] Publisher. 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Good Life Productions. Anchorage, AK.\",\"mediaURL\":\"https://precipitatingchange-resources.concord.org/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/JackieLesson5_88.mp4\"}}", + "approved_script_label": "teacherEditionTips", + "component_label": "windowShade", + "approved_script": { + "name": "Teacher Edition", + "url": "https://teacher-edition-tips-plugin.concord.org/version/v3.6.0/plugin.js", + "label": "teacherEditionTips", + "description": "This plugin provides Teacher Edition components", + "version": 3, + "json_url": "https://teacher-edition-tips-plugin.concord.org/version/v3.6.0/manifest.json", + "authoring_metadata": "{\"components\":[{\"label\":\"windowShade\",\"name\":\"Window Shades\",\"scope\":\"embeddable\",\"guiAuthoring\":true},{\"label\":\"sideTip\",\"name\":\"Side Tips\",\"scope\":\"embeddable\",\"guiAuthoring\":true},{\"label\":\"questionWrapper\",\"name\":\"Question Wrapper\",\"scope\":\"embeddable-decoration\",\"decorates\":[\"Embeddable::MultipleChoice\",\"Embeddable::OpenResponse\",\"Embeddable::ImageQuestion\",\"ManagedInteractive\",\"MwInteractive\",\"ImageInteractive\",\"VideoInteractive\"],\"guiAuthoring\":true,\"guiPreview\":true}]}" + } + }, + "is_hidden": false, + "is_full_width": true, + "type": "Embeddable::EmbeddablePlugin", + "ref_id": "10261-Embeddable::EmbeddablePlugin" + }, + "section": null + }] + }, { + "additional_sections": {}, + "embeddable_display_mode": "stacked", + "id": 143600, + "is_completion": false, + "is_hidden": false, + "layout": "l-full-width", + "name": "What is an air mass?", + "position": 3, + "show_header": true, + "show_info_assessment": true, + "show_interactive": false, + "show_sidebar": false, + "sidebar": null, + "sidebar_title": "Did you know?", + "toggle_info_assessment": false, + "embeddables": [{ + "embeddable": { + "content": "\u003Cp\u003E\u003Cstrong\u003EMeasuring Wind with the Compass\u0026nbsp;\u003C/strong\u003E\u003C/p\u003E\n\u003Cp\u003EOne way wind direction\u0026nbsp;can be measured is with\u0026nbsp;a weather\u0026nbsp;vane or air socks. When the wind blows, the\u0026nbsp;weather\u0026nbsp;vane rotates and lines up with the path the air is flowing. So,\u0026nbsp;wind direction\u0026nbsp;is determined by what direction the wind is blowing and measured in degrees (\u0026deg;).\u003C/p\u003E\n\u003Cp\u003E\u003Cimg class=\"\" style=\"display: block; margin-left: auto; margin-right: auto;\" src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/WindCompass.jpg\" alt=\"\" width=\"323\" height=\"328\" /\u003E\u003C/p\u003E\n\u003Cp\u003EIn this activity, you will use a Wind Table to map the movement of air on a grid representing a region in Alaska. Go to your Science Notebooks, Lesson 5, page 21, for further instructions and to record your observations.\u003C/p\u003E\n\u003Cp\u003E\u003Cstrong\u003EWind Table\u003C/strong\u003E\u003C/p\u003E\n\u003Cp\u003E\u003Cimg style=\"display: block; margin-left: auto; margin-right: auto;\" src=\"https://precipitatingchange-resources.concord.org/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/WindTunnels.png\" width=\"576\" height=\"510\" /\u003E\u003C/p\u003E\n\u003Cp\u003E\u0026nbsp;\u003C/p\u003E", + "is_callout": false, + "is_full_width": true, + "is_hidden": false, + "name": "", + "type": "Embeddable::Xhtml", + "ref_id": "147906-Embeddable::Xhtml" + }, + "section": "header_block" + }, { + "embeddable": { + "plugin": { + "description": "", + "author_data": "{\"tipType\":\"windowShade\",\"questionWrapper\":{\"correctExplanation\":\"correct\",\"distractorsExplanation\":\"distractor\",\"exemplar\":\"exemplar\",\"teacherTip\":\"teacherTip\",\"teacherTipImageOverlay\":\"\"},\"windowShade\":{\"windowShadeType\":\"theoryAndBackground\",\"layout\":\"mediaLeft\",\"initialOpenState\":false,\"content\":\"\\n###Activity 1 - **What is an Air Mass?**\\nIn this activity students explore the patterns of air movement within and between air masses. Using a hands-on \u201cwind table,\u201d they engage in a tangible interaction with wind. By leveraging patterns from the previous activity dataset and the wind table, they will discover that when two air masses meet, the air converges. Weather scientists refer to these regions as fronts. \\n\\n###Wind Table Directions\\n * **1.Introduce the Wind Table.** Wind is one of the first things that atmospheric scientists look at when investigating the weather, but it can be difficult to understand by just looking at data and maps. A hands-on model is helpful to investigate a phenomenon like the wind.\\n\\n\\n * **2.Assign teams:** Assign research teams a Wind Table position number, either #1 or #2. \\n * **3.Wind tunnel position:** Have students place wind tunnel #1 and wind tunnel #2 according to the diagram in their Science Notebook for their assigned Team #.\\n * **4.Reminders:** Read over the things to keep in mind on page 21 in the Science Notebook, together as a class:\\n * **BE CAREFUL NOT TO PUT YOUR FINGERS NEAR THE FAN**\\n * Graph paper represents a region.\\n * A wind vane can be placed anywhere on the graph paper to determine what direction the wind is coming from.\\n * Record the wind direction by drawing an arrow in the direction the wind vane is pointing. (Recall that wind is always recorded showing the direction the wind is coming from.) If there is not a clear determination where the wind is coming from, then leave the square blank.\\n * Place a Styrofoam ball on the wind table to see the interaction between the two air masses.\\n * **5.Analyze air mass interactions** \\n\\n * Once all of the groups have finished mapping the wind direction, ask the students to determine the boundary of the two air masses by drawing a circle around the different air masses. \\n\\n * Ask the students if there was anywhere on the grid that they either had trouble deciding what direction to draw their arrow. Some students might remark that the wind vane wobbles or spins in the region between the two distinct air masses. Instruct the students to identify the diagonal region between the two air masses and circle this area with a green marker. \\n\\n* **6.Connecting the Wind Table to the interpolated map.** Ask students to compare Alaska Weather Stations: 7 pm Interpolated data with the wind map they created on their Wind Table. Lead a class conversation. See possible Discussion Points below. \\n\",\"content2\":\"\",\"mediaType\":\"none\",\"mediaCaption\":\"Last, First. \\\"Title of Work.\\\" Year created. Site Title [OR] Publisher. 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(Note that scientists also include pressure, but pressure is not covered in this unit.)\\n\\n###Wind Table Demonstration \\nThe compass rose describes the direction the wind is blowing in degrees. Wind coming directly from the South has a direction of 180\u00b0, from the East 90\u00b0, from the North 360\u00b0, etc. Place the fan to the \u201cNorth\u201d of the weather vane and turn it on. Move the weather vane so that it's at the center of the rose and have students read the wind direction from the rose. Then, move the fan to other locations. Ask students where you should move the fan to get a wind direction of, for example, 180\u00b0, 90\u00b0, 45\u00b0, etc. Move the fan to check their predictions. \\n\\n**Teacher Note:** Wind direction is determined by what direction the wind is coming from. This is a consequence of how it is measured. 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(cont.)", + "position": 4, + "show_header": true, + "show_info_assessment": true, + "show_interactive": false, + "show_sidebar": false, + "sidebar": null, + "sidebar_title": "Did you know?", + "toggle_info_assessment": false, + "embeddables": [{ + "embeddable": { + "content": "\u003Cp\u003EIDENTIFYING AIR MASSES\u003C/p\u003E\n\u003Cp\u003EIn Lesson 5 of your Science Notebook on pages 21-23, you have additional data weather station data and maps that show you the direction of the wind. On page 22, you will find a map that shows you the 7 pm reading from the additional weather stations. The arrows on the map represent the\u0026nbsp;wind direction. The data on page 23 of your Science Notebook, \"Weather Stations 7 pm Interpolated\" comes from an\u0026nbsp;interpolation\u0026nbsp;of wind direction\u0026nbsp;across the mainland of Alaska at 7 pm. See map below. Using the map on page 23, draw a line that splits the map into two parts: one section with the wind coming from the same direction and the other section with the wind coming from a different direction. It is your job to determine where you see that change in the\u0026nbsp;wind direction.\u003C/p\u003E\n\u003Cp\u003EStrategy for Identifying Two Air Masses:\u003C/p\u003E\n\u003Cp\u003E1. Make Sense of the Map:\u0026nbsp;\u003Cbr /\u003E\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026bull; Look at each row and see if the arrows change direction as you move across the row.\u0026nbsp;\u003Cbr /\u003E\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026bull; Look at each column and see if the arrows change direction as you move down the column.\u0026nbsp;\u003Cbr /\u003E2. Identify where you are going to place your line.\u0026nbsp;\u003Cbr /\u003E3. Draw your line on your paper map.\u003C/p\u003E\n\u003Cp\u003E\u003Cimg style=\"display: block; margin-left: auto; margin-right: auto;\" src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/Lesson57pmInterpolated.jpg\" width=\"623\" height=\"382\" /\u003E\u003C/p\u003E", + "is_callout": false, + "is_full_width": true, + "is_hidden": false, + "name": "", + "type": "Embeddable::Xhtml", + "ref_id": "147907-Embeddable::Xhtml" + }, + "section": "header_block" + }, { + "embeddable": { + "default_text": "", + "give_prediction_feedback": false, + "hint": "", + "is_full_width": true, + "is_hidden": false, + "is_prediction": false, + "name": "", + "prediction_feedback": "", + "prompt": "\u003Cp\u003EWhy did you draw the line there?\u003C/p\u003E", + "show_in_featured_question_report": true, + "type": "Embeddable::OpenResponse", + "ref_id": "208885-Embeddable::OpenResponse" + }, + "section": null + }] + }, { + "additional_sections": {}, + "embeddable_display_mode": "stacked", + "id": 143602, + "is_completion": false, + "is_hidden": false, + "layout": "l-full-width", + "name": "What is an air mass? (cont.)", + "position": 5, + "show_header": true, + "show_info_assessment": true, + "show_interactive": false, + "show_sidebar": false, + "sidebar": null, + "sidebar_title": "Did you know?", + "toggle_info_assessment": false, + "embeddables": [{ + "embeddable": { + "content": "\u003Cp\u003EThe line that you drew across your map represents a boundary between two\u0026nbsp;air masses. An air mass is a body of air with similar temperature and\u0026nbsp;air moisture\u0026nbsp;content. Identifying air masses and their properties is an important part of the work of atmospheric scientists. On the map you may have noticed a temperature number at the top of the square and an\u0026nbsp;air moisture\u0026nbsp;content number at the bottom of the square.\u003C/p\u003E\n\u003Cp\u003E\u003Cimg style=\"display: block; margin-left: auto; margin-right: auto;\" src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/TempMoisture.jpg\" width=\"212\" height=\"292\" /\u003E\u003C/p\u003E", + "is_callout": false, + "is_full_width": true, + "is_hidden": false, + "name": "", + "type": "Embeddable::Xhtml", + "ref_id": "147908-Embeddable::Xhtml" + }, + "section": "header_block" + }, { + "embeddable": { + "content": "\u003Cp\u003EDevelop a way to define the two air masses using the temperature and\u0026nbsp;air moisture\u0026nbsp;content values provided on the Alaskan Stations: Interpolated at 7 pm Map.\u003C/p\u003E\r\n\u003Cp\u003E\u003Cimg src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/Lesson5AirMasses1and2.jpg\" width=\"651\" height=\"429\" /\u003E\u003C/p\u003E\r\n\u003Cp\u003EDefined Air Masses for the Alaska Mainland at 7 pm\u003C/p\u003E", + "is_callout": true, + "is_full_width": true, + "is_hidden": false, + "name": "DEFINING AIR MASSES", + "type": "Embeddable::Xhtml", + "ref_id": "147909-Embeddable::Xhtml" + }, + "section": null + }, { + "embeddable": { + "custom": false, + "enable_check_answer": false, + "give_prediction_feedback": false, + "hint": "", + "is_full_width": true, + "is_hidden": false, + "is_prediction": false, + "layout": "vertical", + "multi_answer": false, + "name": "Multiple Choice Question element", + "prediction_feedback": "", + "prompt": "\u003Cp\u003E\u003Cstrong\u003EAir Mass #1 Properties\u003C/strong\u003E\u003C/p\u003E\r\n\u003Cp\u003ETemperature: Compare Air Mass #1 to Air Mass #2.\u003C/p\u003E\r\n\u003Cp\u003EAir Mass #1 is:\u003C/p\u003E", + "show_as_menu": false, + "show_in_featured_question_report": true, + "choices": [{ + "choice": "colder", + "is_correct": false, + "prompt": "" + }, { + "choice": "warmer", + "is_correct": false, + "prompt": "" + }], + "type": "Embeddable::MultipleChoice", + "ref_id": "17140-Embeddable::MultipleChoice" + }, + "section": null + }, { + "embeddable": { + "custom": false, + "enable_check_answer": false, + "give_prediction_feedback": false, + "hint": "", + "is_full_width": true, + "is_hidden": false, + "is_prediction": false, + "layout": "vertical", + "multi_answer": false, + "name": "Multiple Choice Question element", + "prediction_feedback": "", + "prompt": "\u003Cp\u003E\u003Cimg src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/images/air-moisture-scale.png\" width=\"321\" height=\"88\" /\u003E\u003C/p\u003E\r\n\u003Cp\u003EAir moisture: Compare Air Mass #1 to Air Mass #2.\u003C/p\u003E\r\n\u003Cp\u003EAir Mass #1 is:\u003C/p\u003E", + "show_as_menu": false, + "show_in_featured_question_report": true, + "choices": [{ + "choice": "more moist", + "is_correct": false, + "prompt": "" + }, { + "choice": "more dry", + "is_correct": false, + "prompt": "" + }], + "type": "Embeddable::MultipleChoice", + "ref_id": "17141-Embeddable::MultipleChoice" + }, + "section": null + }, { + "embeddable": { + "custom": false, + "enable_check_answer": false, + "give_prediction_feedback": false, + "hint": "", + "is_full_width": true, + "is_hidden": false, + "is_prediction": false, + "layout": "vertical", + "multi_answer": false, + "name": "Multiple Choice Question element", + "prediction_feedback": "", + "prompt": "\u003Cp\u003E\u003Cstrong\u003EAir Mass #2 Properties\u003C/strong\u003E\u003C/p\u003E\r\n\u003Cp\u003ETemperature: Compare Air Mass #2 to Air Mass #1.\u003C/p\u003E\r\n\u003Cp\u003EAir Mass #2 over land is:\u003C/p\u003E", + "show_as_menu": false, + 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are very interested in fronts because they are where the\u0026nbsp;weather\u0026nbsp;can change. Sometimes this change is very sudden.\u003C/p\u003E", + "is_callout": false, + "is_full_width": true, + "is_hidden": false, + "name": "", + "type": "Embeddable::Xhtml", + "ref_id": "147910-Embeddable::Xhtml" + }, + "section": "header_block" + }, { + "embeddable": { + "content": "\u003Cp\u003EGo to page 24 in your Science Notebook and compare the 7 pm interpolated map and the 7 pm radar map.\u003C/p\u003E\r\n\u003Cp\u003E\u003Cimg class=\"\" src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/Lesson5_7pmInterpolatedRADARMAPcomparison.jpg\" alt=\"\" width=\"860\" height=\"300\" /\u003E\u003C/p\u003E\r\n\u003Cp\u003EDiscuss with your research team and write a general statement that answers the question, \u0026ldquo;How do air masses affect where it rains?\"\u0026nbsp;\u0026nbsp;\u003C/p\u003E\r\n\u003Cp\u003E\u0026nbsp;\u003C/p\u003E", + "is_callout": true, + "is_full_width": true, + "is_hidden": false, + "name": "TASK", + "type": "Embeddable::Xhtml", + "ref_id": "147911-Embeddable::Xhtml" + }, + "section": null + }, { + "embeddable": { + "default_text": "", + "give_prediction_feedback": false, + "hint": "\u003Cp\u003E\u0026bull; Where is the front? Where is it raining? How do they compare?\u003Cbr /\u003E\u0026bull; How does the location of the precipitation on the radar map compare to the warm air mass, the cold air mass, and the front?\u003Cbr /\u003E\u0026bull; What is the air like where it is raining?\u003C/p\u003E", + "is_full_width": true, + "is_hidden": false, + "is_prediction": false, + "name": "", + "prediction_feedback": "", + "prompt": "\u003Cp\u003EHow do air masses affect where it rains?\u003C/p\u003E", + "show_in_featured_question_report": true, + "type": "Embeddable::OpenResponse", + "ref_id": "208886-Embeddable::OpenResponse" + }, + "section": null + }, { + "embeddable": { + "content": "\u003Cp\u003EGo to page 25 in your Science Notebook and work with you research team to make a prediction for where you think it could rain at 7 am by drawing on the 7 am weather station map in your notebook.\u003C/p\u003E\r\n\u003Cp\u003E\u003Cimg src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/L4_ACT1_Alaska%20Weather%20Stations_7am%20Interpolated.png\" width=\"437\" height=\"263\" /\u003E\u003C/p\u003E\r\n\u003Cp\u003EAlaska Stations: Interpolated at 7 am\u003C/p\u003E", + "is_callout": true, + "is_full_width": true, + "is_hidden": false, + "name": "TASK", + "type": "Embeddable::Xhtml", + "ref_id": "147912-Embeddable::Xhtml" + }, + "section": null + }, { + "embeddable": { + "default_text": "", + "give_prediction_feedback": false, + "hint": "", + "is_full_width": true, + "is_hidden": false, + "is_prediction": false, + "name": "", + "prediction_feedback": "", + "prompt": "\u003Cp\u003EExplain why you think it could rain in the area you selected.\u003C/p\u003E", + "show_in_featured_question_report": true, + "type": "Embeddable::OpenResponse", + "ref_id": "208887-Embeddable::OpenResponse" + }, + "section": null + }, { + "embeddable": { + "plugin": { + "description": "", + "author_data": "{\"tipType\":\"windowShade\",\"questionWrapper\":{\"correctExplanation\":\"correct\",\"distractorsExplanation\":\"distractor\",\"exemplar\":\"exemplar\",\"teacherTip\":\"teacherTip\",\"teacherTipImageOverlay\":\"\",\"location\":\"bottom\"},\"windowShade\":{\"windowShadeType\":\"discussionPoints\",\"layout\":\"mediaLeft\",\"initialOpenState\":false,\"content\":\"###Identifying Air Masses\\n\\nPossible discussion questions:\\n\\n* How do we identify air masses? 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Compare your prediction to the radar image for 7 am. 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Sometimes it feels cold; sometimes it feels warm. The wind is what moves air. Weather scientists use\u0026nbsp;wind direction\u0026nbsp;to distinguish multiple air masses. What happens at the boundary of those two air masses? You will explore that question using a new Virtual Model. \u0026nbsp;\u003C/p\u003E", + "is_callout": false, + "is_full_width": true, + "is_hidden": false, + "name": "", + "type": "Embeddable::Xhtml", + "ref_id": "147914-Embeddable::Xhtml" + }, + "section": "header_block" + }, { + "embeddable": { + "content": "\u003Cp\u003EThis model shows wind as moving arrowheads and precipitation as green circles. There are two air masses. Identify where the front is.\u0026nbsp;\u003C/p\u003E\r\n\u003Cp\u003EThen, by trying different settings of the temperature and moisture, see if you can make up a rule for what conditions produce precipitation along the front, and on which side of the front the precipitation will occur.\u0026nbsp;\u003C/p\u003E\r\n\u003Cp\u003EStart by pressing \u003Cstrong\u003ESetup\u003C/strong\u003E and \u003Cstrong\u003ERun\u003C/strong\u003E. As you change temperatures and moisture settings you may want to press \u003Cstrong\u003ESetup\u003C/strong\u003E occasionally to start fresh. 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Virtual Model\\n\\n**Objective:** To build students\u2019 rule refinement skills by experimenting with a model to figure out its built-in weather rules. In this model, precipitation falls under a variety of conditions that can be set by changing temperatures and moisture for two air masses. \\n\\nStudents can vary the temperature and moisture of two air masses in order to better understand how interacting air masses create patterns of rain at a front. Through this process, students will come up with an even more robust rule for predicting rain that involves interacting air masses. The specific computational thinking practice highlighted and practiced in this activity is **Rule Refinement**.\\n\\n**1. Class discussion about air mass properties.**Use the Alaska Weather Stations: 7am Interpolated map! [](https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/Lesson5AirMasses1and2.jpg) to remind students of the properties of the air masses in their regional weather system. See Discussion Points below for possible prompts. \\n\\n**2. Set up the model challenge.** \\n\\n* Have students recall the rule they developed to answer the question \u201cHow do air masses affect where it rains?\u201d \\n\\n* Students will use the Lesson 5 virtual model to help refine their rule.\\n\\n**3. Exploring the Virtual Model.** \\n\\nIntroduce the task, and give students time to explore the model. Then let them tell you what they discovered. They may notice:\\n\\n * The properties of the incoming air can be changed using the sliders on the left and bottom.\\n\\n * The direction of the wind can be seen with arrows and trails that can be turned on or off.\\n\\n * Precipitation appears as green circles with bigger circles meaning heavier rain.\\n\\n * Color of arrows correspond to temperature (Red = Warm, Blue = Cold, Purple = In Between)\\n\\n * Size of arrows correspond to air moisture (Small = dry, Large = moist or humid)\\n\\nYou may want to point out that\\n\\n * Even though the air in the model moves, the model shows airflow for a certain time. Time does not change.\\n\\n**4. Experiment with the Model to find the Rule**\\n\\nTell students that this model has a built-in rule for precipitation made by the model\u2019s programmer. 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their computer model to predict weather in Alaska. Then they tested their model to see how well it worked. They found their predictions were only right about half the time. The students had different ideas for improving the model.\u003C/p\u003E\r\n\u003Cp\u003EHere are the students\u0026rsquo; ideas:\u003C/p\u003E\r\n\u003Ctable cellpadding=\"30\"\u003E\r\n\u003Ctbody\u003E\r\n\u003Ctr\u003E\r\n\u003Cth colspan=\"2\"\u003E\u003Cstrong\u003EAlex\u003C/strong\u003E\u003C/th\u003E\r\n\u003Cth colspan=\"2\"\u003E\u003Cstrong\u003EDelana\u003C/strong\u003E\u003C/th\u003E\r\n\u003C/tr\u003E\r\n\u003Ctr\u003E\r\n\u003Ctd width=\"88\"\u003E\u003Cimg src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/Alex%206.png\" width=\"72\" height=\"90\" align=\"center\" hspace=\"10\" vspace=\"10\" /\u003E\u003C/td\u003E\r\n\u003Ctd style=\"padding: 10px;\" width=\"350\"\u003EWe need to run the model longer. The longer you run a computer model the better the prediction will be.\u003C/td\u003E\r\n\u003Ctd width=\"88\"\u003E\u003Cimg src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/Delana6.png\" width=\"70\" height=\"90\" align=\"center\" hspace=\"10\" vspace=\"10\" /\u003E\u003C/td\u003E\r\n\u003Ctd style=\"padding: 10px;\" width=\"350\"\u003EThere\u0026rsquo;s no way to make a computer model that can predict the weather. 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That way we\u0026rsquo;ll know the model works.\u003C/td\u003E\r\n\u003C/tr\u003E\r\n\u003C/tbody\u003E\r\n\u003C/table\u003E", + "is_callout": false, + "is_full_width": true, + "is_hidden": false, + "name": "", + "type": "Embeddable::Xhtml", + "ref_id": "147922-Embeddable::Xhtml" + }, + "section": "header_block" + }, { + "embeddable": { + "plugin": { + "description": null, + "author_data": "{\"tipType\":\"windowShade\",\"windowShade\":{\"windowShadeType\":\"teacherTip\",\"layout\":\"mediaLeft\",\"initialOpenState\":true,\"content\":\"###Pre-Assessment Implementation\\n*Lesson 6, Opening: How Do We Make An Accurate Model To Predict Weather? Pre-Assessment*\\nDuring the pre-assessment, each student will view the probe and make an individual choice. The request for explanation will only be on the post-assessment. 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We suggest teachers review the information and think about ways to scaffold students toward developing knowledge and practice as appropriate for their classes. We also recommend emphasizing the underlying ideas and practices, rather than on vocabulary terms. By discussing the different options, students can engage in productive talk related to these computational thinking concepts without using technical terminology. \\n\\nThis assessment probe is designed to assess and scaffold students in thinking and talking about **Rule Refinement** and, especially, **Rule Testing**. **Rule Refinement** involves refining a rule for use in a modeling environment using scientific principles and incorporating additional data, making the rule more precise, computational, and/or detecting and correcting errors. **Rule Testing** is a process of \\\"calibration\\\" between the modeling environment and the observable world. It involves systematically testing a rule to detect errors and limitations, and analyzing the efficiency of various solutions.\\n\\nThe assessment is situated in the unit context to provide an opportunity for students to make sense about rule refinement and rule testing in a specific, tangible weather problem. While one of the responses makes the most sense from a practical standpoint for this problem, other responses have implicit connections to facets of computational thinking (e.g., using understanding of systems to determine model rules and iteration in modeling). Using an indefinite problem provides space for students to think and talk about different approaches to refining and testing rules for a computer model. 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We sometimes see this type of reasoning when students and even adults talk about climate change models. Some people say things like, \u201cthey are just models, so they don\u2019t really tell us what\u2019s going to happen in the real world.\u201d \\n\\nStudents who choose Delana\u2019s response could use support in developing understanding that computer models don\u2019t need to be perfect in order to be useful. No model is perfectly accurate. Models just need to be good enough for a given purpose. Computer modelers set calibration targets that define how close to the actual event they want their prediction to be (e.g., maybe they want their model to predict the correct outcome of rain or no rain for the next day 95% of the time). Uncertainty is also built into weather models for precipitation in other ways (e.g., a forecast of 70% chance of rain for a given day). Knowing that there is a 70% chance of rain tomorrow is better than not having any information about tomorrow\u2019s weather at all. Students who choose Delana\u2019s response (as well as all the other students) could benefit from conversations about and examples of what it means for a model to be \u201cgood enough\u201d to serve a purpose.\\n\\n###Middle Level \\n\u2022\\t**Alex\u2019s response (run the model longer)** suggests awareness that models are not perfect and that they can improve over time. This response may also appeal to some students who know about the idea of computer iteration (i.e., a process in which a set of instructions is repeated in a sequence multiple times or until a condition is met). Sometimes computer models need to run over time through multiple iterations to reach a certain set of criteria for the output. However, in this case, if the computer model is only making a correct prediction about half the time, then the computer needing more time to process the data probably isn\u2019t the problem. \\n\\nStudents who choose Alex\u2019s response could benefit from a discussion about whether or not they think running the model longer would help in this case.\\n\\n\u2022\\t**Kalin\u2019s response (keep working on rules using science)** has some merit. We do want to work on model rules based on scientific principles. However, when modeling a real-world system, it\u2019s not enough to just use the rules of science to make our models. We need to know that our model is actually going to work (i.e., be sufficiently accurate in outputs such as predictions) when it is applied in the real world. Real-world systems are complex. If we just go by the rules of science, we may be overlooking possible problems with either the rules of the model (e.g., omitting an important variable) or with input data (e.g., perhaps a temperature sensor is faulty or isn\u2019t calibrated correctly). In either case, just working on the rules of the model would not be enough to know that the model really works unless we check our weather model predictions against the weather that actually occurs.\\n\\n###More Formal Ideas\\n\u2022\\t**Sage\u2019s answer (refine and test model predictions using Alaska weather data)** is the only option that acknowledges the importance of using calibration to test model rules, which is essential for establishing confidence in a computer model that is designed to represent or simulate an event or phenomenon in the real world. Weather modelers need to compare their model outputs to real-world data to ascertain how well they are working. 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Then they tested their model to see how well it worked. They found their predictions were only right about half the time. The students had different ideas for improving the model.\u003C/p\u003E\r\n\u003Cp\u003EHere are the students\u0026rsquo; ideas:\u003C/p\u003E\r\n\u003Ctable cellpadding=\"30\"\u003E\r\n\u003Ctbody\u003E\r\n\u003Ctr\u003E\r\n\u003Cth colspan=\"2\"\u003E\u003Cstrong\u003EAlex\u003C/strong\u003E\u003C/th\u003E\r\n\u003Cth colspan=\"2\"\u003E\u003Cstrong\u003EDelana\u003C/strong\u003E\u003C/th\u003E\r\n\u003C/tr\u003E\r\n\u003Ctr\u003E\r\n\u003Ctd width=\"88\"\u003E\u003Cimg src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/Alex%206.png\" width=\"72\" height=\"90\" align=\"center\" hspace=\"10\" vspace=\"10\" /\u003E\u003C/td\u003E\r\n\u003Ctd style=\"padding: 10px;\" width=\"350\"\u003EWe need to run the model longer. The longer you run a computer model the better the prediction will be.\u003C/td\u003E\r\n\u003Ctd width=\"88\"\u003E\u003Cimg src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/Delana6.png\" width=\"70\" height=\"90\" align=\"center\" hspace=\"10\" vspace=\"10\" /\u003E\u003C/td\u003E\r\n\u003Ctd style=\"padding: 10px;\" width=\"350\"\u003EThere\u0026rsquo;s no way to make a computer model that can predict the weather. Computer models aren\u0026rsquo;t the real world, so they can\u0026rsquo;t predict what will happen in the real world.\u003C/td\u003E\r\n\u003C/tr\u003E\r\n\u003C/tbody\u003E\r\n\u003Ctbody\u003E\r\n\u003Ctr\u003E\r\n\u003Cth colspan=\"2\"\u003E\u003Cstrong\u003EKalin\u003C/strong\u003E\u003C/th\u003E\r\n\u003Cth colspan=\"2\"\u003E\u003Cstrong\u003ESage\u003C/strong\u003E\u003C/th\u003E\r\n\u003C/tr\u003E\r\n\u003Ctr\u003E\r\n\u003Ctd width=\"88\"\u003E\r\n\u003Cp\u003E\u003Cimg src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/Kalin1.png\" width=\"72\" height=\"90\" align=\"center\" hspace=\"10\" vspace=\"10\" /\u003E\u003C/p\u003E\r\n\u003C/td\u003E\r\n\u003Ctd style=\"padding: 10px;\" width=\"350\"\u003EWe should keep working on the rules based on the science of weather prediction. If we get the science right, the model will be accurate.\u003C/td\u003E\r\n\u003Ctd width=\"88\"\u003E\r\n\u003Cp\u003E\u003Cimg src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/Sage4.png\" width=\"72\" height=\"90\" align=\"center\" hspace=\"8\" vspace=\"8\" /\u003E\u003C/p\u003E\r\n\u003C/td\u003E\r\n\u003Ctd style=\"padding: 10px;\" width=\"350\"\u003EWe should keep working on the rules and testing the model predictions using Alaska weather data. That way we\u0026rsquo;ll know the model works.\u003C/td\u003E\r\n\u003C/tr\u003E\r\n\u003C/tbody\u003E\r\n\u003C/table\u003E", + "is_callout": false, + "is_full_width": true, + "is_hidden": false, + "name": "", + "type": "Embeddable::Xhtml", + "ref_id": "147921-Embeddable::Xhtml" + }, + "section": "header_block" + }, { + "embeddable": { + "plugin": { + "description": null, + "author_data": "{\"tipType\":\"windowShade\",\"windowShade\":{\"windowShadeType\":\"teacherTip\",\"layout\":\"mediaLeft\",\"initialOpenState\":true,\"content\":\"###Pre-Assessment Implementation\\n*Lesson 6, Opening: How Do We Make An Accurate Model To Predict Weather? Pre-Assessment*\\nDuring the pre-assessment, each student will view the probe and make an individual choice. The request for explanation will only be on the post-assessment. After students make an individual choice for the pre-assessment, lead a discussion including, for example, a pair/share opportunity and/or full class discussion. \\n\\nAt this time, encourage students to share and discuss their ideas and reasons without indicating that any one answer is better or worse. Let the students know that they should keep thinking about this question and that the class will return to it at the end of the lesson.\",\"content2\":\"\",\"mediaType\":\"none\",\"mediaCaption\":\"Last, First. \\\"Title of Work.\\\" Year created. Site Title [OR] Publisher. 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We suggest teachers review the information and think about ways to scaffold students toward developing knowledge and practice as appropriate for their classes. We also recommend emphasizing the underlying ideas and practices, rather than on vocabulary terms. By discussing the different options, students can engage in productive talk related to these computational thinking concepts without using technical terminology. \\n\\nThis assessment probe is designed to assess and scaffold students in thinking and talking about **Rule Refinement** and, especially, **Rule Testing**. **Rule Refinement** involves refining a rule for use in a modeling environment using scientific principles and incorporating additional data, making the rule more precise, computational, and/or detecting and correcting errors. **Rule Testing** is a process of \\\"calibration\\\" between the modeling environment and the observable world. It involves systematically testing a rule to detect errors and limitations, and analyzing the efficiency of various solutions.\\n\\nThe assessment is situated in the unit context to provide an opportunity for students to make sense about rule refinement and rule testing in a specific, tangible weather problem. While one of the responses makes the most sense from a practical standpoint for this problem, other responses have implicit connections to facets of computational thinking (e.g., using understanding of systems to determine model rules and iteration in modeling). Using an indefinite problem provides space for students to think and talk about different approaches to refining and testing rules for a computer model. 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We sometimes see this type of reasoning when students and even adults talk about climate change models. Some people say things like, \u201cthey are just models, so they don\u2019t really tell us what\u2019s going to happen in the real world.\u201d \\n\\nStudents who choose Delana\u2019s response could use support in developing understanding that computer models don\u2019t need to be perfect in order to be useful. No model is perfectly accurate. Models just need to be good enough for a given purpose. Computer modelers set calibration targets that define how close to the actual event they want their prediction to be (e.g., maybe they want their model to predict the correct outcome of rain or no rain for the next day 95% of the time). Uncertainty is also built into weather models for precipitation in other ways (e.g., a forecast of 70% chance of rain for a given day). Knowing that there is a 70% chance of rain tomorrow is better than not having any information about tomorrow\u2019s weather at all. Students who choose Delana\u2019s response (as well as all the other students) could benefit from conversations about and examples of what it means for a model to be \u201cgood enough\u201d to serve a purpose.\\n\\n###Middle Level \\n\u2022\\t**Alex\u2019s response (run the model longer)** suggests awareness that models are not perfect and that they can improve over time. This response may also appeal to some students who know about the idea of computer iteration (i.e., a process in which a set of instructions is repeated in a sequence multiple times or until a condition is met). Sometimes computer models need to run over time through multiple iterations to reach a certain set of criteria for the output. However, in this case, if the computer model is only making a correct prediction about half the time, then the computer needing more time to process the data probably isn\u2019t the problem. \\n\\nStudents who choose Alex\u2019s response could benefit from a discussion about whether or not they think running the model longer would help in this case.\\n\\n\u2022\\t**Kalin\u2019s response (keep working on rules using science)** has some merit. We do want to work on model rules based on scientific principles. However, when modeling a real-world system, it\u2019s not enough to just use the rules of science to make our models. We need to know that our model is actually going to work (i.e., be sufficiently accurate in outputs such as predictions) when it is applied in the real world. Real-world systems are complex. If we just go by the rules of science, we may be overlooking possible problems with either the rules of the model (e.g., omitting an important variable) or with input data (e.g., perhaps a temperature sensor is faulty or isn\u2019t calibrated correctly). In either case, just working on the rules of the model would not be enough to know that the model really works unless we check our weather model predictions against the weather that actually occurs.\\n\\n###More Formal Ideas\\n\u2022\\t**Sage\u2019s answer (refine and test model predictions using Alaska weather data)** is the only option that acknowledges the importance of using calibration to test model rules, which is essential for establishing confidence in a computer model that is designed to represent or simulate an event or phenomenon in the real world. Weather modelers need to compare their model outputs to real-world data to ascertain how well they are working. 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You are now ready to begin to apply all of that knowledge to the unit challenge:\u0026nbsp;What will the\u0026nbsp;weather\u0026nbsp;be in Anchorage 24 hours from now?\u003C/p\u003E\n\u003Cp\u003EUse the resources from your past lessons to help inform your prediction. Go to page 28 in your Science Notebooks to review the Lesson 1, Weather Radar Maps for the Alaskan Region, to help you.\u003C/p\u003E\n\u003Cp\u003E\u003Cimg src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/L1AKRADARMAPAPRIL21_7am.png\" width=\"303\" height=\"231\" /\u003E\u003Cimg src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/L1AKRADARMAPAPRIL21_1pm.png\" width=\"303\" height=\"231\" /\u003E\u003Cimg src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/L1AKRADARMAPAPRIL21_7pm.png\" width=\"303\" height=\"231\" /\u003E\u003Cimg src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/L1AKRADARMAPAPRIL22_1am.png\" width=\"297\" height=\"230\" /\u003E\u003Cimg src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/L1AKRADARMAPAPRIL22_7am.png\" width=\"303\" height=\"231\" /\u003E\u003C/p\u003E\n\u003Cp\u003E\u0026nbsp;\u003C/p\u003E", + "is_callout": false, + "is_full_width": true, + "is_hidden": false, + "name": "", + "type": "Embeddable::Xhtml", + "ref_id": "147917-Embeddable::Xhtml" + }, + "section": "header_block" + }, { + "embeddable": { + "plugin": { + "description": "", + "author_data": "{\"tipType\":\"windowShade\",\"questionWrapper\":{\"correctExplanation\":\"correct\",\"distractorsExplanation\":\"distractor\",\"exemplar\":\"exemplar\",\"teacherTip\":\"teacherTip\",\"teacherTipImageOverlay\":\"\"},\"windowShade\":{\"windowShadeType\":\"theoryAndBackground\",\"layout\":\"mediaLeft\",\"initialOpenState\":false,\"content\":\"###LESSON 6: MODELING FRONTS\\n**HOW DO FRONTS MOVE?**\\n\\nIn this lesson, students identify the location, direction, and rate of movement of the front. 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In this activity, students use front visualizations from 11 am, 9 pm, and 7 am to see where the air masses are colliding (i.e., the front) at different times and to track the direction of the front. The specific computational thinking skills highlighted and practiced in this activity are **Decomposition**, **Pattern Recognition**, and **Model Evaluation**.\\n\\n###Activity Breakdown\\n\\n1.Play the Lesson 6 Virtual Model tutorial.\\n\\n2.Research teams use the Front Visualizations in their Science Notebooks and the Alaska Map Transparency to describe the direction the front is moving.\\n\\n3.In the student online activity, teams summarize their findings for the direction the front is moving within the region.\",\"content2\":\"\",\"mediaType\":\"none\",\"mediaCaption\":\"Last, First. \\\"Title of Work.\\\" Year created. Site Title [OR] Publisher. 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Strategy Tips \\nThe intention of this task is to provide students with a more open-ended task than seen in Lessons 1 - 4 and to give them an opportunity to apply their CT skills before solving the unit challenge. It is important that students work independently. The goal is to see if students can decompose the mini front challenge on their own. Additionally, this shift in perspective gives the students agency in their own learning to identify which CT skills are key to addressing this question. Students should realize that they know how to identify a front from Lesson 4, and have data at their disposal that can help them figure out the location of the front is at different points in time. Ideally, they will decompose \u201chow the front moves\u201d into two components: direction (which way it is heading) and speed (distance/time). Please see a list of possible discussion prompts to guide students through this process:\\n\\n\\n* Remind students that they learned how to identify a front in the last lesson, and that fronts can be an indicator of complex weather. \\n\\n* Point out that the unit challenge is to make a decision on if they are to continue, cancel, or postpone the Native Youth Olympics (NYO Games) and explain to them that figuring out where this front will be in 24 hours can help improve their prediction.\\n\\n* Raise the question: What do we need to know about the front to predict where it will be in the future? \\n\\n* Ask the research teams to:\\n\\n * Think about the question and brainstorm their ideas as a group.\\n * Identify the computational thinking skills they think will help them address this challenge. \\n\\n * Identify what features in the Virtual Model would help them answer this question. \\n * Identify what data they have from Lessons 1 - 5 that would help them answer this question.\\n* Have research teams answer the online activity questions.\",\"content2\":\"\",\"mediaType\":\"none\",\"mediaCaption\":\"Last, First. \\\"Title of Work.\\\" Year created. 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So you may be wondering when it\u0026rsquo;s going to pass through there. Where the\u0026nbsp;front\u0026nbsp;is at the time of the Alaskan Native Youth Olympics (NYO Games) will greatly affect the\u0026nbsp;weather.\u003C/p\u003E\n\u003Cp\u003ETo best predict where the\u0026nbsp;front\u0026nbsp;will be in 24 hours, you will need to figure out how fast it is moving. This is a calculation of speed (distance over time). Once you know both speed and direction (from Activity 1) of the\u0026nbsp;front, your\u0026nbsp;weather\u0026nbsp;analysis will help you answer the question \u0026ldquo;How fast is the\u0026nbsp;front\u0026nbsp;moving?\u0026rdquo;\u003C/p\u003E\n\u003Cp\u003EYou will have the following tools to help you:\u003C/p\u003E\n\u003Cp\u003E\u0026bull; Your\u0026nbsp;front images from the Virtual Model\u003Cbr /\u003E\u0026bull; A regional map transparency\u003Cbr /\u003E\u0026bull; Rulers and pens\u003C/p\u003E", + "is_callout": false, + "is_full_width": true, + "is_hidden": false, + "name": "", + "type": "Embeddable::Xhtml", + "ref_id": "147919-Embeddable::Xhtml" + }, + "section": "header_block" + }, { + "embeddable": { + "content": "\u003Cp\u003EUsing the available materials, develop a strategy for calculating the rate of the\u0026nbsp;front. Remember that speed equals distance an object moves divided by the time it takes the object to move to its new location.\u003C/p\u003E\r\n\u003Cp style=\"padding-left: 30px;\"\u003E\u003Cstrong\u003E\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Speed = Distance/Time\u003C/strong\u003E\u003C/p\u003E", + "is_callout": true, + "is_full_width": true, + "is_hidden": false, + "name": "TASK ", + "type": "Embeddable::Xhtml", + "ref_id": "147920-Embeddable::Xhtml" + }, + "section": null + }, { + "embeddable": { + "default_text": "", + "give_prediction_feedback": false, + "hint": "\u003Cp\u003E\u0026bull; Your answer should be a rate or speed.\u003C/p\u003E\r\n\u003Cp\u003E\u0026bull; Speed is a measurement of distance over time.\u003C/p\u003E\r\n\u003Cp\u003E\u0026bull; Distance can be measured in units of kilometers, miles, etc.\u003C/p\u003E\r\n\u003Cp\u003E\u0026bull; Time can be measured in hours, days, etc.\u003C/p\u003E", + "is_full_width": true, + "is_hidden": false, + "is_prediction": false, + "name": "", + "prediction_feedback": "", + "prompt": "\u003Cp\u003EHow fast is the\u0026nbsp;front\u0026nbsp;moving? Be as specific as you can.\u003C/p\u003E", + "show_in_featured_question_report": true, + "type": "Embeddable::OpenResponse", + "ref_id": "208896-Embeddable::OpenResponse" + }, + "section": null + }, { + "embeddable": { + "default_text": "", + "give_prediction_feedback": false, + "hint": "\u003Cp\u003E\u0026bull; Explain your strategy.\u003C/p\u003E\r\n\u003Cp\u003E\u0026bull; Talk about what you did to come up with your answer.\u003C/p\u003E", + "is_full_width": true, + "is_hidden": false, + "is_prediction": false, + "name": "", + "prediction_feedback": "", + "prompt": "\u003Cp\u003EDescribe how your team figured out how fast the\u0026nbsp;front\u0026nbsp;is moving.\u003C/p\u003E", + "show_in_featured_question_report": true, + "type": "Embeddable::OpenResponse", + "ref_id": "208897-Embeddable::OpenResponse" + }, + "section": null + }, { + "embeddable": { + "plugin": { + "description": "", + "author_data": "{\"tipType\":\"windowShade\",\"questionWrapper\":{\"correctExplanation\":\"correct\",\"distractorsExplanation\":\"distractor\",\"exemplar\":\"exemplar\",\"teacherTip\":\"teacherTip\",\"teacherTipImageOverlay\":\"\"},\"windowShade\":{\"windowShadeType\":\"theoryAndBackground\",\"layout\":\"mediaLeft\",\"initialOpenState\":false,\"content\":\"###Activity 2 - How Fast is the Front Moving?\\n\\nThe focus of this activity is for students to analyze the visualization data they generated in Activity 1 and to develop a statement defining the speed of the front moving across the region. The activity ends with research teams developing a description of how fast the front is moving and recording it in the student online activity. The specific computational thinking practice highlighted and practiced in this activity is **Pattern Recognition**.\\n\\n\u003Cbr\u003E**1. Calculate the speed the front is moving.**\\n\\n* Pass out to the research teams their Science Notebooks with the front visualizations, Regional Map Transparency, wet erase markers, paper towels, and rulers. \\n\\n* Students may also want to use the [L1A2: Alaska Weather Station Data Sheet](https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/L1A2_WeatherStationDataAK.png) and the [L4A1: Alaska Additional Weather Stations handouts](https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/L4A1_AdditionalWeatherStationsDataSheet_AK.png). \\n\\n* The primary challenge for students will be deciding where on the front to use as a reference point when measuring the distance that it moves from timestamp to timestamp. 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One of your jobs on this committee is to watch the\u0026nbsp;weather\u0026nbsp;and determine if the event is safe to proceed as\u0026nbsp;planned, or if it should be\u0026nbsp;postponed\u0026nbsp;or\u0026nbsp;even canceled.\u003C/p\u003E\n\u003Cp\u003EIt\u0026rsquo;s time to put your computational thinking skills to work!\u003C/p\u003E", + "is_callout": false, + "is_full_width": true, + "is_hidden": false, + "name": "", + "type": "Embeddable::Xhtml", + "ref_id": "147923-Embeddable::Xhtml" + }, + "section": "header_block" + }, { + "embeddable": { + "plugin": { + "description": "", + "author_data": "{\"tipType\":\"windowShade\",\"questionWrapper\":{\"correctExplanation\":\"correct\",\"distractorsExplanation\":\"distractor\",\"exemplar\":\"exemplar\",\"teacherTip\":\"teacherTip\",\"teacherTipImageOverlay\":\"\"},\"windowShade\":{\"windowShadeType\":\"theoryAndBackground\",\"layout\":\"mediaLeft\",\"initialOpenState\":false,\"content\":\"###LESSON 7: ANALYZING DATA AND MAKING A PREDICTION\\n\\n**What will the local weather be 24 hours from now?**\\n\\nIn this lesson, students revisit the unit challenge and the original question posted to them in Lesson 1, \\\"Should the NYO Games proceed as planned, be postponed or canceled?\\\" Students assume the role of weather forecasters and make a weather prediction for Anchorage on April 23 at 7 am using regional data and models they have been exploring throughout this unit. 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Although we have not named the skill until now, notice in the table below the skills you have used to help decide if the NYO Games should proceed.\u003C/p\u003E\r\n\u003Ctable cellpadding=\"30\"\u003E\r\n\u003Ctbody\u003E\r\n\u003Ctr bgcolor=\"#D3D3D3\"\u003E\r\n\u003Cth style=\"border: 1px solid black;\" colspan=\"1\"\u003E\u003Cstrong\u003EDefinition\u003C/strong\u003E\u003C/th\u003E\r\n\u003Cth style=\"border: 1px solid black;\" colspan=\"1\"\u003E\u0026nbsp;\u003C/th\u003E\r\n\u003Cth style=\"border: 1px solid black;\" colspan=\"1\"\u003E\u003Cstrong\u003EComputational Thinking Skill\u003C/strong\u003E\u003C/th\u003E\r\n\u003C/tr\u003E\r\n\u003Ctr\u003E\r\n\u003Ctd style=\"border: 1px solid black; padding: 20px;\" width=\"300\"\u003E\r\n\u003Cp style=\"text-align: left;\"\u003EOrganizing a large amount of information (data) into smaller more manageable parts.\u003C/p\u003E\r\n\u003C/td\u003E\r\n\u003Ctd style=\"border: 1px solid black; text-align: center;\" width=\"250\"\u003E\u003Cimg src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/Glossary/ct-decomposition.jpg\" width=\"235\" height=\"132\" /\u003E\u003C/td\u003E\r\n\u003Ctd style=\"border: 1px solid black; text-align: center; padding: 20px;\" width=\"300\"\u003E\r\n\u003Cp\u003E\u003Cstrong\u003EDecomposition\u003C/strong\u003E\u003C/p\u003E\r\n\u003Cp\u003EIn \u003Cstrong\u003ELesson 1, \u003C/strong\u003Eyou organized weather station data over a two-day period and radar maps of Alaska every 6 hours to make a prediction.\u003C/p\u003E\r\n\u003C/td\u003E\r\n\u003C/tr\u003E\r\n\u003Ctr style=\"border: 1px solid black; text-align: center;\"\u003E\r\n\u003Ctd style=\"border: 1px solid black; padding: 20px;\" width=\"300\"\u003E\r\n\u003Cp style=\"text-align: left;\"\u003ERecognizing that data or information is repeating in a logical (expected) way.\u003C/p\u003E\r\n\u003C/td\u003E\r\n\u003Ctd style=\"border: 1px solid black;\" width=\"250\"\u003E\u003Cimg src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/Captioned_Videos/new_picts/Lesson_5_new_Embedded_assessment/Netlogo_temp_model.png\" width=\"159\" height=\"181\" /\u003E\u003C/td\u003E\r\n\u003Ctd style=\"border: 1px solid black; padding: 20px;\" width=\"300\"\u003E\r\n\u003Cp style=\"text-align: center;\"\u003E\u003Cstrong\u003EPattern Recognition\u003C/strong\u003E\u003C/p\u003E\r\n\u003Cp\u003EIn \u003Cstrong\u003ELesson 2\u003C/strong\u003E, you ran the model to see temperature data and patterns of data moving across the map. Before and after each run of the model, you interpolated data. You discovered that warm and cold spots on the map are at times on certain sides, and also you saw these spots change location over time.\u003C/p\u003E\r\n\u003Cp\u003EIn\u003Cstrong\u003E Lesson 3 and 4\u003C/strong\u003E, you ran the models to develop a general statement to answer the question \"Where does it rain?\".\u003C/p\u003E\r\n\u003C/td\u003E\r\n\u003C/tr\u003E\r\n\u003Ctr style=\"border: 1px solid black; text-align: center;\"\u003E\r\n\u003Ctd style=\"border: 1px solid black; padding: 20px;\" width=\"300\"\u003E\r\n\u003Cp style=\"text-align: left;\"\u003EEstimating an unknown value based on surrounding information.\u003C/p\u003E\r\n\u003C/td\u003E\r\n\u003Ctd style=\"border: 1px solid black;\" width=\"250\"\u003E\u003Cimg class=\"\" src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/Glossary/interpolation.jpg\" alt=\"\" width=\"206\" height=\"117\" /\u003E\u003C/td\u003E\r\n\u003Ctd style=\"border: 1px solid black; padding: 20px;\" width=\"300\"\u003E\r\n\u003Cp style=\"text-align: center;\"\u003E\u003Cstrong\u003EInterpolation\u003C/strong\u003E\u003C/p\u003E\r\n\u003Cp style=\"text-align: center;\"\u003EIn \u003Cstrong\u003ELesson 2\u003C/strong\u003E, you made best guess estimates of the temperatures that were missing on the map.\u003C/p\u003E\r\n\u003C/td\u003E\r\n\u003C/tr\u003E\r\n\u003Ctr style=\"border: 1px solid black; 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The students will make a computer model to predict\u0026nbsp;weather\u0026nbsp;in Alaska.\u003C/p\u003E\r\n\u003Cp\u003EFour students in Ms. Tevuk\u0026rsquo;s class are figuring out how to estimate the temperature of a location. The students are looking at the map below and have different ideas for estimating the temperature at the location marked X using the recorded temperatures of 31\u02da and 59\u02da.\u003C/p\u003E\r\n\u003Cp\u003E\u003Cimg class=\"\" style=\"display: block; margin-left: auto; margin-right: auto;\" src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/L2AssessmentQ.png\" alt=\"\" width=\"550\" height=\"62\" /\u003E\u003C/p\u003E\r\n\u003Cp\u003EHere are the students\u0026rsquo; ideas:\u003C/p\u003E\r\n\u003Ctable cellpadding=\"30\"\u003E\r\n\u003Ctbody\u003E\r\n\u003Ctr\u003E\r\n\u003Cth colspan=\"2\"\u003E\u003Cstrong\u003EAlex\u003C/strong\u003E\u003C/th\u003E\r\n\u003Cth colspan=\"2\"\u003E\u003Cstrong\u003EDelana\u003C/strong\u003E\u003C/th\u003E\r\n\u003C/tr\u003E\r\n\u003Ctr\u003E\r\n\u003Ctd width=\"88\"\u003E\u003Cimg src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/Alex1.png\" width=\"60\" height=\"88\" align=\"center\" hspace=\"10\" vspace=\"10\" /\u003E\u003C/td\u003E\r\n\u003Ctd style=\"padding: 10px;\" width=\"350\"\u003EWe should use the number that is exactly halfway in between 31\u02daand 59\u02da. 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You can\u0026rsquo;t be confident unless you measure it.\u003C/td\u003E\r\n\u003Ctd width=\"88\"\u003E\r\n\u003Cp\u003E\u003Cimg src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/Sage1.png\" width=\"65\" height=\"92\" align=\"center\" hspace=\"8\" vspace=\"8\" /\u003E\u003C/p\u003E\r\n\u003C/td\u003E\r\n\u003Ctd style=\"padding: 10px;\" width=\"350\"\u003EThe X is closer to the 59\u02da than to the 31\u02da, so let\u0026rsquo;s choose a number closer to 59\u02da. 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Pre-Assessment*\\nDuring the pre-assessment, each student will view the probe and make an individual choice. The request for explanation will only be on the post-assessment. After students make an individual commitment for the pre-assessment, you can lead a discussion including, for example, a pair/share opportunity and/or full class discussion. \\n\\nAt this time, encourage students to share and discuss their ideas and reasons without indicating that any one answer is better or worse. Let the students know that they should keep thinking about this question and that the class will return to it at the end of the lesson.\\n\",\"content2\":\"\",\"mediaType\":\"none\",\"mediaCaption\":\"Last, First. \\\"Title of Work.\\\" Year created. Site Title [OR] Publisher. 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Review the information and consider ways to scaffold students toward developing knowledge and practice as appropriate for their classes. We also recommend during the first implementation of the probe, you scaffold students to focus on student ideas about this problem, rather than on vocabulary terms such as **interpolation**. By discussing the different options, students can engage in productive talk related to data sense making and computational thinking without using technical terminology. 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It might be helpful to discuss that we can never collect all the data in the world; there\u2019s too much! Because of this, we need a way to fill in missing values using the data that we do have available. \\n\\n###Middle Level \\n\u2022\\t**Both Alex\u2019s response (choose the value half way between)** and **Sage\u2019s response (choose a number closer to 59)** might be reasonable estimates in certain circumstances (e.g., for picking out what clothes to wear if you were at location X at that time). These approaches are both better than just choosing a random value as an estimate for X. 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The students will make a computer model to predict\u0026nbsp;weather\u0026nbsp;in Alaska.\u003C/p\u003E\r\n\u003Cp\u003EFour students in Ms. Tevuk\u0026rsquo;s class are figuring out how to estimate the temperature of a location. The students are looking at the map below and have different ideas for estimating the temperature at the location marked X using the recorded temperatures of 31\u02da and 59\u02da.\u003C/p\u003E\r\n\u003Cp\u003E\u003Cimg class=\"\" style=\"display: block; margin-left: auto; margin-right: auto;\" src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/L2AssessmentQ.png\" alt=\"\" width=\"550\" height=\"62\" /\u003E\u003C/p\u003E\r\n\u003Cp\u003EHere are the students\u0026rsquo; ideas:\u003C/p\u003E\r\n\u003Ctable cellpadding=\"30\"\u003E\r\n\u003Ctbody\u003E\r\n\u003Ctr\u003E\r\n\u003Cth colspan=\"2\"\u003E\u003Cstrong\u003EAlex\u003C/strong\u003E\u003C/th\u003E\r\n\u003Cth colspan=\"2\"\u003E\u003Cstrong\u003EDelana\u003C/strong\u003E\u003C/th\u003E\r\n\u003C/tr\u003E\r\n\u003Ctr\u003E\r\n\u003Ctd width=\"88\"\u003E\u003Cimg src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/Alex1.png\" width=\"60\" height=\"88\" align=\"center\" hspace=\"10\" vspace=\"10\" /\u003E\u003C/td\u003E\r\n\u003Ctd style=\"padding: 10px;\" width=\"350\"\u003EWe should use the number that is exactly halfway in between 31\u02daand 59\u02da. That\u0026rsquo;s the most exact way to estimate.\u003C/td\u003E\r\n\u003Ctd width=\"88\"\u003E\u003Cimg src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/Delana1.png\" width=\"65\" height=\"92\" align=\"center\" hspace=\"10\" vspace=\"10\" /\u003E\u003C/td\u003E\r\n\u003Ctd style=\"padding: 10px;\" width=\"350\"\u003EWe should mark a number line along the map with the estimate in each square going up the same amount between 31\u02da and 59\u02da. That\u0026rsquo;d be the best estimate.\u003C/td\u003E\r\n\u003C/tr\u003E\r\n\u003C/tbody\u003E\r\n\u003Ctbody\u003E\r\n\u003Ctr\u003E\r\n\u003Cth colspan=\"2\"\u003E\u003Cstrong\u003EKalin\u003C/strong\u003E\u003C/th\u003E\r\n\u003Cth colspan=\"2\"\u003E\u003Cstrong\u003ESage\u003C/strong\u003E\u003C/th\u003E\r\n\u003C/tr\u003E\r\n\u003Ctr\u003E\r\n\u003Ctd width=\"88\"\u003E\r\n\u003Cp\u003E\u003Cimg src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/Kalin.png\" width=\"65\" height=\"88\" align=\"center\" hspace=\"10\" vspace=\"10\" /\u003E\u003C/p\u003E\r\n\u003C/td\u003E\r\n\u003Ctd style=\"padding: 10px;\" width=\"350\"\u003EIt doesn\u0026rsquo;t make sense to estimate the temperature at the X. We\u0026rsquo;d need to go there and measure the temperature. You can\u0026rsquo;t be confident unless you measure it.\u003C/td\u003E\r\n\u003Ctd width=\"88\"\u003E\r\n\u003Cp\u003E\u003Cimg src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/Sage1.png\" width=\"65\" height=\"92\" align=\"center\" hspace=\"8\" vspace=\"8\" /\u003E\u003C/p\u003E\r\n\u003C/td\u003E\r\n\u003Ctd style=\"padding: 10px;\" width=\"350\"\u003EThe X is closer to the 59\u02da than to the 31\u02da, so let\u0026rsquo;s choose a number closer to 59\u02da. 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Pre-Assessment*\\nDuring the pre-assessment, each student will view the probe and make an individual choice. The request for explanation will only be on the post-assessment. After students make an individual commitment for the pre-assessment, you can lead a discussion including, for example, a pair/share opportunity and/or full class discussion. \\n\\nAt this time, encourage students to share and discuss their ideas and reasons without indicating that any one answer is better or worse. Let the students know that they should keep thinking about this question and that the class will return to it at the end of the lesson.\\n\",\"content2\":\"\",\"mediaType\":\"none\",\"mediaCaption\":\"Last, First. \\\"Title of Work.\\\" Year created. Site Title [OR] Publisher. 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Review the information and consider ways to scaffold students toward developing knowledge and practice as appropriate for their classes. We also recommend during the first implementation of the probe, you scaffold students to focus on student ideas about this problem, rather than on vocabulary terms such as **interpolation**. By discussing the different options, students can engage in productive talk related to data sense making and computational thinking without using technical terminology. During the ensuing lesson and the second implementation of the probe, the term interpolation can be used, as appropriate.\\n\\nThis assessment probe is designed to assess and scaffold students in thinking and talking about **interpolation**. **Interpolation** means estimating a value between ones that are known or tabulated using surrounding points or values (that is, estimating an unknown value based on surrounding information). \\n\\nThe assessment is situated within the unit context to provide an opportunity for students to make sense about interpolation of a specific, tangible weather question (i.e., temperatures along a map transect). There is always uncertainty involved when interpolating across data. Also, depending on circumstances, different methods may be appropriate. For example, if the students were trying to figure out how to dress for the day at location X, then simply choosing a number somewhere between the two might be sufficient. 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It might be helpful to discuss that we can never collect all the data in the world; there\u2019s too much! Because of this, we need a way to fill in missing values using the data that we do have available. \\n\\n###Middle Level \\n\u2022\\t**Both Alex\u2019s response (choose the value half way between)** and **Sage\u2019s response (choose a number closer to 59)** might be reasonable estimates in certain circumstances (e.g., for picking out what clothes to wear if you were at location X at that time). These approaches are both better than just choosing a random value as an estimate for X. However, for contexts in which more precision is called for (e.g., making a weather model), then there are ways that we can be more precise in our approaches to interpolation. \\n\\nStudents who choose Alex\u2019s and/or Sage\u2019s response could benefit from discussions of when and why we sometimes might need to be more precise in our estimation approaches. \\n\\n\\n###More Formal Idea\\n\u2022\\t**Delana\u2019s response (mark a number line with the estimate in each square going up the same amount between the two measured values)** suggests that she understands which mathematical interpolation approach will give the most precise value. Again, this level of precision will take more time and effort, and may not even be necessary in some circumstances, as discussed above. 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She will discuss how temperature plays an important part in predicting weather.\u003C/p\u003E", + "is_callout": true, + "is_full_width": true, + "is_hidden": false, + "name": "", + "type": "Embeddable::Xhtml", + "ref_id": "147936-Embeddable::Xhtml" + }, + "section": "header_block" + }, { + "embeddable": { + "name": "", + "url_fragment": null, + "authored_state": "{\"version\":1,\"questionType\":\"iframe_interactive\",\"videoUrl\":\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/Captioned_Videos/JackieLesson2_88_Captioned.mp4\",\"poster\":\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/Captioned_Videos/Posters/Poster_L2_Video.png\"}", + "is_hidden": false, + "is_full_width": true, + "show_in_featured_question_report": true, + "inherit_aspect_ratio_method": true, + "custom_aspect_ratio_method": null, + "inherit_native_width": true, + "custom_native_width": 576, + "inherit_native_height": true, + "custom_native_height": 435, + "inherit_click_to_play": true, + "custom_click_to_play": false, + "inherit_full_window": true, + "custom_full_window": false, + "inherit_click_to_play_prompt": true, + "custom_click_to_play_prompt": null, + "inherit_image_url": true, + "custom_image_url": null, + "library_interactive": { + "hash": "34e1a2a39c058da8ff4ffe5a09ad14af337c4a01", + "data": { + "aspect_ratio_method": "DEFAULT", + "authoring_guidance": "", + "base_url": "https://models-resources.concord.org/question-interactives/version/v1.1.0/video-player/", + "click_to_play": false, + "click_to_play_prompt": null, + "description": "This video player will not have the blue header bar above the interactive.\r\nIt does not save the students position in the video. \r\nIt will not show up in the teacher report.", + "enable_learner_state": false, + "full_window": false, + "has_report_url": false, + "image_url": null, + "name": "Video Player", + "native_height": 435, + "native_width": 576, + "no_snapshots": false, + "show_delete_data_button": false, + "thumbnail_url": "", + "customizable": false, + "authorable": true + } + }, + "type": "ManagedInteractive", + "ref_id": "1705-ManagedInteractive", + "linked_interactives": [] + }, + "section": "header_block" + }] + }, { + "additional_sections": null, + "embeddable_display_mode": "stacked", + "id": 143207, + "is_completion": false, + "is_hidden": false, + "layout": "l-full-width", + "name": "Opening", + "position": 2, + "show_header": true, + "show_info_assessment": true, + "show_interactive": false, + "show_sidebar": false, + "sidebar": null, + "sidebar_title": "Did you know?", + "toggle_info_assessment": false, + "embeddables": [{ + "embeddable": { + "content": "\u003Cp\u003EHave you ever wondered why some temperature displays are in color (for instance, television weather reports), but a thermometer displays temperature in numbers? Or how weather apps can tell you what the temperature is wherever you are? In this lesson, you are going to learn what it means to display temperature for mainland Alaska.\u003C/p\u003E\r\n\u003Cp\u003EAs\u0026nbsp; weather scientists (meteorologists), you will experience a virtual storm event in your classroom. As the virtual storm event occurs, you and your research team will collect and record temperature data.\u0026nbsp;\u003C/p\u003E\r\n\u003Cp\u003EAs part of your lesson challenge, you will need to determine how to capture the data, how to organize the data, and how the data should be displayed. Once you have developed a full picture of the virtual storm event, you will use this data to make a prediction of what the temperature will be at a later time.\u003C/p\u003E", + "is_callout": false, + "is_full_width": true, + "is_hidden": false, + "name": "", + "type": "Embeddable::Xhtml", + "ref_id": "147375-Embeddable::Xhtml" + }, + "section": "header_block" + }, { + "embeddable": { + "name": "Holder for Kevin's video", + "url_fragment": null, + "authored_state": "{\"version\":1,\"questionType\":\"iframe_interactive\"}", + "is_hidden": false, + "is_full_width": true, + "show_in_featured_question_report": true, + "inherit_aspect_ratio_method": true, + "custom_aspect_ratio_method": null, + "inherit_native_width": true, + "custom_native_width": 576, + "inherit_native_height": true, + "custom_native_height": 435, + "inherit_click_to_play": true, + "custom_click_to_play": false, + "inherit_full_window": true, + "custom_full_window": false, + "inherit_click_to_play_prompt": true, + "custom_click_to_play_prompt": null, + "inherit_image_url": true, + "custom_image_url": null, + "library_interactive": { + "hash": "34e1a2a39c058da8ff4ffe5a09ad14af337c4a01", + "data": { + "aspect_ratio_method": "DEFAULT", + "authoring_guidance": "", + "base_url": "https://models-resources.concord.org/question-interactives/version/v1.1.0/video-player/", + "click_to_play": false, + "click_to_play_prompt": null, + "description": "This video player will not have the blue header bar above the interactive.\r\nIt does not save the students position in the video. \r\nIt will not show up in the teacher report.", + "enable_learner_state": false, + "full_window": false, + "has_report_url": false, + "image_url": null, + "name": "Video Player", + "native_height": 435, + "native_width": 576, + "no_snapshots": false, + "show_delete_data_button": false, + "thumbnail_url": "", + "customizable": false, + "authorable": true + } + }, + "type": "ManagedInteractive", + "ref_id": "1706-ManagedInteractive", + "linked_interactives": [] + }, + "section": "header_block" + }, { + "embeddable": { + "plugin": { + "description": "", + "author_data": "{\"tipType\":\"windowShade\",\"questionWrapper\":{\"correctExplanation\":\"correct\",\"distractorsExplanation\":\"distractor\",\"exemplar\":\"exemplar\",\"teacherTip\":\"teacherTip\",\"teacherTipImageOverlay\":\"\"},\"windowShade\":{\"windowShadeType\":\"theoryAndBackground\",\"layout\":\"mediaLeft\",\"initialOpenState\":false,\"content\":\"### LESSON 2: DISPLAYING DATA:\\n\\n**HOW CAN WEATHER FROM THE PAST INFORM FUTURE WEATHER PREDICTIONS?**\\n\\nIn this lesson, students are introduced to the virtual storm technology by experiencing a weather event move through their classroom. A weather station collects data about the current weather at a specific location. The strategic placement of multiple stations and use of digital tools and mathematical concepts allows weather scientists to create a more accurate and complete model/visualization of the weather over a region and analyze it for patterns and trends. \\n\\n**LEARNING GOALS**\\n\\nStudents will be able to:\\n\\n* Take a limited amount of information and develop a more complete picture of the weather (create a weather visualization)\\n\\n* Explain a weather map using traditional weather symbols and codes (weather stations with temperature)\\n\\n* Make minimally informed predictions about future weather events\\n\\n* Explain that weather varies over time\\n\\nComputational Thinking (CT) Skills introduced in this lesson can be found in the table below:\\n\\n| CT Skill | Definition | Use in Lesson |\\n|---------------------|------------------------------------------------------------------------------------------------|-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|\\n| Data Aggregation | Describes the data collection and organization process you use to better understand the topic. | Students will collect temperature data from tablet/laptop and organize the data in charts on the wall. |\\n| Data Abstraction | Simplifying data to make it easier to interpret and find patterns. | Students will come up with a color scheme for temperature and change how the data is represented from numbers to temperature categories, and then to colors. |\\n| Interpolation | Estimating an unknown value based on surrounding information. | Students will make best guess estimates of the temperatures that are missing on the map. |\\n| Pattern Recognition | Recognizing that data or information is repeating in a logical (expected) way. | Students collect data in two rounds and see patterns of data moving across the charts. Before and after each data collection they will interpolate data. They will discover that warm and cold spots on the map are consistently on certain sides, and also see these spots change over time. |\\n| Extrapolation | Following a pattern beyond the known data points. | Students predict future weather based on patterns they observe in the changing temperatures they collected and visualized. |\\n \",\"content2\":\"\",\"mediaType\":\"none\",\"mediaCaption\":\"Last, First. \\\"Title of Work.\\\" Year created. Site Title [OR] Publisher. 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(10 mins)\\n\\n### MATERIALS AND SET-UP\\nActivity 1 - Virtual Storm: Displaying Temperature Data\\n \\nThis activity requires significant setup time and you may want to plan a few hours to transform the classroom into a 7x7 gridded space and to test and set up the iPads/laptops. \\n\\n**Per Research Team (2-4 students):**\\n\\n* Marker\\n* 3\\\" x 3\\\" sticky notes in the following colors: blue, green, yellow, red, purple, orange\\n* Fully charged and connected iPad/laptop that can display the online activity\\n* Set of colored pencils (for individual student sheets)\\n\\n**Per Class:**\\n\\n* Click [HERE](https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/GraphCoordinates_AK.pdf) and print \u201cA-G\u201d and \\\"1-7\\\" coordinates in the largest font possible.\\n\\n* Push desks to walls to get as much open space in your classroom as possible.\\n\\n* Tape labels to the classroom walls, evenly spaced. Make sure the letters are on opposite walls and the numbers on walls opposite, mirroring each other. See image below for an example:\\n\\n\\n\\n* Students should be able to stand in the grid. For example, the smiley face represents a student standing in G6. Adapt the grid points to what you have available in your learning space.\\n\\n**Weather maps:**\\n\\n* Place four large poster-sized sheets of gridded paper on a classroom wall, organizing the chart paper in a row. Each sheet will contain a 7 x 7 grid with axes labeled to match the room set-up. Click [HERE](https://youtu.be/HD_6BAHib1A) to watch a tutorial on how to create weather map grids for your classroom. \\n\\n* Label the top of each sheet with a different time: 7:00 am, 11:00 am, 3:00 pm, and 7:00 pm, and organize them on the wall in order of the time.\\n\\n* Have students track the virtual weather event and record their group's data on the tracking sheet in their Science Notebook.\\n\\n**City Markers:**\\n\\n* Print five city markers by clicking [HERE - PDF](https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/GraphCoordinates_AK.pdf)\\n\\n* Place \\\"City Markers\\\" on the floor in the appropriate classroom grid locations that correspond to the map shown in the image below:\\n\\n\",\"content2\":\"\",\"mediaType\":\"none\",\"mediaCaption\":\"Last, First. \\\"Title of Work.\\\" Year created. Site Title [OR] Publisher. 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Click\u0026nbsp;\u003Cem\u003ESetup\u003C/em\u003E and \u003Cem\u003ERun.\u003C/em\u003E\u0026nbsp;Then click each weather station to see the temperature observed for the communities across Alaska at the given time.\u003C/p\u003E\r\n\u003Cp\u003EThe boxes on the grid are called \u003Cem\u003Ecells\u003C/em\u003E and are identified with a letter and a number.\u0026nbsp;\u003C/p\u003E", + "is_callout": true, + "is_full_width": true, + "is_hidden": false, + "name": "TASK", + "type": "Embeddable::Xhtml", + "ref_id": "149057-Embeddable::Xhtml" + }, + "section": "header_block" + }, { + "embeddable": { + "plugin": { + "description": "", + "author_data": "{\"tipType\":\"windowShade\",\"questionWrapper\":{\"correctExplanation\":\"correct\",\"distractorsExplanation\":\"distractor\",\"exemplar\":\"exemplar\",\"teacherTip\":\"teacherTip\",\"teacherTipImageOverlay\":\"\"},\"windowShade\":{\"windowShadeType\":\"theoryAndBackground\",\"layout\":\"mediaLeft\",\"initialOpenState\":false,\"content\":\"### Activity 1 - Virtual Storm: Visualizing Temperature \\n\\nIn this activity, students simulate the experience of a weather scientist collecting weather data for a large area and organizing it into useful maps to predict a future weather event. Students collaboratively negotiate what the data means, as well as how to accurately record the data and represent it so they can use the emerging pattern to predict a future weather event. The specific computational thinking practices highlighted and practiced in this activity are **Data Aggregation**, **Abstraction**, and **Interpolation**.\\n\\n###Activity Breakdown\\n**1. Setting the stage for the virtual storm.** The grid in the classroom represents a smaller region in Alaska than the area covered in the Lesson 1 radar images. This area includes the following cities: Bettles, Gelena, Nome, Noorvik, and St. Mary\u2019s. In their research teams, students collect temperature data every four hours throughout the region for an eight-hour period of time. \\n\\n* Have a student stand in a square and ask the class to identify the coordinates of where they are standing. Repeat until clear.\\n\\n**2. Round 1 - Starting the Virtual Storm technology. **\\n\\n* Ask research teams to select a student from their team to move to an unoccupied grid cell. \\n\\n* Launch the Virtual Storm technology and have another student from the team record the temperature in the selected cell onto the poster sheet labeled \\\"7:00 am.\\\" \\n\\n* Click \\\"PLAY\\\" on the Virtual Storm technology. Instruct the students to watch the clock in the Weather Sensor, and every four hours record the temperature readings onto the corresponding poster sheets on the walls (7:00 am, 11:00 am, 3:00 pm). After this round, all posters should have eight squares filled in. \\n\\n**3. Round 2 - Students gaining practice by repeating the process.**\\n\\n* Click the \u201cRESET\u201d button. Ask research groups to choose new positions on the grid. \\n* Run the simulation and encourage students to collect and record the data on the three maps again. At the end of this round, each chart should have 16 squares filled in on each chart.\\n\\n**4. Round 3 - Be more strategic.**\\n\\n* Let the research teams rethink their position and either stay or move to a more strategically chosen position.\\n\\n* Run the simulation again, asking students to record the data on three charts. At the end of this round, 24 squares should be filled in with temperature data.\\n\\n** 5. Class Discussion - Emerging patterns \u0026 abstraction.**\\n\\n* Help students develop a color scheme of their choosing, and suggest colored sticky notes for the scheme. Honor the way students want to do it and post the scheme on the wall. For example, students might come up with six temperature categories:\\n * 10-19\u00b0F/-12.2 to -7.2\u00b0C: purple (extremely cold)\\n * 20-29\u00b0F/-6.7 to -1.7\u00b0C: blue (very cold)\\n * 30-39\u00b0F/-1.1 to 3.9\u00b0C: green (cold)\\n * 40-49\u00b0F/4.4 to 9.4\u00b0C: yellow (cool)\\n * 50-59\u00b0F/10 to 15\u00b0C: orange (warm)\\n * 60-69\u00b0F/15.6 to 20.6\u00b0C: red (very warm)\\n\\n* Before going on, have students place the colored sticky notes with the temperatures written on them over the original temperatures. Each team is responsible for their first three postings. \\n\\n** 6. Round 4 - Interpolation test.** \\n\\n* Direct the research teams to choose a new positions on the grid and ask them to take a **\\\"GUESS\\\"** of what the temperature will be for each of the charts.\\n\\n* Run the simulation. Students use the correct colored post-it note for the actual temperature and write **\u201cACTUAL\u201d** on the note and place it over their previous guesses. At the end of this round, there should be 32 squares covered on each chart.\\n\\n**7. Class discussion - Introduce interpolation strategy.** Please see Interpolation Strategy discussion prompts in the Discussion Points below. \\n\\n**8. Round 5 - Repeat interpolation strategy.**\\n\\n* Students repeat Step 6 with the new Interpolation Strategy informing their decision. At the end of this round, there should be 40 squares covered on the chart. \\n\\n**9. Interpolate to Complete the Image.**\\n\\n* As a class, fill in the remaining nine squares on the charts with the agreed upon colored sticky notes. Do not run the simulation to check. At this time, the three charts should be completely filled in.\",\"content2\":\"\",\"mediaType\":\"none\",\"mediaCaption\":\"Last, First. \\\"Title of Work.\\\" Year created. Site Title [OR] Publisher. 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If students struggle with coming up with an answer, remind them how they tend to see temperature on common weather forecasts.\\n\\n###Data Abstraction (simplifying or generalizing data to analyze it for trends). \\nPossible prompts for the discussion:\\n\\n* Do you see any patterns with the color coding that you did not see before we added the post-it notes?\\n\\n* How does adding the color help? (It helps your perception: your eye is more easily able to see clusters and trends.)\\n\\n* Is there any disadvantage to using color instead of the numbers? (Yes, we lose detail. We can no longer tell the difference between a cell that was 44\u00b0 and one that was 46\u00b0.)\\n\\n###Interpolation Strategy\\nLead a class discussion reflecting on which guesses were right, wrong, and close. Possible prompts:\\n\\n* Which groups got their predictions right? What was their strategy?\\n\\n* Which groups got their predictions wrong? How close were they? 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Scientists have many methods for constructing unknown data between known data points. This is called data\u0026nbsp;interpolation.\u003C/p\u003E\n\u003Cp\u003EThere are many different methods to interpolate data. Let\u0026rsquo;s look at the three\u0026nbsp;interpolation\u0026nbsp;methods used to make these maps.\u003C/p\u003E\n\u003Cp\u003E\u003Cimg class=\"\" src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/images/AKABCinterpolationtemp.jpg\" alt=\"\" width=\"484\" height=\"383\" /\u003E\u003C/p\u003E\n\u003Cp\u003E\u003Cstrong\u003ENearest Neighbor Interpolation\u003C/strong\u003E\u003C/p\u003E\n\u003Cp\u003EFor Square A, you may have guessed 54\u0026deg;F degrees or something very close to that. This is the simplest\u0026nbsp;interpolation\u0026nbsp;method. It is called\u0026nbsp;\u003Cstrong\u003ENearest Neighbor\u003C/strong\u003E. With this method, you find the nearest\u0026nbsp;weather station to the unknown point and assume it has a similar temperature.\u003C/p\u003E\n\u003Cp\u003E\u003Cbr /\u003E\u003Cstrong\u003ELinear Interpolation\u003C/strong\u003E\u003C/p\u003E\n\u003Cp\u003EFor Square B, you may have guessed between 38\u0026deg;F and 50\u0026deg;F, but closer to 50\u0026deg;F. Since this square is between two known temperatures, the unknown temperature is probably between 38\u0026deg;F and 50\u0026deg;F. To be even closer, you can think of it like a number line with temperature in each square increasing by four degrees.\u003C/p\u003E\n\u003Cp\u003E\u003Cimg class=\"\" src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/images/AKlinearinterpolation.jpg\" alt=\"\" width=\"310\" height=\"151\" /\u003E\u003C/p\u003E\n\u003Cp\u003EThis method is called\u003Cstrong\u003E Linear Interpolation\u003C/strong\u003E.\u003C/p\u003E\n\u003Cp\u003E\u003Cbr /\u003E\u003Cstrong\u003EWeighted Average Interpolation\u003C/strong\u003E\u003C/p\u003E\n\u003Cp\u003EFor Square C, the square is between other squares at 30\u0026deg;F, 48\u0026deg;F, and 50\u0026deg;F. You could average the three numbers and get approximately 43\u0026deg;F. Or you could try to be even more precise. The unknown square is closer to the 50\u0026deg;F square than to the others. Therefore, you can estimate the temperature to be a little higher than the average (maybe 45\u0026deg;F or 46\u0026deg;F). 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"thumbnail_url": "https://learn-resources.concord.org/images/stem-resources/icons/pc-lesson3.png", + "time_to_complete": null, + "version": 1, + "theme_name": "Precipitating Change", + "pages": [{ + "additional_sections": {}, + "embeddable_display_mode": "stacked", + "id": 143592, + "is_completion": false, + "is_hidden": false, + "layout": "l-full-width", + "name": "Page 1", + "position": 1, + "show_header": true, + "show_info_assessment": true, + "show_interactive": false, + "show_sidebar": false, + "sidebar": null, + "sidebar_title": "Did you know?", + "toggle_info_assessment": false, + "embeddables": [{ + "embeddable": { + "content": "\u003Cp\u003EWhich Estimates Should We Trust?\u003C/p\u003E\r\n\u003Cp\u003EMs. Tevuk\u0026rsquo;s class is looking at a temperature map with five data points taken from weather station observations. All five weather station observations were made at the same time on the same day. The map also shows some temperatures that were estimated using the weather station observation data (estimated temperatures are in parentheses).\u003C/p\u003E\r\n\u003Cp\u003E\u003Cimg style=\"display: block; margin-left: auto; margin-right: auto;\" src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/L3AssessmentProbeMap.png\" width=\"555\" height=\"444\" /\u003E\u003C/p\u003E\r\n\u003Cp\u003EMs. Tevuk asks the students which of the estimated temperatures they are LEAST CERTAIN (MOST UNSURE) about.\u003C/p\u003E\r\n\u003Cp\u003EHere are the students\u0026rsquo; ideas. (Each student\u0026rsquo;s estimated temperature choice is in \u003Cstrong\u003Ebold\u003C/strong\u003E to make it easier to find.)\u003C/p\u003E\r\n\u003Ctable cellpadding=\"30\"\u003E\r\n\u003Ctbody\u003E\r\n\u003Ctr\u003E\r\n\u003Cth colspan=\"2\"\u003E\u003Cstrong\u003EAlex\u003C/strong\u003E\u003C/th\u003E\r\n\u003Cth colspan=\"2\"\u003E\u003Cstrong\u003EDelana\u003C/strong\u003E\u003C/th\u003E\r\n\u003C/tr\u003E\r\n\u003Ctr\u003E\r\n\u003Ctd width=\"88\"\u003E\u003Cimg src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/Alex1-1.png\" width=\"80\" height=\"100\" align=\"center\" hspace=\"10\" vspace=\"10\" /\u003E\u003C/td\u003E\r\n\u003Ctd style=\"padding: 10px;\" width=\"350\"\u003E\r\n\u003Cp\u003EI\u0026rsquo;m least certain about the estimate of \u003Cstrong\u003E53\u02da\u003C/strong\u003E because it\u0026rsquo;s furthest outside of the temperatures that were actually measured at a weather station.\u003C/p\u003E\r\n\u003Cp\u003E\u003Cimg style=\"display: block; margin-left: auto; margin-right: auto;\" src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/Lesson3AlexsChoice.png\" width=\"223\" height=\"200\" /\u003E\u003C/p\u003E\r\n\u003C/td\u003E\r\n\u003Ctd width=\"88\"\u003E\u003Cimg src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/Delana2.png\" width=\"80\" height=\"100\" align=\"center\" hspace=\"10\" vspace=\"10\" /\u003E\u003C/td\u003E\r\n\u003Ctd style=\"padding: 10px;\" width=\"350\"\u003E\r\n\u003Cp\u003EI\u0026rsquo;m least certain about the estimate of \u003Cstrong\u003E43\u02da\u003C/strong\u003E because it\u0026rsquo;s far away from any temperatures measured at a weather station.\u0026nbsp;\u003C/p\u003E\r\n\u003Cp\u003E\u003Cimg style=\"display: block; margin-left: auto; margin-right: auto;\" src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/Lesson3DelanasChoice.png\" width=\"222\" height=\"200\" /\u003E\u003C/p\u003E\r\n\u003C/td\u003E\r\n\u003C/tr\u003E\r\n\u003C/tbody\u003E\r\n\u003Ctbody\u003E\r\n\u003Ctr\u003E\r\n\u003Cth colspan=\"2\"\u003E\u003Cstrong\u003EKalin\u003C/strong\u003E\u003C/th\u003E\r\n\u003Cth colspan=\"2\"\u003E\u003Cstrong\u003ESage\u003C/strong\u003E\u003C/th\u003E\r\n\u003C/tr\u003E\r\n\u003Ctr\u003E\r\n\u003Ctd width=\"88\"\u003E\r\n\u003Cp\u003E\u003Cimg src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/Kalin3.png\" width=\"80\" height=\"100\" align=\"center\" hspace=\"10\" vspace=\"10\" /\u003E\u003C/p\u003E\r\n\u003C/td\u003E\r\n\u003Ctd style=\"padding: 10px;\" width=\"350\"\u003E\r\n\u003Cp\u003EI\u0026rsquo;m least certain about the estimate of \u003Cstrong\u003E39\u02da\u003C/strong\u003E because there aren\u0026rsquo;t any other estimated temperatures near the 39\u02da estimate.\u003C/p\u003E\r\n\u003Cp\u003E\u003Cimg style=\"display: block; margin-left: auto; margin-right: auto;\" src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/Lesson3KalinsChoice.png\" width=\"230\" height=\"204\" /\u003E\u003C/p\u003E\r\n\u003C/td\u003E\r\n\u003Ctd width=\"88\"\u003E\r\n\u003Cp\u003E\u003Cimg src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/Lesson3SageAvatar.png\" width=\"80\" height=\"100\" align=\"center\" hspace=\"8\" vspace=\"8\" /\u003E\u003C/p\u003E\r\n\u003C/td\u003E\r\n\u003Ctd style=\"padding: 10px;\" width=\"350\"\u003E\r\n\u003Cp\u003EI\u0026rsquo;m least certain about the estimate of \u003Cstrong\u003E37\u02da\u003C/strong\u003E because weather usually moves from west to east, so I\u0026rsquo;m unsure about estimates on the west side of the map.\u003C/p\u003E\r\n\u003Cp\u003E\u003Cimg class=\"\" style=\"display: block; margin-left: auto; margin-right: auto;\" src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/Lesson3SagesChoice.png\" alt=\"\" width=\"230\" height=\"206\" /\u003E\u003C/p\u003E\r\n\u003C/td\u003E\r\n\u003C/tr\u003E\r\n\u003C/tbody\u003E\r\n\u003C/table\u003E", + "is_callout": false, + "is_full_width": true, + "is_hidden": false, + "name": "", + "type": "Embeddable::Xhtml", + "ref_id": "147898-Embeddable::Xhtml" + }, + "section": "header_block" + }, { + "embeddable": { + "plugin": { + "description": null, + "author_data": "{\"tipType\":\"windowShade\",\"windowShade\":{\"windowShadeType\":\"teacherTip\",\"layout\":\"mediaLeft\",\"initialOpenState\":true,\"content\":\"###Pre-Assessment Implementation\\n*Lesson 3, Opening: Which Estimates Should We Trust? Pre-Assessment*\\nDuring the pre-assessment, each student will view the probe and make an individual choice. The request for explanation will only be on the post-assessment implementation. After students make an individual choice for the pre-assessment, you can lead discussion including, for example, a pair/share opportunity and/or full class discussion. \\n\\nAt this time, encourage students to share and discuss their ideas and reasons without indicating that any one answer is better or worse. Let the students know that they should keep thinking about this question and that the class will return to it at the end of the lesson.\",\"content2\":\"\",\"mediaType\":\"none\",\"mediaCaption\":\"Last, First. \\\"Title of Work.\\\" Year created. Site Title [OR] Publisher. 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Review the information below and think about ways to scaffold students toward developing knowledge and practice as appropriate for their classes. Also, we recommend that during the first implementation of the probe, that you scaffold students to focus on their own ideas about this problem, rather than on vocabulary terms such as **interpolation** and **extrapolation**. By discussing the different options, students can engage in productive talk related to these data sense making and computational thinking concepts without necessarily using technical terminology. During the ensuing lesson and the second implementation of the probe, the terms **interpolation** and **extrapolation** can be used, if appropriate.\\n\\nThis assessment probe is designed to assess and scaffold students in thinking and talking about **interpolation** and **extrapolation**. **Interpolation** means finding an estimation of a value between ones that are known or tabulated using surrounding points or values (that is, estimating an unknown value based on surrounding information). **Extrapolation** means finding or concluding something by assuming that existing trends will continue, or a current method will remain applicable beyond existing known values (that is, following a pattern beyond the known data points). \\n\\nInterpolation and extrapolation are similar, but because extrapolation involves estimating beyond the known data points, this approach is subject to greater uncertainty and has a higher risk of producing more imprecise or potentially even meaningless results compared with interpolation. \\n\\nThe assessment is situated in the unit context to provide an opportunity for students to make sense about extrapolation and interpolation of a specific, tangible weather problem (i.e., temperatures in a two-dimensional area at one point in time). While extrapolation is associated with higher levels of uncertainty, it\u2019s also sometimes necessary. This is true, for example, for forecasting (prediction). Prediction of future weather will always involve extrapolation (i.e., extending the pattern of weather data into the future given that observed data cannot be obtained for the future until time passes and the future becomes the present!). Uncertainty associated with extrapolation is why there\u2019s always some level of uncertainty in weather forecasts. Basically, this is why weather forecasts are sometimes wrong. There is always some uncertainty associated with interpolation too, though generally it is less so than with extrapolation.\\n\\nThis assessment also relates to **pattern recognition** and **data aggregation**. **Pattern recognition** involves identifying patterns and trends within and across groups of data/information as seen in the observable world. Students employ **pattern recognition** in this assessment as they view the distribution of temperatures in the map grid and make sense of patterns and trends across the grid (in both observed and estimated values) to think about the question. **Data aggregation** involves determining the appropriate data to collect or generate in order to study the identified phenomenon. Students should consider more and less appropriate ways to aggregate data in the map grid as they figure out which response they think is best. For example, students should be think about which cells in the grid have enough data to estimate temperatures for from collected data, and which temperatures might be problematic to estimate \u2013 meaning we might need to collect more data to generate a good estimate for temperatures in those cells. \\n\\nWhile one of the responses makes the most sense from a practical standpoint for this particular problem, there\u2019s no absolutely correct answer. Using an indefinite problem provides space for students to think and talk about how much confidence we can have in different interpolated and extrapolated values. \",\"content2\":\"\",\"mediaType\":\"none\",\"mediaCaption\":\"Last, First. \\\"Title of Work.\\\" Year created. Site Title [OR] Publisher. 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The values in parentheses are all estimated, so having other estimated values near the value that Kalin chooses would not necessarily make us more confident about Kalin\u2019s choice. If there were additional observed values near the cell that Kalin chose, that would help boost our confidence. We can feel more confident about interpolated values for data the more observed data values we have for a given area. \\n\\nStudents who choose 39\u00b0 as the most uncertain value could benefit from discussions about the difference between observed data points and estimated data points. Students can think about which types of values are more trustworthy and why (e.g., local conditions like elevation changes or water bodies could affect local values, making estimated temperatures less reliable than observed values). Students may come up with potential problems with observed values too (e.g., a faulty thermometer), which is fine. \\n\\n\\n###Middle Level\\n\u2022\\t**Sage\u2019s response (37\u00b0)** suggests that she may be thinking beyond interpolation to also consider weather processes (e.g., movement of air masses across Alaska). While that shows some good thinking, the values on the assessment probe map all represent one point in time, so we would be less concerned about air movement over time and issues like east versus west in Alaska for this particular problem. \\n\\nLater in the unit, students who chose 37\u00b0 may benefit from discussions that emphasize the difference between interpolating data from known values at one point in time versus doing things like making predictions into the future across a two-dimensional area based on known information such as wind speed, wind direction, etc. \\n\\n\\n###Upper Middle Level\\n\u2022\\t**Delana\u2019s response (43\u00b0)** suggests that she understands that we can be more confident about estimates when we have observed values nearby. We should be less confident about interpolated data (there are many estimated values near the 43\u00b0 cell) nearby in comparison with nearby observed data.\\n\\nWhile students who choose Delana\u2019s response have useful ideas about confidence and interpolation, they could also benefit from some scaffolding to reason more deeply about interpolation versus extrapolation. Moving beyond the area of known data points (i.e., extrapolation) is generally associated with higher uncertainty compared with interpolation. For example, if there is a weather front just to the east of the 46\u00b0 and 51\u00b0 measured temperature values, the 53\u00b0 estimated value could be quite different from what an actual observed measurement taken at that location would be. \\n\\n\\n###More Formal Idea\\n\u2022\\t**Alex\u2019s response (53\u00b0)** and rationale recognizes the problems associated with extrapolation beyond known data points. 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All five weather station observations were made at the same time on the same day. The map also shows some temperatures that were estimated using the weather station observation data (estimated temperatures are in parentheses).\u003C/p\u003E\r\n\u003Cp\u003E\u003Cimg style=\"display: block; margin-left: auto; margin-right: auto;\" src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/L3AssessmentProbeMap.png\" width=\"555\" height=\"444\" /\u003E\u003C/p\u003E\r\n\u003Cp\u003EMs. Tevuk asks the students which of the estimated temperatures they are LEAST CERTAIN (MOST UNSURE) about.\u003C/p\u003E\r\n\u003Cp\u003EHere are the students\u0026rsquo; ideas. (Each student\u0026rsquo;s estimated temperature choice is in \u003Cstrong\u003Ebold\u003C/strong\u003E to make it easier to find.)\u003C/p\u003E\r\n\u003Ctable cellpadding=\"30\"\u003E\r\n\u003Ctbody\u003E\r\n\u003Ctr\u003E\r\n\u003Cth colspan=\"2\"\u003E\u003Cstrong\u003EAlex\u003C/strong\u003E\u003C/th\u003E\r\n\u003Cth colspan=\"2\"\u003E\u003Cstrong\u003EDelana\u003C/strong\u003E\u003C/th\u003E\r\n\u003C/tr\u003E\r\n\u003Ctr\u003E\r\n\u003Ctd width=\"88\"\u003E\u003Cimg src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/Alex1-1.png\" width=\"80\" height=\"100\" align=\"center\" hspace=\"10\" vspace=\"10\" /\u003E\u003C/td\u003E\r\n\u003Ctd style=\"padding: 10px;\" width=\"350\"\u003E\r\n\u003Cp\u003EI\u0026rsquo;m least certain about the estimate of \u003Cstrong\u003E53\u02da\u003C/strong\u003E because it\u0026rsquo;s furthest outside of the temperatures that were actually measured at a weather station.\u003C/p\u003E\r\n\u003Cp\u003E\u003Cimg style=\"display: block; margin-left: auto; margin-right: auto;\" src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/Lesson3AlexsChoice.png\" width=\"223\" height=\"200\" /\u003E\u003C/p\u003E\r\n\u003C/td\u003E\r\n\u003Ctd width=\"88\"\u003E\u003Cimg src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/Delana2.png\" width=\"80\" height=\"100\" align=\"center\" hspace=\"10\" vspace=\"10\" /\u003E\u003C/td\u003E\r\n\u003Ctd style=\"padding: 10px;\" width=\"350\"\u003E\r\n\u003Cp\u003EI\u0026rsquo;m least certain about the estimate of \u003Cstrong\u003E43\u02da\u003C/strong\u003E because it\u0026rsquo;s far away from any temperatures measured at a weather station.\u0026nbsp;\u003C/p\u003E\r\n\u003Cp\u003E\u003Cimg style=\"display: block; margin-left: auto; margin-right: auto;\" src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/Lesson3DelanasChoice.png\" width=\"222\" height=\"200\" /\u003E\u003C/p\u003E\r\n\u003C/td\u003E\r\n\u003C/tr\u003E\r\n\u003C/tbody\u003E\r\n\u003Ctbody\u003E\r\n\u003Ctr\u003E\r\n\u003Cth colspan=\"2\"\u003E\u003Cstrong\u003EKalin\u003C/strong\u003E\u003C/th\u003E\r\n\u003Cth colspan=\"2\"\u003E\u003Cstrong\u003ESage\u003C/strong\u003E\u003C/th\u003E\r\n\u003C/tr\u003E\r\n\u003Ctr\u003E\r\n\u003Ctd width=\"88\"\u003E\r\n\u003Cp\u003E\u003Cimg src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/Kalin3.png\" width=\"80\" height=\"100\" align=\"center\" hspace=\"10\" vspace=\"10\" /\u003E\u003C/p\u003E\r\n\u003C/td\u003E\r\n\u003Ctd style=\"padding: 10px;\" width=\"350\"\u003E\r\n\u003Cp\u003EI\u0026rsquo;m least certain about the estimate of \u003Cstrong\u003E39\u02da\u003C/strong\u003E because there aren\u0026rsquo;t any other estimated temperatures near the 39\u02da estimate.\u003C/p\u003E\r\n\u003Cp\u003E\u003Cimg style=\"display: block; margin-left: auto; margin-right: auto;\" src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/Lesson3KalinsChoice.png\" width=\"230\" height=\"204\" /\u003E\u003C/p\u003E\r\n\u003C/td\u003E\r\n\u003Ctd width=\"88\"\u003E\r\n\u003Cp\u003E\u003Cimg src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/Lesson3SageAvatar.png\" width=\"80\" height=\"100\" align=\"center\" hspace=\"8\" vspace=\"8\" /\u003E\u003C/p\u003E\r\n\u003C/td\u003E\r\n\u003Ctd style=\"padding: 10px;\" width=\"350\"\u003E\r\n\u003Cp\u003EI\u0026rsquo;m least certain about the estimate of \u003Cstrong\u003E37\u02da\u003C/strong\u003E because weather usually moves from west to east, so I\u0026rsquo;m unsure about estimates on the west side of the map.\u003C/p\u003E\r\n\u003Cp\u003E\u003Cimg class=\"\" style=\"display: block; margin-left: auto; margin-right: auto;\" src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/Lesson3SagesChoice.png\" alt=\"\" width=\"230\" height=\"206\" /\u003E\u003C/p\u003E\r\n\u003C/td\u003E\r\n\u003C/tr\u003E\r\n\u003C/tbody\u003E\r\n\u003C/table\u003E", + "is_callout": false, + "is_full_width": true, + "is_hidden": false, + "name": "", + "type": "Embeddable::Xhtml", + "ref_id": "147895-Embeddable::Xhtml" + }, + "section": "header_block" + }, { + "embeddable": { + "plugin": { + "description": null, + "author_data": "{\"tipType\":\"windowShade\",\"windowShade\":{\"windowShadeType\":\"teacherTip\",\"layout\":\"mediaLeft\",\"initialOpenState\":true,\"content\":\"###Pre-Assessment Implementation\\n*Lesson 3, Opening: Which Estimates Should We Trust? Pre-Assessment*\\nDuring the pre-assessment, each student will view the probe and make an individual choice. The request for explanation will only be on the post-assessment implementation. After students make an individual choice for the pre-assessment, you can lead discussion including, for example, a pair/share opportunity and/or full class discussion. \\n\\nAt this time, encourage students to share and discuss their ideas and reasons without indicating that any one answer is better or worse. Let the students know that they should keep thinking about this question and that the class will return to it at the end of the lesson.\",\"content2\":\"\",\"mediaType\":\"none\",\"mediaCaption\":\"Last, First. \\\"Title of Work.\\\" Year created. Site Title [OR] Publisher. Gallery [OR] Location. http://www.url.com.\",\"mediaURL\":\"\"}}", + "approved_script_label": "teacherEditionTips", + "component_label": "windowShade", + "approved_script": { + "name": "Teacher Edition", + "url": "https://teacher-edition-tips-plugin.concord.org/version/v3.6.0/plugin.js", + "label": "teacherEditionTips", + "description": "This plugin provides Teacher Edition components", + "version": 3, + "json_url": "https://teacher-edition-tips-plugin.concord.org/version/v3.6.0/manifest.json", + "authoring_metadata": "{\"components\":[{\"label\":\"windowShade\",\"name\":\"Window Shades\",\"scope\":\"embeddable\",\"guiAuthoring\":true},{\"label\":\"sideTip\",\"name\":\"Side Tips\",\"scope\":\"embeddable\",\"guiAuthoring\":true},{\"label\":\"questionWrapper\",\"name\":\"Question Wrapper\",\"scope\":\"embeddable-decoration\",\"decorates\":[\"Embeddable::MultipleChoice\",\"Embeddable::OpenResponse\",\"Embeddable::ImageQuestion\",\"ManagedInteractive\",\"MwInteractive\",\"ImageInteractive\",\"VideoInteractive\"],\"guiAuthoring\":true,\"guiPreview\":true}]}" + } + }, + "is_hidden": false, + "is_full_width": true, + "type": "Embeddable::EmbeddablePlugin", + "ref_id": "10237-Embeddable::EmbeddablePlugin" + }, + "section": null + }, { + "embeddable": { + "plugin": { + "description": null, + "author_data": "{\"tipType\":\"windowShade\",\"windowShade\":{\"windowShadeType\":\"theoryAndBackground\",\"layout\":\"mediaLeft\",\"initialOpenState\":true,\"content\":\"###Computational Thinking Concepts and Practices:\\n- Interpolation\\n- Extrapolation\\n- Pattern Recognition\\n- Data Aggregation\\n\\n###What is the Purpose of this Assessment Probe?\\nThe following information provides background for teachers and is not necessarily representative of the learning goals for everything students should understand. Review the information below and think about ways to scaffold students toward developing knowledge and practice as appropriate for their classes. Also, we recommend that during the first implementation of the probe, that you scaffold students to focus on their own ideas about this problem, rather than on vocabulary terms such as **interpolation** and **extrapolation**. By discussing the different options, students can engage in productive talk related to these data sense making and computational thinking concepts without necessarily using technical terminology. During the ensuing lesson and the second implementation of the probe, the terms **interpolation** and **extrapolation** can be used, if appropriate.\\n\\nThis assessment probe is designed to assess and scaffold students in thinking and talking about **interpolation** and **extrapolation**. **Interpolation** means finding an estimation of a value between ones that are known or tabulated using surrounding points or values (that is, estimating an unknown value based on surrounding information). **Extrapolation** means finding or concluding something by assuming that existing trends will continue, or a current method will remain applicable beyond existing known values (that is, following a pattern beyond the known data points). \\n\\nInterpolation and extrapolation are similar, but because extrapolation involves estimating beyond the known data points, this approach is subject to greater uncertainty and has a higher risk of producing more imprecise or potentially even meaningless results compared with interpolation. \\n\\nThe assessment is situated in the unit context to provide an opportunity for students to make sense about extrapolation and interpolation of a specific, tangible weather problem (i.e., temperatures in a two-dimensional area at one point in time). While extrapolation is associated with higher levels of uncertainty, it\u2019s also sometimes necessary. This is true, for example, for forecasting (prediction). Prediction of future weather will always involve extrapolation (i.e., extending the pattern of weather data into the future given that observed data cannot be obtained for the future until time passes and the future becomes the present!). Uncertainty associated with extrapolation is why there\u2019s always some level of uncertainty in weather forecasts. Basically, this is why weather forecasts are sometimes wrong. There is always some uncertainty associated with interpolation too, though generally it is less so than with extrapolation.\\n\\nThis assessment also relates to **pattern recognition** and **data aggregation**. **Pattern recognition** involves identifying patterns and trends within and across groups of data/information as seen in the observable world. Students employ **pattern recognition** in this assessment as they view the distribution of temperatures in the map grid and make sense of patterns and trends across the grid (in both observed and estimated values) to think about the question. **Data aggregation** involves determining the appropriate data to collect or generate in order to study the identified phenomenon. Students should consider more and less appropriate ways to aggregate data in the map grid as they figure out which response they think is best. For example, students should be think about which cells in the grid have enough data to estimate temperatures for from collected data, and which temperatures might be problematic to estimate \u2013 meaning we might need to collect more data to generate a good estimate for temperatures in those cells. \\n\\nWhile one of the responses makes the most sense from a practical standpoint for this particular problem, there\u2019s no absolutely correct answer. Using an indefinite problem provides space for students to think and talk about how much confidence we can have in different interpolated and extrapolated values. \",\"content2\":\"\",\"mediaType\":\"none\",\"mediaCaption\":\"Last, First. \\\"Title of Work.\\\" Year created. Site Title [OR] Publisher. 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The values in parentheses are all estimated, so having other estimated values near the value that Kalin chooses would not necessarily make us more confident about Kalin\u2019s choice. If there were additional observed values near the cell that Kalin chose, that would help boost our confidence. We can feel more confident about interpolated values for data the more observed data values we have for a given area. \\n\\nStudents who choose 39\u00b0 as the most uncertain value could benefit from discussions about the difference between observed data points and estimated data points. Students can think about which types of values are more trustworthy and why (e.g., local conditions like elevation changes or water bodies could affect local values, making estimated temperatures less reliable than observed values). Students may come up with potential problems with observed values too (e.g., a faulty thermometer), which is fine. \\n\\n\\n###Middle Level\\n\u2022\\t**Sage\u2019s response (37\u00b0)** suggests that she may be thinking beyond interpolation to also consider weather processes (e.g., movement of air masses across Alaska). While that shows some good thinking, the values on the assessment probe map all represent one point in time, so we would be less concerned about air movement over time and issues like east versus west in Alaska for this particular problem. \\n\\nLater in the unit, students who chose 37\u00b0 may benefit from discussions that emphasize the difference between interpolating data from known values at one point in time versus doing things like making predictions into the future across a two-dimensional area based on known information such as wind speed, wind direction, etc. \\n\\n\\n###Upper Middle Level\\n\u2022\\t**Delana\u2019s response (43\u00b0)** suggests that she understands that we can be more confident about estimates when we have observed values nearby. We should be less confident about interpolated data (there are many estimated values near the 43\u00b0 cell) nearby in comparison with nearby observed data.\\n\\nWhile students who choose Delana\u2019s response have useful ideas about confidence and interpolation, they could also benefit from some scaffolding to reason more deeply about interpolation versus extrapolation. Moving beyond the area of known data points (i.e., extrapolation) is generally associated with higher uncertainty compared with interpolation. For example, if there is a weather front just to the east of the 46\u00b0 and 51\u00b0 measured temperature values, the 53\u00b0 estimated value could be quite different from what an actual observed measurement taken at that location would be. \\n\\n\\n###More Formal Idea\\n\u2022\\t**Alex\u2019s response (53\u00b0)** and rationale recognizes the problems associated with extrapolation beyond known data points. 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She will discuss how air moisture plays an important part in forming precipitation.\u003C/p\u003E", + "is_callout": true, + "is_full_width": true, + "is_hidden": false, + "name": "", + "type": "Embeddable::Xhtml", + "ref_id": "148013-Embeddable::Xhtml" + }, + "section": "header_block" + }, { + "embeddable": { + "name": "", + "url_fragment": null, + "authored_state": "{\"version\":1,\"questionType\":\"iframe_interactive\",\"videoUrl\":\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/Captioned_Videos/JackieLesson3_88_Captioned.mp4\",\"poster\":\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/Captioned_Videos/Posters/Poster_L3_Video.png\"}", + "is_hidden": false, + "is_full_width": true, + "show_in_featured_question_report": true, + "inherit_aspect_ratio_method": true, + "custom_aspect_ratio_method": null, + "inherit_native_width": true, + "custom_native_width": 576, + "inherit_native_height": true, + "custom_native_height": 435, + "inherit_click_to_play": true, + "custom_click_to_play": false, + "inherit_full_window": true, + "custom_full_window": false, + "inherit_click_to_play_prompt": true, + "custom_click_to_play_prompt": null, + "inherit_image_url": true, + "custom_image_url": null, + "library_interactive": { + "hash": "34e1a2a39c058da8ff4ffe5a09ad14af337c4a01", + "data": { + "aspect_ratio_method": "DEFAULT", + "authoring_guidance": "", + "base_url": "https://models-resources.concord.org/question-interactives/version/v1.1.0/video-player/", + "click_to_play": false, + "click_to_play_prompt": null, + "description": "This video player will not have the blue header bar above the interactive.\r\nIt does not save the students position in the video. \r\nIt will not show up in the teacher report.", + "enable_learner_state": false, + "full_window": false, + "has_report_url": false, + "image_url": null, + "name": "Video Player", + "native_height": 435, + "native_width": 576, + "no_snapshots": false, + "show_delete_data_button": false, + "thumbnail_url": "", + "customizable": false, + "authorable": true + } + }, + "type": "ManagedInteractive", + "ref_id": "1765-ManagedInteractive", + "linked_interactives": [] + }, + "section": "header_block" + }] + }, { + "additional_sections": {}, + "embeddable_display_mode": "stacked", + "id": 143588, + "is_completion": false, + "is_hidden": false, + "layout": "l-full-width", + "name": "Opening", + "position": 2, + "show_header": true, + "show_info_assessment": true, + "show_interactive": false, + "show_sidebar": false, + "sidebar": null, + "sidebar_title": "Did you know?", + "toggle_info_assessment": false, + "embeddables": [{ + "embeddable": { + "content": "\u003Cp\u003EHave you ever been caught without your parka or boots when you needed them? Predicting rain or snow\u0026nbsp;is a special challenge for weather scientists. Watch the video below to learn more about forecasting the weather in Alaska.\u003C/p\u003E\r\n\u003Cp\u003EAs weather scientists, you will continue to explore weather maps. Now, you will add two additional pieces of information to each square: precipitation (a symbol) and air moisture content (a number). 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00000000..f30b308c --- /dev/null +++ b/src/public/offline-activities/precipitating-change-v2/lesson-4-post.json @@ -0,0 +1,248 @@ +{ + "description": "\u003Cp\u003EBuilding Rules: Where does it rain?\u003C/p\u003E", + "editor_mode": 0, + "layout": 0, + "name": "Alaska 2021 - Lesson 4: Post-thoughts - What Do You Think?", + "notes": "", + "project_id": 25, + "related": "", + "runtime": "Activity Player", + "show_submit_button": true, + "student_report_enabled": true, + "thumbnail_url": "https://learn-resources.concord.org/images/stem-resources/icons/pc-lesson3.png", + "time_to_complete": null, + "version": 1, + "theme_name": "Precipitating Change", + "pages": [{ + "additional_sections": {}, + "embeddable_display_mode": "stacked", + "id": 143598, + "is_completion": false, + "is_hidden": false, + "layout": "l-full-width", + "name": "Page 1", + "position": 1, + "show_header": true, + "show_info_assessment": true, + "show_interactive": false, + "show_sidebar": false, + "sidebar": null, + "sidebar_title": "Did you know?", + "toggle_info_assessment": false, + "embeddables": [{ + "embeddable": { + "content": "\u003Cp\u003E\u003Cstrong\u003EWhat Are the Rules for Fronts and Precipitation?\u003C/strong\u003E\u003C/p\u003E\r\n\u003Cp\u003EMs. Tevuk\u0026rsquo;s students need to write a rule for their computer model to predict areas of precipitation on a map showing weather fronts. They have different ideas for what the rule should be.\u003C/p\u003E\r\n\u003Cp\u003EHere are the students\u0026rsquo; ideas: The rule should be that precipitation happens\u0026hellip;\u003C/p\u003E\r\n\u003Ctable cellpadding=\"30\"\u003E\r\n\u003Ctbody\u003E\r\n\u003Ctr\u003E\r\n\u003Cth colspan=\"2\"\u003E\u003Cstrong\u003EAlex\u003C/strong\u003E\u003C/th\u003E\r\n\u003Cth colspan=\"2\"\u003E\u003Cstrong\u003EDelana\u003C/strong\u003E\u003C/th\u003E\r\n\u003C/tr\u003E\r\n\u003Ctr\u003E\r\n\u003Ctd width=\"88\"\u003E\u003Cimg src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/Alex4.png\" width=\"72\" height=\"90\" align=\"center\" hspace=\"10\" vspace=\"10\" /\u003E\u003C/td\u003E\r\n\u003Ctd style=\"padding: 10px;\" width=\"350\"\u003E\u003Cstrong\u003Ewith a warm front coming in\u003C/strong\u003E because warm air moves in and mixes with cold air, which leads to precipitation. You don\u0026rsquo;t get precipitation with a cold front because cold air is dry.\u003C/td\u003E\r\n\u003Ctd width=\"88\"\u003E\u003Cimg src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/Delana4.png\" width=\"70\" height=\"90\" align=\"center\" hspace=\"10\" vspace=\"10\" /\u003E\u003C/td\u003E\r\n\u003Ctd style=\"padding: 10px;\" width=\"350\"\u003E\u003Cstrong\u003Ewith both cold fronts and warm fronts coming in\u003C/strong\u003E because in both cases warm air and cold air meet, leading to condensation and precipitation.\u003C/td\u003E\r\n\u003C/tr\u003E\r\n\u003C/tbody\u003E\r\n\u003Ctbody\u003E\r\n\u003Ctr\u003E\r\n\u003Cth colspan=\"2\"\u003E\u003Cstrong\u003EKalin\u003C/strong\u003E\u003C/th\u003E\r\n\u003Cth colspan=\"2\"\u003E\u003Cstrong\u003ESage\u003C/strong\u003E\u003C/th\u003E\r\n\u003C/tr\u003E\r\n\u003Ctr\u003E\r\n\u003Ctd width=\"88\"\u003E\r\n\u003Cp\u003E\u003Cimg src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/Kalin6.png\" width=\"72\" height=\"90\" align=\"center\" hspace=\"10\" vspace=\"10\" /\u003E\u003C/p\u003E\r\n\u003C/td\u003E\r\n\u003Ctd style=\"padding: 10px;\" width=\"350\"\u003E\u003Cstrong\u003Ewith a cold front coming in\u003C/strong\u003E because it\u0026rsquo;s usually rainy or snowy when it\u0026rsquo;s cold out. You don\u0026rsquo;t get precipitation with a warm front because it\u0026rsquo;s warm when the sun is shining.\u003C/td\u003E\r\n\u003Ctd width=\"88\"\u003E\r\n\u003Cp\u003E\u003Cimg src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/Sage2.png\" width=\"72\" height=\"90\" align=\"center\" hspace=\"8\" vspace=\"8\" /\u003E\u003C/p\u003E\r\n\u003C/td\u003E\r\n\u003Ctd style=\"padding: 10px;\" width=\"350\"\u003E\u003Cstrong\u003Eafter a cold front has passed by\u003C/strong\u003E because the cold air the front leaves behind is humid, which leads to precipitation.\u003C/td\u003E\r\n\u003C/tr\u003E\r\n\u003C/tbody\u003E\r\n\u003C/table\u003E", + "is_callout": false, + "is_full_width": true, + "is_hidden": false, + "name": "", + "type": "Embeddable::Xhtml", + "ref_id": "147904-Embeddable::Xhtml" + }, + "section": "header_block" + }, { + "embeddable": { + "plugin": { + "description": null, + "author_data": "{\"tipType\":\"windowShade\",\"windowShade\":{\"windowShadeType\":\"teacherTip\",\"layout\":\"mediaLeft\",\"initialOpenState\":true,\"content\":\"###Pre-Assessment Implementation\\n*Lesson 4, Opening: What Are the Rules for Fronts and Precipitation? Pre-Assessment*\\nDuring the pre-assessment, each student will view the probe and make an individual choice. The request for explanation will only be on the post-assessment. After students make an individual choice for the pre-assessment, the teacher can lead discussion including, for example, a pair/share opportunity and/or full class discussion. \\n\\nAt this time, encourage students to share and discuss their ideas and reasons without indicating that any one answer is better or worse. Let the students know that they should keep thinking about this question and that the class will return to it at the end of the next lesson (Lesson 5).\",\"content2\":\"\",\"mediaType\":\"none\",\"mediaCaption\":\"Last, First. \\\"Title of Work.\\\" Year created. Site Title [OR] Publisher. 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We suggest teachers review the information below and think about ways to scaffold students toward developing knowledge and practice as appropriate for their classes. Also, we recommend that during the first implementation of the probe, teachers scaffold students to focus on students\u2019 own ideas about this problem. By discussing the different options, students can engage in productive talk related to the different response patterns, priming them to look for productive patterns to associate with precipitation in the upcoming lessons. \\n\\nDuring the ensuing two lessons and the second implementation of the probe, students should be able to use the data from the virtual storm to identify the patterns of temperature, humidity, and movement that are associated with precipitation.\\n\\nThis assessment probe is designed to assess and scaffold students in thinking and talking about how patterns of data (i.e., temperature, humidity, and air movement) are associated with precipitation in a location. To keep things simple, we only focus on two types of fronts: cold fronts and warm fronts. Both types of fronts can be associated with precipitation. Identifying patterns associated with precipitation is an example of the computational thinking practice of **Pattern Recognition**. Once patterns associated with precipitation are identified, they can be used in conjunction with data to make a **Data-based Prediction**, which is what Ms. Tevuk\u2019s students are trying to do in the scenario for this assessment probe. **Data-based Prediction** involves identifying patterns and trends within and across groups of data/information as seen in the observable world. The patterns of data associated with precipitation in turn can be used to create rules for the computer model in a process of **Rule Abstraction**. **Rule abstraction** involves creating a general statement derived from exploring patterns in data in order to establish rule(s) or principles. In other words, if you know the patterns of variable values associated with precipitation, you can use those patterns to write rules for predicting precipitation.\\n\\nAs a **cold front** moves into an area, the heavier cool air pushes under the lighter warm air. The air behind a cold front is colder and usually drier than the warm air in front. The warm air in front becomes cooler as it is pushed upward by the entering cold air. If the warm air is humid enough, the water vapor it contains will condense into clouds as it rises, and precipitation may fall. \\n\u003Cimg src=\\\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/L4L5AssessmentTeacherGuideImage2.png\\\" width=\\\"850\\\" height=\\\"180\\\" /\u003E\\n \\n\\nWhen a **warm front** moves into an area, warm air moves above a cool air mass. As the warm air rises, it condenses, often forming clouds and precipitation. \\n\u003Cimg src=\\\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/L4L5AssessmentTeacherGuideImage1.png\\\" width=\\\"850\\\" height=\\\"180\\\" /\u003E\\n\\nThe assessment is situated in the unit context to provide an opportunity for students to make sense about patterns when reasoning about air masses, fronts, and precipitation. In this assessment, one of the responses is scientifically correct while the other responses that relate to some informal ideas about weather that students may hold. \",\"content2\":\"\",\"mediaType\":\"none\",\"mediaCaption\":\"Last, First. \\\"Title of Work.\\\" Year created. Site Title [OR] Publisher. 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Students may associate sun with warm, and rain and snow with cold. Based on that experience, they may think that a cold front is connected to precipitation.\\n\\nStudents who choose Kalin\u2019s response could benefit from having experiences that challenge their simple association idea. For example, looking at weather maps that show warmer air often has more moisture in it and colder air is often drier can help these students develop understanding that relationships might not be as simple as they think. Students who choose Kalin\u2019s response may not think about weather as something that happens with matter. Instead, they may just think of weather in terms of the actions of natural \\\"actors\\\" (e.g., the sun makes it warm, the wind makes it cold). These students could use help in learning that air masses are matter (they are made up of molecules and have mass). If we didn\u2019t have air masses made of matter on Earth, then we wouldn\u2019t have weather. You might talk with students about concrete examples that they can extend to think about air masses as entities made of stuff \u2013 for example, they could compare an empty balloon, a balloon filled with warm air, and a balloon filled with cold air. There is very little stuff (matter or molecules of air) in the empty balloon, while there is more stuff (matter) in the balloons filled with warm and cold air.\\n\\n###Middle Level \\n\u2022\\t**Both Alex\u2019s response (precipitation occurs with a warm front coming in)** and **Sage\u2019s response (precipitation occurs after a cold front has passed by an area)** suggest that they are aware that precipitation is associated with bodies of air moving and with the different conditions in those bodies of air (i.e., temperature, levels of humidity). However, both Sage\u2019s and Alex\u2019s ideas include some incorrect patterns that lead to problematic rules. \\n\\n\u2022\\t**Alex** thinks that cold air and warm air mixing causes precipitation. However, warm and cold air masses don\u2019t mix very readily, and it is instead actually warm air rising, expanding, and condensing that generally leads to precipitation. In addition, while Alex knows that cold fronts can be drier than warm fronts, that doesn\u2019t mean that there won\u2019t be any precipitation with cold fronts. Precipitation can occur with a cold front when warm air is pushed up, expands, and condenses.\\n\\nStudents who choose Alex\u2019s response could benefit from working with data to observe the following patterns: (1) precipitation can occur with a cold front and (2) fronts do not necessarily mix.\\n\\n\u2022\\t**Sage** thinks that cold air is humid, which leads to condensation and precipitation. However, warm air masses often have a higher level of humidity compared with cold air masses. It can be confusing that condensation occurs with rising, expanding, and cooling. The unit does not go into this in depth, however. For students who choose Sage\u2019s response, it is probably sufficient here to scaffold experiences with data and virtual storm showing the general pattern of warm air masses having higher levels of humidity than cool air masses.\\n\\n\u2022\\tStudents who choose Alex or Sage\u2019s response can also benefit from discussion and emphasis on the importance of getting the rule right (enough) in order to create a computational model that works. The students working on their weather model will not be able to predict weather with any consistency or accuracy if there is a big problem with the rule (algorithm) they have written into their computer model. \\n\\n###More Formal Idea\\n\u2022\\t**Delana\u2019s response (precipitation occurs with both cold fronts and warm fronts coming in)** is the best answer. Delana\u2019s explanation does not include a more complete mechanistic sequence involving cold air pushing warm air up; warm air rising, expanding, and condensing; and precipitation occurring as a result. This is because the Precipitating Change curriculum simplifies weather phenomena by emphasizing important patterns and de-emphasizing complicated mechanisms. This focus allows the curriculum to scaffold students in connecting observed patterns with rules that can be used to create predictive weather forecasting computer models. 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They have different ideas for what the rule should be.\u003C/p\u003E\r\n\u003Cp\u003EHere are the students\u0026rsquo; ideas: The rule should be that precipitation happens\u0026hellip;\u003C/p\u003E\r\n\u003Ctable cellpadding=\"30\"\u003E\r\n\u003Ctbody\u003E\r\n\u003Ctr\u003E\r\n\u003Cth colspan=\"2\"\u003E\u003Cstrong\u003EAlex\u003C/strong\u003E\u003C/th\u003E\r\n\u003Cth colspan=\"2\"\u003E\u003Cstrong\u003EDelana\u003C/strong\u003E\u003C/th\u003E\r\n\u003C/tr\u003E\r\n\u003Ctr\u003E\r\n\u003Ctd width=\"88\"\u003E\u003Cimg src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/Alex4.png\" width=\"72\" height=\"90\" align=\"center\" hspace=\"10\" vspace=\"10\" /\u003E\u003C/td\u003E\r\n\u003Ctd style=\"padding: 10px;\" width=\"350\"\u003E\u003Cstrong\u003Ewith a warm front coming in\u003C/strong\u003E because warm air moves in and mixes with cold air, which leads to precipitation. You don\u0026rsquo;t get precipitation with a cold front because cold air is dry.\u003C/td\u003E\r\n\u003Ctd width=\"88\"\u003E\u003Cimg src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/Delana4.png\" width=\"70\" height=\"90\" align=\"center\" hspace=\"10\" vspace=\"10\" /\u003E\u003C/td\u003E\r\n\u003Ctd style=\"padding: 10px;\" width=\"350\"\u003E\u003Cstrong\u003Ewith both cold fronts and warm fronts coming in\u003C/strong\u003E because in both cases warm air and cold air meet, leading to condensation and precipitation.\u003C/td\u003E\r\n\u003C/tr\u003E\r\n\u003C/tbody\u003E\r\n\u003Ctbody\u003E\r\n\u003Ctr\u003E\r\n\u003Cth colspan=\"2\"\u003E\u003Cstrong\u003EKalin\u003C/strong\u003E\u003C/th\u003E\r\n\u003Cth colspan=\"2\"\u003E\u003Cstrong\u003ESage\u003C/strong\u003E\u003C/th\u003E\r\n\u003C/tr\u003E\r\n\u003Ctr\u003E\r\n\u003Ctd width=\"88\"\u003E\r\n\u003Cp\u003E\u003Cimg src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/Kalin6.png\" width=\"72\" height=\"90\" align=\"center\" hspace=\"10\" vspace=\"10\" /\u003E\u003C/p\u003E\r\n\u003C/td\u003E\r\n\u003Ctd style=\"padding: 10px;\" width=\"350\"\u003E\u003Cstrong\u003Ewith a cold front coming in\u003C/strong\u003E because it\u0026rsquo;s usually rainy or snowy when it\u0026rsquo;s cold out. You don\u0026rsquo;t get precipitation with a warm front because it\u0026rsquo;s warm when the sun is shining.\u003C/td\u003E\r\n\u003Ctd width=\"88\"\u003E\r\n\u003Cp\u003E\u003Cimg src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/Sage2.png\" width=\"72\" height=\"90\" align=\"center\" hspace=\"8\" vspace=\"8\" /\u003E\u003C/p\u003E\r\n\u003C/td\u003E\r\n\u003Ctd style=\"padding: 10px;\" width=\"350\"\u003E\u003Cstrong\u003Eafter a cold front has passed by\u003C/strong\u003E because the cold air the front leaves behind is humid, which leads to precipitation.\u003C/td\u003E\r\n\u003C/tr\u003E\r\n\u003C/tbody\u003E\r\n\u003C/table\u003E", + "is_callout": false, + "is_full_width": true, + "is_hidden": false, + "name": "", + "type": "Embeddable::Xhtml", + "ref_id": "147903-Embeddable::Xhtml" + }, + "section": "header_block" + }, { + "embeddable": { + "plugin": { + "description": null, + "author_data": "{\"tipType\":\"windowShade\",\"windowShade\":{\"windowShadeType\":\"teacherTip\",\"layout\":\"mediaLeft\",\"initialOpenState\":true,\"content\":\"###Pre-Assessment Implementation\\n*Lesson 4, Opening: What Are the Rules for Fronts and Precipitation? Pre-Assessment*\\nDuring the pre-assessment, each student will view the probe and make an individual choice. The request for explanation will only be on the post-assessment. After students make an individual choice for the pre-assessment, the teacher can lead discussion including, for example, a pair/share opportunity and/or full class discussion. \\n\\nAt this time, encourage students to share and discuss their ideas and reasons without indicating that any one answer is better or worse. Let the students know that they should keep thinking about this question and that the class will return to it at the end of the next lesson (Lesson 5).\",\"content2\":\"\",\"mediaType\":\"none\",\"mediaCaption\":\"Last, First. \\\"Title of Work.\\\" Year created. Site Title [OR] Publisher. Gallery [OR] Location. http://www.url.com.\",\"mediaURL\":\"\"}}", + "approved_script_label": "teacherEditionTips", + "component_label": "windowShade", + "approved_script": { + "name": "Teacher Edition", + "url": "https://teacher-edition-tips-plugin.concord.org/version/v3.6.0/plugin.js", + "label": "teacherEditionTips", + "description": "This plugin provides Teacher Edition components", + "version": 3, + "json_url": "https://teacher-edition-tips-plugin.concord.org/version/v3.6.0/manifest.json", + "authoring_metadata": "{\"components\":[{\"label\":\"windowShade\",\"name\":\"Window Shades\",\"scope\":\"embeddable\",\"guiAuthoring\":true},{\"label\":\"sideTip\",\"name\":\"Side Tips\",\"scope\":\"embeddable\",\"guiAuthoring\":true},{\"label\":\"questionWrapper\",\"name\":\"Question Wrapper\",\"scope\":\"embeddable-decoration\",\"decorates\":[\"Embeddable::MultipleChoice\",\"Embeddable::OpenResponse\",\"Embeddable::ImageQuestion\",\"ManagedInteractive\",\"MwInteractive\",\"ImageInteractive\",\"VideoInteractive\"],\"guiAuthoring\":true,\"guiPreview\":true}]}" + } + }, + "is_hidden": false, + "is_full_width": true, + "type": "Embeddable::EmbeddablePlugin", + "ref_id": "10253-Embeddable::EmbeddablePlugin" + }, + "section": null + }, { + "embeddable": { + "plugin": { + "description": null, + "author_data": "{\"tipType\":\"windowShade\",\"windowShade\":{\"windowShadeType\":\"theoryAndBackground\",\"layout\":\"mediaLeft\",\"initialOpenState\":true,\"content\":\"###Computational Thinking Concepts and Practices:\\n* Pattern Recognition\\n* Data-based Prediction\\n* Rule Abstraction\\n\\n###What is the Purpose of this Assessment Probe?\\nThe following information provides background for teachers. We suggest teachers review the information below and think about ways to scaffold students toward developing knowledge and practice as appropriate for their classes. Also, we recommend that during the first implementation of the probe, teachers scaffold students to focus on students\u2019 own ideas about this problem. By discussing the different options, students can engage in productive talk related to the different response patterns, priming them to look for productive patterns to associate with precipitation in the upcoming lessons. \\n\\nDuring the ensuing two lessons and the second implementation of the probe, students should be able to use the data from the virtual storm to identify the patterns of temperature, humidity, and movement that are associated with precipitation.\\n\\nThis assessment probe is designed to assess and scaffold students in thinking and talking about how patterns of data (i.e., temperature, humidity, and air movement) are associated with precipitation in a location. To keep things simple, we only focus on two types of fronts: cold fronts and warm fronts. Both types of fronts can be associated with precipitation. Identifying patterns associated with precipitation is an example of the computational thinking practice of **Pattern Recognition**. Once patterns associated with precipitation are identified, they can be used in conjunction with data to make a **Data-based Prediction**, which is what Ms. Tevuk\u2019s students are trying to do in the scenario for this assessment probe. **Data-based Prediction** involves identifying patterns and trends within and across groups of data/information as seen in the observable world. The patterns of data associated with precipitation in turn can be used to create rules for the computer model in a process of **Rule Abstraction**. **Rule abstraction** involves creating a general statement derived from exploring patterns in data in order to establish rule(s) or principles. In other words, if you know the patterns of variable values associated with precipitation, you can use those patterns to write rules for predicting precipitation.\\n\\nAs a **cold front** moves into an area, the heavier cool air pushes under the lighter warm air. The air behind a cold front is colder and usually drier than the warm air in front. The warm air in front becomes cooler as it is pushed upward by the entering cold air. If the warm air is humid enough, the water vapor it contains will condense into clouds as it rises, and precipitation may fall. \\n\u003Cimg src=\\\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/L4L5AssessmentTeacherGuideImage2.png\\\" width=\\\"850\\\" height=\\\"180\\\" /\u003E\\n \\n\\nWhen a **warm front** moves into an area, warm air moves above a cool air mass. As the warm air rises, it condenses, often forming clouds and precipitation. \\n\u003Cimg src=\\\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/L4L5AssessmentTeacherGuideImage1.png\\\" width=\\\"850\\\" height=\\\"180\\\" /\u003E\\n\\nThe assessment is situated in the unit context to provide an opportunity for students to make sense about patterns when reasoning about air masses, fronts, and precipitation. In this assessment, one of the responses is scientifically correct while the other responses that relate to some informal ideas about weather that students may hold. \",\"content2\":\"\",\"mediaType\":\"none\",\"mediaCaption\":\"Last, First. \\\"Title of Work.\\\" Year created. Site Title [OR] Publisher. Gallery [OR] Location. http://www.url.com.\",\"mediaURL\":\"\"}}", + "approved_script_label": "teacherEditionTips", + "component_label": "windowShade", + "approved_script": { + "name": "Teacher Edition", + "url": "https://teacher-edition-tips-plugin.concord.org/version/v3.6.0/plugin.js", + "label": "teacherEditionTips", + "description": "This plugin provides Teacher Edition components", + "version": 3, + "json_url": "https://teacher-edition-tips-plugin.concord.org/version/v3.6.0/manifest.json", + "authoring_metadata": "{\"components\":[{\"label\":\"windowShade\",\"name\":\"Window Shades\",\"scope\":\"embeddable\",\"guiAuthoring\":true},{\"label\":\"sideTip\",\"name\":\"Side Tips\",\"scope\":\"embeddable\",\"guiAuthoring\":true},{\"label\":\"questionWrapper\",\"name\":\"Question Wrapper\",\"scope\":\"embeddable-decoration\",\"decorates\":[\"Embeddable::MultipleChoice\",\"Embeddable::OpenResponse\",\"Embeddable::ImageQuestion\",\"ManagedInteractive\",\"MwInteractive\",\"ImageInteractive\",\"VideoInteractive\"],\"guiAuthoring\":true,\"guiPreview\":true}]}" + } + }, + "is_hidden": false, + "is_full_width": true, + "type": "Embeddable::EmbeddablePlugin", + "ref_id": "10254-Embeddable::EmbeddablePlugin" + }, + "section": null + }, { + "embeddable": { + "plugin": { + "description": null, + "author_data": "{\"tipType\":\"windowShade\",\"windowShade\":{\"windowShadeType\":\"discussionPoints\",\"layout\":\"mediaLeft\",\"initialOpenState\":true,\"content\":\"###What Are Common Student Ideas and What Supports Could Help Students?\\nBelow are some issues to consider in assessing students\u2019 ideas, and some suggestions of ways to support students in developing more formal reasoning about patterns associated with fronts and precipitation.\\n\\n###Less Formal Ideas\\n\u2022\\t**Kalin\u2019s response (precipitation with a cold front coming in)** suggests that Kalin may just be thinking about patterns of familiar things going together (cold and wet, warm and sunny) rather than thinking about patterns associated with different types of air masses interacting with one another. Students may associate sun with warm, and rain and snow with cold. Based on that experience, they may think that a cold front is connected to precipitation.\\n\\nStudents who choose Kalin\u2019s response could benefit from having experiences that challenge their simple association idea. For example, looking at weather maps that show warmer air often has more moisture in it and colder air is often drier can help these students develop understanding that relationships might not be as simple as they think. Students who choose Kalin\u2019s response may not think about weather as something that happens with matter. Instead, they may just think of weather in terms of the actions of natural \\\"actors\\\" (e.g., the sun makes it warm, the wind makes it cold). These students could use help in learning that air masses are matter (they are made up of molecules and have mass). If we didn\u2019t have air masses made of matter on Earth, then we wouldn\u2019t have weather. You might talk with students about concrete examples that they can extend to think about air masses as entities made of stuff \u2013 for example, they could compare an empty balloon, a balloon filled with warm air, and a balloon filled with cold air. There is very little stuff (matter or molecules of air) in the empty balloon, while there is more stuff (matter) in the balloons filled with warm and cold air.\\n\\n###Middle Level \\n\u2022\\t**Both Alex\u2019s response (precipitation occurs with a warm front coming in)** and **Sage\u2019s response (precipitation occurs after a cold front has passed by an area)** suggest that they are aware that precipitation is associated with bodies of air moving and with the different conditions in those bodies of air (i.e., temperature, levels of humidity). However, both Sage\u2019s and Alex\u2019s ideas include some incorrect patterns that lead to problematic rules. \\n\\n\u2022\\t**Alex** thinks that cold air and warm air mixing causes precipitation. However, warm and cold air masses don\u2019t mix very readily, and it is instead actually warm air rising, expanding, and condensing that generally leads to precipitation. In addition, while Alex knows that cold fronts can be drier than warm fronts, that doesn\u2019t mean that there won\u2019t be any precipitation with cold fronts. Precipitation can occur with a cold front when warm air is pushed up, expands, and condenses.\\n\\nStudents who choose Alex\u2019s response could benefit from working with data to observe the following patterns: (1) precipitation can occur with a cold front and (2) fronts do not necessarily mix.\\n\\n\u2022\\t**Sage** thinks that cold air is humid, which leads to condensation and precipitation. However, warm air masses often have a higher level of humidity compared with cold air masses. It can be confusing that condensation occurs with rising, expanding, and cooling. The unit does not go into this in depth, however. For students who choose Sage\u2019s response, it is probably sufficient here to scaffold experiences with data and virtual storm showing the general pattern of warm air masses having higher levels of humidity than cool air masses.\\n\\n\u2022\\tStudents who choose Alex or Sage\u2019s response can also benefit from discussion and emphasis on the importance of getting the rule right (enough) in order to create a computational model that works. The students working on their weather model will not be able to predict weather with any consistency or accuracy if there is a big problem with the rule (algorithm) they have written into their computer model. \\n\\n###More Formal Idea\\n\u2022\\t**Delana\u2019s response (precipitation occurs with both cold fronts and warm fronts coming in)** is the best answer. Delana\u2019s explanation does not include a more complete mechanistic sequence involving cold air pushing warm air up; warm air rising, expanding, and condensing; and precipitation occurring as a result. This is because the Precipitating Change curriculum simplifies weather phenomena by emphasizing important patterns and de-emphasizing complicated mechanisms. This focus allows the curriculum to scaffold students in connecting observed patterns with rules that can be used to create predictive weather forecasting computer models. 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She will discuss how\u0026nbsp;making sense of the weather data helps in predicting\u0026nbsp;weather.\u003C/p\u003E", + "is_callout": true, + "is_full_width": true, + "is_hidden": false, + "name": "", + "type": "Embeddable::Xhtml", + "ref_id": "148014-Embeddable::Xhtml" + }, + "section": "header_block" + }, { + "embeddable": { + "name": "", + "url_fragment": null, + "authored_state": "{\"version\":1,\"questionType\":\"iframe_interactive\",\"poster\":\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/Captioned_Videos/Posters/Poster_L4_Video.png\",\"videoUrl\":\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/Captioned_Videos/JackieLesson4_88_Captioned.mp4\"}", + "is_hidden": false, + "is_full_width": true, + "show_in_featured_question_report": true, + "inherit_aspect_ratio_method": true, + "custom_aspect_ratio_method": null, + "inherit_native_width": true, + "custom_native_width": 576, + "inherit_native_height": true, + "custom_native_height": 435, + "inherit_click_to_play": true, + "custom_click_to_play": false, + "inherit_full_window": true, + "custom_full_window": false, + "inherit_click_to_play_prompt": true, + "custom_click_to_play_prompt": null, + "inherit_image_url": true, + "custom_image_url": null, + "library_interactive": { + "hash": "34e1a2a39c058da8ff4ffe5a09ad14af337c4a01", + "data": { + "aspect_ratio_method": "DEFAULT", + "authoring_guidance": "", + "base_url": "https://models-resources.concord.org/question-interactives/version/v1.1.0/video-player/", + "click_to_play": false, + "click_to_play_prompt": null, + "description": "This video player will not have the blue header bar above the interactive.\r\nIt does not save the students position in the video. \r\nIt will not show up in the teacher report.", + "enable_learner_state": false, + "full_window": false, + "has_report_url": false, + "image_url": null, + "name": "Video Player", + "native_height": 435, + "native_width": 576, + "no_snapshots": false, + "show_delete_data_button": false, + "thumbnail_url": "", + "customizable": false, + "authorable": true + } + }, + "type": "ManagedInteractive", + "ref_id": "1766-ManagedInteractive", + "linked_interactives": [] + }, + "section": "header_block" + }] + }, { + "additional_sections": {}, + "embeddable_display_mode": "stacked", + "id": 143593, + "is_completion": false, + "is_hidden": false, + "layout": "l-full-width", + "name": "Opening", + "position": 2, + "show_header": true, + "show_info_assessment": true, + "show_interactive": false, + "show_sidebar": false, + "sidebar": null, + "sidebar_title": "Did you know?", + "toggle_info_assessment": false, + "embeddables": [{ + "embeddable": { + "content": "\u003Cp\u003EAs weather scientists, your job is not only to collect and organize data, but also to make sense of the data you collected. One way to make sense of the data is to develop a rule, generalized statements of patterns you see again and again.\u003C/p\u003E\n\u003Cp\u003EExample: This rule has two parts that must happen to have a certain result. If it was a [ \u003Cstrong\u003Every nice summer\u003C/strong\u003E ] and if it is [ \u003Cstrong\u003EAugust\u003C/strong\u003E ], then there will be [ \u003Cstrong\u003Elots of berries to pick\u003C/strong\u003E ].\u0026nbsp;\u003C/p\u003E\n\u003Cp style=\"text-align: justify;\"\u003E\u003Cimg class=\"\" src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/RuleStatement.jpg\" alt=\"\" width=\"472\" height=\"221\" /\u003E\u003C/p\u003E\n\u003Cp\u003EThink about developing a similar statement that could be used to determine where it will rain.\u003C/p\u003E", + "is_callout": false, + "is_full_width": true, + "is_hidden": false, + "name": "", + "type": "Embeddable::Xhtml", + "ref_id": "147899-Embeddable::Xhtml" + }, + "section": "header_block" + }, { + "embeddable": { + "plugin": { + "description": "", + "author_data": "{\"tipType\":\"windowShade\",\"questionWrapper\":{\"correctExplanation\":\"correct\",\"distractorsExplanation\":\"distractor\",\"exemplar\":\"exemplar\",\"teacherTip\":\"teacherTip\",\"teacherTipImageOverlay\":\"\"},\"windowShade\":{\"windowShadeType\":\"theoryAndBackground\",\"layout\":\"mediaLeft\",\"initialOpenState\":false,\"content\":\"### LESSON 4: BUILDING RULES\\n**WHERE DOES IT RAIN?**\\n\\nIn this lesson, students develop a rule for where it will rain and test their rule using a Virtual Model. 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a/src/public/offline-activities/precipitating-change-v2/lesson-5-post.json b/src/public/offline-activities/precipitating-change-v2/lesson-5-post.json new file mode 100644 index 00000000..a96cb3e0 --- /dev/null +++ b/src/public/offline-activities/precipitating-change-v2/lesson-5-post.json @@ -0,0 +1,285 @@ +{ + "description": "", + "editor_mode": 0, + "layout": 0, + "name": "Alaska 2021 - Lesson 5: Post-thoughts - How should we represent wind direction?", + "notes": "", + "project_id": 25, + "related": "", + "runtime": "Activity Player", + "show_submit_button": true, + "student_report_enabled": true, + "thumbnail_url": "https://learn-resources.concord.org/images/stem-resources/icons/pc-lesson2.png", + "time_to_complete": null, + "version": 1, + "theme_name": "Precipitating Change", + "pages": [{ + "additional_sections": {}, + "embeddable_display_mode": "stacked", + "id": 143619, + "is_completion": false, + "is_hidden": false, + "layout": "l-full-width", + "name": "Page 1", + "position": 1, + "show_header": true, + "show_info_assessment": false, + "show_interactive": false, + "show_sidebar": false, + "sidebar": null, + "sidebar_title": "Did you know?", + "toggle_info_assessment": false, + "embeddables": [{ + "embeddable": { + "content": "\u003Cp\u003E\u003Cstrong\u003EHow Should We Represent Wind Direction?\u003C/strong\u003E\u003C/p\u003E\r\n\u003Cp\u003EThe word represent means to let one thing stand for another. For example, some people use the symbol of a\u003C/p\u003E\r\n\u003Cp\u003Eheart [\u003Cimg src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/Captioned_Videos/new_picts/heart2.png\" width=\"27\" height=\"23\" /\u003E] to represent (or stand for) love. \u0026nbsp;\u003C/p\u003E\r\n\u003Cp\u003EFour students in Ms. Tevuk\u0026rsquo;s class are figuring out how to represent wind direction both (1) in their computer model that does calculations to predict the weather and (2) on a map the computer model produces to show the weather prediction. The students have different ideas about how to represent wind direction for these two purposes.\u003C/p\u003E\r\n\u003Cp\u003EHere are some different options Ms. Tevuk\u0026rsquo;s students are considering for representing wind direction.\u003C/p\u003E\r\n\u003Cp\u003E\u0026bull;\u0026nbsp;\u003Cstrong\u003EWind direction represented with degree number (between 0 and 360) based on the compass\u0026nbsp;\u003C/strong\u003E\u003C/p\u003E\r\n\u003Cp\u003E\u003Cimg src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/Captioned_Videos/new_picts/Lesson_5_new_Embedded_assessment/Version2_wind_direction_with_degrees.png\" width=\"503\" height=\"230\" /\u003E\u003C/p\u003E\r\n\u003Cp\u003E\u003Cstrong\u003E\u0026bull;\u0026nbsp;Wind direction represented with letters based on the compass\u0026nbsp;\u003C/strong\u003E\u003C/p\u003E\r\n\u003Cp\u003E\u003Cstrong\u003E\u003Cimg src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/Captioned_Videos/new_picts/Lesson_5_new_Embedded_assessment/Version2_wind_direction_with_letters.png\" width=\"509\" height=\"234\" /\u003E\u003C/strong\u003E\u003C/p\u003E\r\n\u003Cp\u003E\u003Cstrong\u003E\u0026bull;\u0026nbsp;Wind direction represented with arrows\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u003C/strong\u003E\u003C/p\u003E\r\n\u003Cp\u003E\u003Cstrong\u003E\u003Cimg class=\"\" src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/Captioned_Videos/new_picts/Lesson_5_new_Embedded_assessment/Wind_direction_based_arrows.png\" alt=\"\" width=\"177\" height=\"181\" /\u003E\u003C/strong\u003E\u003C/p\u003E\r\n\u003Cp\u003E\u003Cstrong\u003E\u0026bull;\u0026nbsp;Wind direction represented with different colors\u003C/strong\u003E\u003C/p\u003E\r\n\u003Cp\u003E\u003Cstrong\u003E\u003Cimg class=\"\" src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/Captioned_Videos/new_picts/Lesson_5_new_Embedded_assessment/Wind_direction_different_colors.png\" alt=\"\" width=\"173\" height=\"177\" /\u003E\u003C/strong\u003E\u003C/p\u003E\r\n\u003Cp\u003EHere are the students\u0026rsquo; ideas:\u003C/p\u003E\r\n\u003Ctable style=\"border: solid 1px #000;\" cellpadding=\"30\"\u003E\r\n\u003Ctbody\u003E\r\n\u003Ctr\u003E\r\n\u003Cth style=\"border-right: solid 1px #000;\" colspan=\"2\"\u003E\u003Cstrong\u003EAlex\u003C/strong\u003E\u003C/th\u003E\r\n\u003Cth colspan=\"2\"\u003E\u003Cstrong\u003EDelana\u003C/strong\u003E\u003C/th\u003E\r\n\u003C/tr\u003E\r\n\u003Ctr\u003E\r\n\u003Ctd style=\"border-bottom: solid 1px #000;\" width=\"88\"\u003E\u003Cimg src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/Alex1.png\" width=\"60\" height=\"88\" align=\"center\" hspace=\"10\" vspace=\"10\" /\u003E\u003C/td\u003E\r\n\u003Ctd style=\"border-right: solid 1px #000; border-bottom: solid 1px #000; padding: 10px;\" width=\"350\"\u003E\r\n\u003Cp\u003EI think we should use the \u003Cstrong\u003Eletters for the computer model\u003C/strong\u003E because there are only 8 options, so the computer will have simple information to calculate with and it won\u0026rsquo;t get stuck computing. We can use the \u003Cstrong\u003Earrows on the map\u003C/strong\u003E because that way you can see which way the wind is going.\u003C/p\u003E\r\n\u003Cp\u003E\u003Cimg src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/Captioned_Videos/new_picts/Lesson_5_new_Embedded_assessment/Version2_letters_for_computer_model_Alex.png\" width=\"267\" height=\"183\" /\u003E\u003C/p\u003E\r\n\u003Cp\u003E\u003Cimg class=\"\" src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/Captioned_Videos/new_picts/Lesson_5_new_Embedded_assessment/Parts/Alex_Part2.png\" alt=\"\" width=\"270\" height=\"185\" /\u003E\u003C/p\u003E\r\n\u003C/td\u003E\r\n\u003Ctd style=\"border-bottom: solid 1px #000;\" width=\"88\"\u003E\u003Cimg src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/Delana1.png\" width=\"65\" height=\"92\" align=\"center\" hspace=\"10\" vspace=\"10\" /\u003E\u003C/td\u003E\r\n\u003Ctd style=\"border-bottom: solid 1px #000; padding: 10px;\" width=\"350\"\u003E\r\n\u003Cp\u003ELet\u0026rsquo;s use \u003Cstrong\u003Enumber of degrees on the computer model\u003C/strong\u003E because computers do calculations with numbers. I think we should use \u003Cstrong\u003Earrows on the map\u003C/strong\u003E because they make the pattern of wind direction easy to see.\u003C/p\u003E\r\n\u003Cp\u003E\u003Cimg src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/Captioned_Videos/new_picts/Lesson_5_new_Embedded_assessment/Version2_compass_degrees_for_computer_model_Delana.png\" width=\"269\" height=\"181\" /\u003E\u003C/p\u003E\r\n\u003Cp\u003E\u003Cimg class=\"\" src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/Captioned_Videos/new_picts/Lesson_5_new_Embedded_assessment/Parts/Delana_Part2.png\" alt=\"\" width=\"271\" height=\"180\" /\u003E\u003C/p\u003E\r\n\u003C/td\u003E\r\n\u003C/tr\u003E\r\n\u003Ctr\u003E\r\n\u003Cth style=\"border-right: solid 1px #000;\" colspan=\"2\"\u003E\u003Cstrong\u003EKalin\u003C/strong\u003E\u003C/th\u003E\r\n\u003Cth colspan=\"2\"\u003E\u003Cstrong\u003ESage\u003C/strong\u003E\u003C/th\u003E\r\n\u003C/tr\u003E\r\n\u003Ctr\u003E\r\n\u003Ctd width=\"88\"\u003E\r\n\u003Cp\u003E\u003Cimg src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/Kalin.png\" width=\"65\" height=\"88\" align=\"center\" hspace=\"10\" vspace=\"10\" /\u003E\u003C/p\u003E\r\n\u003C/td\u003E\r\n\u003Ctd style=\"border-right: solid 1px #000; padding: 10px;\" width=\"350\"\u003E\r\n\u003Cp\u003EI think we should use \u003Cstrong\u003Enumber of degrees for both the computer model and the map\u003C/strong\u003E because computers do calculations with numbers and our map should show what the computer calculated.\u003C/p\u003E\r\n\u003Cp\u003E\u003Cimg src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/Captioned_Videos/new_picts/Lesson_5_new_Embedded_assessment/Version2_compass_degrees_for_computer_model_Kalin.png\" width=\"257\" height=\"185\" /\u003E\u003C/p\u003E\r\n\u003Cp\u003E\u003Cimg src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/Captioned_Videos/new_picts/Lesson_5_new_Embedded_assessment/Version2_compass_degree_numbers_for_map_Kalin.png\" width=\"253\" height=\"181\" /\u003E\u003C/p\u003E\r\n\u003C/td\u003E\r\n\u003Ctd width=\"88\"\u003E\r\n\u003Cp\u003E\u003Cimg src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/Sage1.png\" width=\"65\" height=\"92\" align=\"center\" hspace=\"8\" vspace=\"8\" /\u003E\u003C/p\u003E\r\n\u003C/td\u003E\r\n\u003Ctd style=\"padding: 10px;\" width=\"350\"\u003E\r\n\u003Cp\u003EI think we should use \u003Cstrong\u003Ecolors for both the computer model and the map.\u003C/strong\u003E Colors are good for the map because it\u0026rsquo;s easy to see patterns in different colors. 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Pre-Assessment*\\nDuring the pre-assessment, each student will view the probe and make an individual choice. The request for explanation will only be on the post-assessment. After students make an individual commitment for the pre-assessment, you can lead a discussion including, for example, a pair/share opportunity and/or full class discussion. \\n\\nAt this time, encourage students to share and discuss their ideas and reasons without indicating that any one answer is better or worse. Let the students know that they should keep thinking about this question and that the class will return to it at the end of the lesson.\\n\",\"content2\":\"\",\"mediaType\":\"none\",\"mediaCaption\":\"Last, First. \\\"Title of Work.\\\" Year created. Site Title [OR] Publisher. 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Review the information and consider ways to scaffold students toward developing knowledge and practice as appropriate for their classes. We also recommend during the first implementation of the probe, you scaffold students to focus on student ideas about this problem, rather than on vocabulary terms such as **interpolation**. By discussing the different options, students can engage in productive talk related to data sense making and computational thinking without using technical terminology. During the ensuing lesson and the second implementation of the probe, the term interpolation can be used, as appropriate.\\n\\nThis assessment probe is designed to assess and scaffold students in thinking and talking about **interpolation**. **Interpolation** means estimating a value between ones that are known or tabulated using surrounding points or values (that is, estimating an unknown value based on surrounding information). \\n\\nThe assessment is situated within the unit context to provide an opportunity for students to make sense about interpolation of a specific, tangible weather question (i.e., temperatures along a map transect). There is always uncertainty involved when interpolating across data. Also, depending on circumstances, different methods may be appropriate. For example, if the students were trying to figure out how to dress for the day at location X, then simply choosing a number somewhere between the two might be sufficient. 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For example, some people use the symbol of a\u003C/p\u003E\r\n\u003Cp\u003Eheart [\u003Cimg src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/Captioned_Videos/new_picts/heart2.png\" width=\"27\" height=\"23\" /\u003E] to represent (or stand for) love. \u0026nbsp;\u003C/p\u003E\r\n\u003Cp\u003EFour students in Ms. Tevuk\u0026rsquo;s class are figuring out how to represent wind direction both (1) in their computer model that does calculations to predict the weather and (2) on a map the computer model produces to show the weather prediction. The students have different ideas about how to represent wind direction for these two purposes.\u003C/p\u003E\r\n\u003Cp\u003EHere are some different options Ms. Tevuk\u0026rsquo;s students are considering for representing wind direction.\u003C/p\u003E\r\n\u003Cp\u003E\u0026bull;\u0026nbsp;\u003Cstrong\u003EWind direction represented with degree number (between 0 and 360) based on the compass\u0026nbsp;\u003C/strong\u003E\u003C/p\u003E\r\n\u003Cp\u003E\u003Cimg src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/Captioned_Videos/new_picts/Lesson_5_new_Embedded_assessment/Version2_wind_direction_with_degrees.png\" width=\"503\" height=\"230\" /\u003E\u003C/p\u003E\r\n\u003Cp\u003E\u003Cstrong\u003E\u0026bull;\u0026nbsp;Wind direction represented with letters based on the compass\u0026nbsp;\u003C/strong\u003E\u003C/p\u003E\r\n\u003Cp\u003E\u003Cstrong\u003E\u003Cimg src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/Captioned_Videos/new_picts/Lesson_5_new_Embedded_assessment/Version2_wind_direction_with_letters.png\" width=\"509\" height=\"234\" /\u003E\u003C/strong\u003E\u003C/p\u003E\r\n\u003Cp\u003E\u003Cstrong\u003E\u0026bull;\u0026nbsp;Wind direction represented with arrows\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u003C/strong\u003E\u003C/p\u003E\r\n\u003Cp\u003E\u003Cstrong\u003E\u003Cimg class=\"\" src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/Captioned_Videos/new_picts/Lesson_5_new_Embedded_assessment/Wind_direction_based_arrows.png\" alt=\"\" width=\"177\" height=\"181\" /\u003E\u003C/strong\u003E\u003C/p\u003E\r\n\u003Cp\u003E\u003Cstrong\u003E\u0026bull;\u0026nbsp;Wind direction represented with different colors\u003C/strong\u003E\u003C/p\u003E\r\n\u003Cp\u003E\u003Cstrong\u003E\u003Cimg class=\"\" src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/Captioned_Videos/new_picts/Lesson_5_new_Embedded_assessment/Wind_direction_different_colors.png\" alt=\"\" width=\"173\" height=\"177\" /\u003E\u003C/strong\u003E\u003C/p\u003E\r\n\u003Cp\u003EHere are the students\u0026rsquo; ideas:\u003C/p\u003E\r\n\u003Ctable style=\"border: solid 1px #000;\" cellpadding=\"30\"\u003E\r\n\u003Ctbody\u003E\r\n\u003Ctr\u003E\r\n\u003Cth style=\"border-right: solid 1px #000;\" colspan=\"2\"\u003E\u003Cstrong\u003EAlex\u003C/strong\u003E\u003C/th\u003E\r\n\u003Cth colspan=\"2\"\u003E\u003Cstrong\u003EDelana\u003C/strong\u003E\u003C/th\u003E\r\n\u003C/tr\u003E\r\n\u003Ctr\u003E\r\n\u003Ctd style=\"border-bottom: solid 1px #000;\" width=\"88\"\u003E\u003Cimg src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/Alex1.png\" width=\"60\" height=\"88\" align=\"center\" hspace=\"10\" vspace=\"10\" /\u003E\u003C/td\u003E\r\n\u003Ctd style=\"border-right: solid 1px #000; border-bottom: solid 1px #000; padding: 10px;\" width=\"350\"\u003E\r\n\u003Cp\u003EI think we should use the \u003Cstrong\u003Eletters for the computer model\u003C/strong\u003E because there are only 8 options, so the computer will have simple information to calculate with and it won\u0026rsquo;t get stuck computing. We can use the \u003Cstrong\u003Earrows on the map\u003C/strong\u003E because that way you can see which way the wind is going.\u003C/p\u003E\r\n\u003Cp\u003E\u003Cimg src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/Captioned_Videos/new_picts/Lesson_5_new_Embedded_assessment/Version2_letters_for_computer_model_Alex.png\" width=\"267\" height=\"183\" /\u003E\u003C/p\u003E\r\n\u003Cp\u003E\u003Cimg class=\"\" src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/Captioned_Videos/new_picts/Lesson_5_new_Embedded_assessment/Parts/Alex_Part2.png\" alt=\"\" width=\"270\" height=\"185\" /\u003E\u003C/p\u003E\r\n\u003C/td\u003E\r\n\u003Ctd style=\"border-bottom: solid 1px #000;\" width=\"88\"\u003E\u003Cimg src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/Delana1.png\" width=\"65\" height=\"92\" align=\"center\" hspace=\"10\" vspace=\"10\" /\u003E\u003C/td\u003E\r\n\u003Ctd style=\"border-bottom: solid 1px #000; padding: 10px;\" width=\"350\"\u003E\r\n\u003Cp\u003ELet\u0026rsquo;s use \u003Cstrong\u003Enumber of degrees on the computer model\u003C/strong\u003E because computers do calculations with numbers. I think we should use \u003Cstrong\u003Earrows on the map\u003C/strong\u003E because they make the pattern of wind direction easy to see.\u003C/p\u003E\r\n\u003Cp\u003E\u003Cimg src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/Captioned_Videos/new_picts/Lesson_5_new_Embedded_assessment/Version2_compass_degrees_for_computer_model_Delana.png\" width=\"269\" height=\"181\" /\u003E\u003C/p\u003E\r\n\u003Cp\u003E\u003Cimg class=\"\" src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/Captioned_Videos/new_picts/Lesson_5_new_Embedded_assessment/Parts/Delana_Part2.png\" alt=\"\" width=\"271\" height=\"180\" /\u003E\u003C/p\u003E\r\n\u003C/td\u003E\r\n\u003C/tr\u003E\r\n\u003Ctr\u003E\r\n\u003Cth style=\"border-right: solid 1px #000;\" colspan=\"2\"\u003E\u003Cstrong\u003EKalin\u003C/strong\u003E\u003C/th\u003E\r\n\u003Cth colspan=\"2\"\u003E\u003Cstrong\u003ESage\u003C/strong\u003E\u003C/th\u003E\r\n\u003C/tr\u003E\r\n\u003Ctr\u003E\r\n\u003Ctd style=\"border-bottom: solid 1px #000;\" width=\"88\"\u003E\r\n\u003Cp\u003E\u003Cimg src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/Kalin.png\" width=\"65\" height=\"88\" align=\"center\" hspace=\"10\" vspace=\"10\" /\u003E\u003C/p\u003E\r\n\u003C/td\u003E\r\n\u003Ctd style=\"border-right: solid 1px #000; border-bottom: solid 1px #000; padding: 10px;\" width=\"350\"\u003E\r\n\u003Cp\u003EI think we should use \u003Cstrong\u003Enumber of degrees for both the computer model and the map\u003C/strong\u003E because computers do calculations with numbers and our map should show what the computer calculated.\u003C/p\u003E\r\n\u003Cp\u003E\u003Cimg src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/Captioned_Videos/new_picts/Lesson_5_new_Embedded_assessment/Version2_compass_degrees_for_computer_model_Kalin.png\" width=\"257\" height=\"185\" /\u003E\u003C/p\u003E\r\n\u003Cp\u003E\u003Cimg src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/Captioned_Videos/new_picts/Lesson_5_new_Embedded_assessment/Version2_compass_degree_numbers_for_map_Kalin.png\" width=\"253\" height=\"181\" /\u003E\u003C/p\u003E\r\n\u003C/td\u003E\r\n\u003Ctd style=\"border-bottom: solid 1px #000;\" width=\"88\"\u003E\r\n\u003Cp\u003E\u003Cimg src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/Sage1.png\" width=\"65\" height=\"92\" align=\"center\" hspace=\"8\" vspace=\"8\" /\u003E\u003C/p\u003E\r\n\u003C/td\u003E\r\n\u003Ctd style=\"border-bottom: solid 1px #000; padding: 10px;\" width=\"350\"\u003E\r\n\u003Cp\u003EI think we should use \u003Cstrong\u003Ecolors for both the computer model and the map.\u003C/strong\u003E Colors are good for the map because it\u0026rsquo;s easy to see patterns in different colors. Then it helps to have your computer model and map match, so it makes sense to use colors for the computer model too.\u003C/p\u003E\r\n\u003Cp\u003E\u003Cimg class=\"\" src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/Captioned_Videos/new_picts/Lesson_5_new_Embedded_assessment/Parts/Sage_Part1.png\" alt=\"\" width=\"275\" height=\"193\" /\u003E\u003C/p\u003E\r\n\u003Cp\u003E\u003Cimg class=\"\" src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/Captioned_Videos/new_picts/Lesson_5_new_Embedded_assessment/Parts/Sage_Part2.png\" alt=\"\" width=\"275\" height=\"190\" /\u003E\u003C/p\u003E\r\n\u003C/td\u003E\r\n\u003C/tr\u003E\r\n\u003C/tbody\u003E\r\n\u003C/table\u003E", + "is_callout": false, + "is_full_width": true, + "is_hidden": false, + "name": "", + "type": "Embeddable::Xhtml", + "ref_id": "147929-Embeddable::Xhtml" + }, + "section": "header_block" + }, { + "embeddable": { + "name": "", + "url_fragment": null, + "authored_state": "{\"version\":1,\"questionType\":\"multiple_choice\",\"multipleAnswers\":false,\"layout\":\"vertical\",\"choices\":[{\"id\":\"1\",\"content\":\"Alex\",\"correct\":false},{\"id\":\"2\",\"content\":\"Delana\",\"correct\":false},{\"id\":\"3\",\"content\":\"Kalin\",\"correct\":false},{\"content\":\"Sage\",\"correct\":false,\"id\":\"48ed2c41-2f41-4d5e-b70c-89cc42e2eb72\"}],\"prompt\":\"\u003Cp\u003EWhich student\u2019s idea do you agree with the most?\u003C/p\u003E\"}", + "is_hidden": false, + "is_full_width": true, + "show_in_featured_question_report": true, + "inherit_aspect_ratio_method": true, + "custom_aspect_ratio_method": "DEFAULT", + "inherit_native_width": true, + "custom_native_width": 576, + "inherit_native_height": true, + "custom_native_height": 435, + "inherit_click_to_play": true, + "custom_click_to_play": false, + "inherit_full_window": true, + "custom_full_window": false, + "inherit_click_to_play_prompt": true, + "custom_click_to_play_prompt": null, + "inherit_image_url": true, + "custom_image_url": null, + "library_interactive": { + "hash": "98f3d10aa7f2fce6bdeb0ecda339fa56dc80b37c", + "data": { + "aspect_ratio_method": "DEFAULT", + "authoring_guidance": "", + "base_url": "https://models-resources.concord.org/question-interactives/version/v1.1.0/multiple-choice/", + "click_to_play": false, + "click_to_play_prompt": null, + "description": "", + "enable_learner_state": true, + "full_window": false, + "has_report_url": false, + "image_url": null, + "name": "Multiple Choice", + "native_height": 435, + "native_width": 576, + "no_snapshots": false, + "show_delete_data_button": false, + "thumbnail_url": "", + "customizable": true, + "authorable": true + } + }, + "type": "ManagedInteractive", + "ref_id": "1698-ManagedInteractive", + "linked_interactives": [] + }, + "section": "header_block" + }, { + "embeddable": { + "name": "", + "url_fragment": null, + "authored_state": "{\"version\":1,\"questionType\":\"open_response\",\"prompt\":\"\u003Cp\u003EWhy do you think the choice you picked is the best for representing wind direction in the computer model and on the map? Please explain your reasoning. \u003C/p\u003E\"}", + "is_hidden": false, + "is_full_width": true, + "show_in_featured_question_report": true, + "inherit_aspect_ratio_method": true, + "custom_aspect_ratio_method": "DEFAULT", + "inherit_native_width": true, + "custom_native_width": 576, + "inherit_native_height": true, + "custom_native_height": 435, + "inherit_click_to_play": true, + "custom_click_to_play": false, + "inherit_full_window": true, + "custom_full_window": false, + "inherit_click_to_play_prompt": true, + "custom_click_to_play_prompt": null, + "inherit_image_url": true, + "custom_image_url": null, + "library_interactive": { + "hash": "512e0a0a74a0e1cd6247a8ec98fa94dabb8a6132", + "data": { + "aspect_ratio_method": "DEFAULT", + "authoring_guidance": "", + "base_url": "https://models-resources.concord.org/question-interactives/version/v1.1.0/open-response/", + "click_to_play": false, + "click_to_play_prompt": null, + "description": "", + "enable_learner_state": true, + "full_window": false, + "has_report_url": false, + "image_url": null, + "name": "Open Response", + "native_height": 435, + "native_width": 576, + "no_snapshots": false, + "show_delete_data_button": false, + "thumbnail_url": "", + "customizable": true, + "authorable": true + } + }, + "type": "ManagedInteractive", + "ref_id": "1699-ManagedInteractive", + "linked_interactives": [] + }, + "section": "header_block" + }, { + "embeddable": { + "custom": false, + "enable_check_answer": false, + "give_prediction_feedback": false, + "hint": "", + "is_full_width": true, + "is_hidden": false, + "is_prediction": false, + "layout": "vertical", + "multi_answer": false, + "name": "Multiple Choice Question element", + "prediction_feedback": "", + "prompt": "\u003Cp\u003EWhich student\u0026rsquo;s idea do you agree with the most?\u003C/p\u003E", + "show_as_menu": false, + "show_in_featured_question_report": true, + "choices": [{ + "choice": "Alex", + "is_correct": false, + "prompt": "" + }, { + "choice": "Delana", + "is_correct": false, + "prompt": "" + }, { + "choice": "Kalin", + "is_correct": false, + "prompt": "" + }, { + "choice": "Sage", + "is_correct": false, + "prompt": "" + }], + "type": "Embeddable::MultipleChoice", + "ref_id": "17146-Embeddable::MultipleChoice" + }, + "section": null + }, { + "embeddable": { + "plugin": { + "description": null, + "author_data": "{\"tipType\":\"windowShade\",\"windowShade\":{\"windowShadeType\":\"teacherTip\",\"layout\":\"mediaLeft\",\"initialOpenState\":true,\"content\":\"###Pre-Assessment Implementation\\n*Lesson 2, Opening: How Should We Estimate the Temperature? Pre-Assessment*\\nDuring the pre-assessment, each student will view the probe and make an individual choice. The request for explanation will only be on the post-assessment. After students make an individual commitment for the pre-assessment, you can lead a discussion including, for example, a pair/share opportunity and/or full class discussion. \\n\\nAt this time, encourage students to share and discuss their ideas and reasons without indicating that any one answer is better or worse. Let the students know that they should keep thinking about this question and that the class will return to it at the end of the lesson.\\n\",\"content2\":\"\",\"mediaType\":\"none\",\"mediaCaption\":\"Last, First. \\\"Title of Work.\\\" Year created. Site Title [OR] Publisher. Gallery [OR] Location. http://www.url.com.\",\"mediaURL\":\"\"}}", + "approved_script_label": "teacherEditionTips", + "component_label": "windowShade", + "approved_script": { + "name": "Teacher Edition", + "url": "https://teacher-edition-tips-plugin.concord.org/version/v3.6.0/plugin.js", + "label": "teacherEditionTips", + "description": "This plugin provides Teacher Edition components", + "version": 3, + "json_url": "https://teacher-edition-tips-plugin.concord.org/version/v3.6.0/manifest.json", + "authoring_metadata": "{\"components\":[{\"label\":\"windowShade\",\"name\":\"Window Shades\",\"scope\":\"embeddable\",\"guiAuthoring\":true},{\"label\":\"sideTip\",\"name\":\"Side Tips\",\"scope\":\"embeddable\",\"guiAuthoring\":true},{\"label\":\"questionWrapper\",\"name\":\"Question Wrapper\",\"scope\":\"embeddable-decoration\",\"decorates\":[\"Embeddable::MultipleChoice\",\"Embeddable::OpenResponse\",\"Embeddable::ImageQuestion\",\"ManagedInteractive\",\"MwInteractive\",\"ImageInteractive\",\"VideoInteractive\"],\"guiAuthoring\":true,\"guiPreview\":true}]}" + } + }, + "is_hidden": false, + "is_full_width": true, + "type": "Embeddable::EmbeddablePlugin", + "ref_id": "10295-Embeddable::EmbeddablePlugin" + }, + "section": null + }, { + "embeddable": { + "plugin": { + "description": null, + "author_data": "{\"tipType\":\"windowShade\",\"windowShade\":{\"windowShadeType\":\"theoryAndBackground\",\"layout\":\"mediaLeft\",\"initialOpenState\":true,\"content\":\"###Computational Thinking Concept and Practice:\\n* Interpolation\\n\\n###What is the Purpose of this Assessment Probe?\\nThe following information provides background for **teachers** and is not necessarily representative of the learning goals for everything students should understand. Review the information and consider ways to scaffold students toward developing knowledge and practice as appropriate for their classes. We also recommend during the first implementation of the probe, you scaffold students to focus on student ideas about this problem, rather than on vocabulary terms such as **interpolation**. By discussing the different options, students can engage in productive talk related to data sense making and computational thinking without using technical terminology. During the ensuing lesson and the second implementation of the probe, the term interpolation can be used, as appropriate.\\n\\nThis assessment probe is designed to assess and scaffold students in thinking and talking about **interpolation**. **Interpolation** means estimating a value between ones that are known or tabulated using surrounding points or values (that is, estimating an unknown value based on surrounding information). \\n\\nThe assessment is situated within the unit context to provide an opportunity for students to make sense about interpolation of a specific, tangible weather question (i.e., temperatures along a map transect). There is always uncertainty involved when interpolating across data. Also, depending on circumstances, different methods may be appropriate. For example, if the students were trying to figure out how to dress for the day at location X, then simply choosing a number somewhere between the two might be sufficient. 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Gallery [OR] Location. http://www.url.com.\",\"mediaURL\":\"\"}}", + "approved_script_label": "teacherEditionTips", + "component_label": "windowShade", + "approved_script": { + "name": "Teacher Edition", + "url": "https://teacher-edition-tips-plugin.concord.org/version/v3.6.0/plugin.js", + "label": "teacherEditionTips", + "description": "This plugin provides Teacher Edition components", + "version": 3, + "json_url": "https://teacher-edition-tips-plugin.concord.org/version/v3.6.0/manifest.json", + "authoring_metadata": "{\"components\":[{\"label\":\"windowShade\",\"name\":\"Window Shades\",\"scope\":\"embeddable\",\"guiAuthoring\":true},{\"label\":\"sideTip\",\"name\":\"Side Tips\",\"scope\":\"embeddable\",\"guiAuthoring\":true},{\"label\":\"questionWrapper\",\"name\":\"Question Wrapper\",\"scope\":\"embeddable-decoration\",\"decorates\":[\"Embeddable::MultipleChoice\",\"Embeddable::OpenResponse\",\"Embeddable::ImageQuestion\",\"ManagedInteractive\",\"MwInteractive\",\"ImageInteractive\",\"VideoInteractive\"],\"guiAuthoring\":true,\"guiPreview\":true}]}" + } + }, + "is_hidden": false, + "is_full_width": true, + "type": "Embeddable::EmbeddablePlugin", + "ref_id": "10296-Embeddable::EmbeddablePlugin" + }, + "section": null + }, { + "embeddable": { + "plugin": { + "description": null, + "author_data": "{\"tipType\":\"windowShade\",\"windowShade\":{\"windowShadeType\":\"discussionPoints\",\"layout\":\"mediaLeft\",\"initialOpenState\":true,\"content\":\"###What Are Common Student Ideas and What Supports Could Help Students?\\nBelow are some issues to consider in assessing students\u2019 ideas, and some suggestions of ways to support students in developing more formal reasoning.\\n\\n###Less Formal Ideas\\n\u2022\\t**Kalin\u2019s response (It doesn\u2019t make sense to estimate; you need to go there and measure.)** suggests a very concrete thinking approach consistent with the idea that \u201cyou\u2019ve got to see it to believe it.\u201d \\n\\nStudents who choose Kalin\u2019s response could benefit from discussions about how while estimates and interpolations may not be perfect, they can still give us a sense of what\u2019s going on in a system when we have limited data. It might be helpful to discuss that we can never collect all the data in the world; there\u2019s too much! Because of this, we need a way to fill in missing values using the data that we do have available. \\n\\n###Middle Level \\n\u2022\\t**Both Alex\u2019s response (choose the value half way between)** and **Sage\u2019s response (choose a number closer to 59)** might be reasonable estimates in certain circumstances (e.g., for picking out what clothes to wear if you were at location X at that time). These approaches are both better than just choosing a random value as an estimate for X. However, for contexts in which more precision is called for (e.g., making a weather model), then there are ways that we can be more precise in our approaches to interpolation. \\n\\nStudents who choose Alex\u2019s and/or Sage\u2019s response could benefit from discussions of when and why we sometimes might need to be more precise in our estimation approaches. \\n\\n\\n###More Formal Idea\\n\u2022\\t**Delana\u2019s response (mark a number line with the estimate in each square going up the same amount between the two measured values)** suggests that she understands which mathematical interpolation approach will give the most precise value. Again, this level of precision will take more time and effort, and may not even be necessary in some circumstances, as discussed above. 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She will discuss how wind direction\u0026nbsp;impacts different air masses.\u003C/p\u003E", + "is_callout": true, + "is_full_width": true, + "is_hidden": false, + "name": "", + "type": "Embeddable::Xhtml", + "ref_id": "148015-Embeddable::Xhtml" + }, + "section": "header_block" + }, { + "embeddable": { + "name": "", + "url_fragment": null, + "authored_state": "{\"version\":1,\"questionType\":\"iframe_interactive\",\"videoUrl\":\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/Captioned_Videos/JackieLesson5_88_Captioned.mp4\",\"poster\":\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/Captioned_Videos/Posters/Poster_L5_Video.png\"}", + "is_hidden": false, + "is_full_width": true, + "show_in_featured_question_report": true, + "inherit_aspect_ratio_method": true, + "custom_aspect_ratio_method": null, + "inherit_native_width": true, + "custom_native_width": 576, + "inherit_native_height": true, + "custom_native_height": 435, + "inherit_click_to_play": true, + "custom_click_to_play": false, + "inherit_full_window": true, + "custom_full_window": false, + "inherit_click_to_play_prompt": true, + "custom_click_to_play_prompt": null, + "inherit_image_url": true, + "custom_image_url": null, + "library_interactive": { + "hash": "34e1a2a39c058da8ff4ffe5a09ad14af337c4a01", + "data": { + "aspect_ratio_method": "DEFAULT", + "authoring_guidance": "", + "base_url": "https://models-resources.concord.org/question-interactives/version/v1.1.0/video-player/", + "click_to_play": false, + "click_to_play_prompt": null, + "description": "This video player will not have the blue header bar above the interactive.\r\nIt does not save the students position in the video. \r\nIt will not show up in the teacher report.", + "enable_learner_state": false, + "full_window": false, + "has_report_url": false, + "image_url": null, + "name": "Video Player", + "native_height": 435, + "native_width": 576, + "no_snapshots": false, + "show_delete_data_button": false, + "thumbnail_url": "", + "customizable": false, + "authorable": true + } + }, + "type": "ManagedInteractive", + "ref_id": "1767-ManagedInteractive", + "linked_interactives": [] + }, + "section": "header_block" + }] + }, { + "additional_sections": {}, + "embeddable_display_mode": "stacked", + "id": 143599, + "is_completion": false, + "is_hidden": false, + "layout": "l-full-width", + "name": "Opening", + "position": 2, + "show_header": true, + "show_info_assessment": true, + "show_interactive": false, + "show_sidebar": false, + "sidebar": null, + "sidebar_title": "Did you know?", + "toggle_info_assessment": false, + "embeddables": [{ + "embeddable": { + "content": "\u003Cp\u003EHave you ever noticed that the wind can come from one direction and then a few hours later a different direction? As weather scientists, you will explore a new component of the\u0026nbsp;weather\u0026nbsp;- wind! The direction of the wind can give you clues about what\u0026nbsp;weather\u0026nbsp;to expect. And when the wind changes its direction drastically, interesting\u0026nbsp;weather\u0026nbsp;events can happen.\u003C/p\u003E\n\u003Cp\u003E\u003Cbr /\u003EIn this lesson you will explore how air masses interact by\u0026nbsp;setting up a wind table. You will also revisit weather station data and radar maps you used in Lesson 1 with some additions: wind data and five more\u0026nbsp;weather\u0026nbsp;stations. In your Science Notebook, go to Lesson 5 to locate the following information:\u0026nbsp;\u003Cbr /\u003E\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; 0 Map with Additional Weather Stations and Data Tables\u0026nbsp;\u003Cbr /\u003E\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; 0 Alaskan Stations 7 pm Readings \u003Cbr /\u003E\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; 0 Alaskan Stations 7 pm Interpolated Map\u003Cbr /\u003E\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;0 Alaskan Stations 7 am Interpolated Map\u003Cbr /\u003E\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u003C/p\u003E", + "is_callout": false, + "is_full_width": true, + "is_hidden": false, + "name": "", + "type": "Embeddable::Xhtml", + "ref_id": "147905-Embeddable::Xhtml" + }, + "section": "header_block" + }, { + "embeddable": { + "plugin": { + "description": "", + "author_data": "{\"tipType\":\"windowShade\",\"questionWrapper\":{\"correctExplanation\":\"correct\",\"distractorsExplanation\":\"distractor\",\"exemplar\":\"exemplar\",\"teacherTip\":\"teacherTip\",\"teacherTipImageOverlay\":\"\"},\"windowShade\":{\"windowShadeType\":\"theoryAndBackground\",\"layout\":\"mediaLeft\",\"initialOpenState\":false,\"content\":\"###LESSON 5: IDENTIFYING AIR MASSES\\n\\n**WHERE DOES THE AIR COME FROM?**\\n\\nIn this lesson, students investigate the role that wind plays in determining the weather and are introduced to ways to identify and define an air mass. Air masses have a similar range of weather variables (temperature and moisture), have indistinct boundaries, and are categorized by the range of weather variables within them. The air within an air mass is constantly moving and precipitation can occur where air from different air masses mixes/interacts. Scientists use models to predict where precipitation will occur based on where different air masses interact, the type of air in each, and the movement of that air.\\n\\nTo begin to identify air masses, students will do a hands-on wind table activity, and get new temperature, air moisture content, and wind direction data for five additional weather stations. As in Lesson 4, the students once again construct a set of rules through a series of activities that allow them to uncover patterns in the data, investigate the mechanisms for these patterns, and abstract a rule that describes the relationship between wind direction, its associated air mass, and the resulting precipitation. \\n\\n###LEARNING GOALS\\nStudents will be able to:\\n\\n* Identify and define an air mass\\n\\n* Explain that air masses are defined by where they come from\\n\\n* Explain the role of wind in weather events\\n\\n* Identify where on a map two different masses are interacting/mixing\\n\\n* Develop a rule for how wind moves and test the rule with multiple kinds of air masses\\n\\n* Develop a rule to express the relationship between weather components (temperature and moisture) and air masses\\n\\nComputational Thinking (CT) skills introduced in this lessons can be found in the table below:\\n\\n| CT Skill | Definition |\\n|---------------------|---------------------------------------------------------------------------------------------------|------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|\\n| Pattern Recognition | Recognizing that data or information is repeating in a logical (expected) way |\\n| Rule Abstraction | Developing a statement of how things work based on the patterns you observed |\\n| Rule Testing | Investigating whether a rule will still be true in different situations |\\n| Rule Refinement | Modifying a rule to be more precise (exact, careful about details) to work in the model |\",\"content2\":\"\",\"mediaType\":\"none\",\"mediaCaption\":\"Last, First. \\\"Title of Work.\\\" Year created. 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(25 mins)\\n\\n* Post-Assessment - What Are the Rules for Fronts and Precipitation? (10 mins)\\n\\n###MATERIALS AND SET-UP\\n\\nActivity 1 - What is an Air Mass?\\n\\nPer Research Team:\\n\\n* Direct students to Lesson 5 in their Science Notebooks to find the following information:\\n * Lesson 5, Activity 1: Wind Table Instructions and Questions\\n * Lesson 5, Activity 2: Additional Weather Station Data\\n * Lesson 5, Activity 2: Weather Stations 7 pm Readings\\n * Lesson 5, Activity 2: Weather Stations 7 pm Interpolated\\n * Lesson 5, Activity 2: 7 pm Weather Station Data and 7 pm Radar Map\\n * Lesson 5, Activity 2: 7 am Weather Station Data \\n\\nPer Class:\\n\\n* Set up on one demonstration table that students can gather around: a wind fan, a piece of paper with a wind rose taped to the table, and a single weather vane. See below for a top-down view. \\n\\n\u003Cimg src=\\\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/Lesson5WIndTablesTopDownView1.jpg\\\" width=\\\"400\\\" height=\\\"350\\\"\u003E\\n\\n* To print the wind rose, click [here](https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/WindCompass.jpg) to download. \",\"content2\":\"\",\"mediaType\":\"none\",\"mediaCaption\":\"Last, First. \\\"Title of Work.\\\" Year created. Site Title [OR] Publisher. Gallery [OR] Location. http://www.url.com.\",\"mediaURL\":\"\"}}", + "approved_script_label": "teacherEditionTips", + "component_label": "windowShade", + "approved_script": { + "name": "Teacher Edition", + "url": "https://teacher-edition-tips-plugin.concord.org/version/v3.6.0/plugin.js", + "label": "teacherEditionTips", + "description": "This plugin provides Teacher Edition components", + "version": 3, + "json_url": "https://teacher-edition-tips-plugin.concord.org/version/v3.6.0/manifest.json", + "authoring_metadata": "{\"components\":[{\"label\":\"windowShade\",\"name\":\"Window Shades\",\"scope\":\"embeddable\",\"guiAuthoring\":true},{\"label\":\"sideTip\",\"name\":\"Side Tips\",\"scope\":\"embeddable\",\"guiAuthoring\":true},{\"label\":\"questionWrapper\",\"name\":\"Question Wrapper\",\"scope\":\"embeddable-decoration\",\"decorates\":[\"Embeddable::MultipleChoice\",\"Embeddable::OpenResponse\",\"Embeddable::ImageQuestion\",\"ManagedInteractive\",\"MwInteractive\",\"ImageInteractive\",\"VideoInteractive\"],\"guiAuthoring\":true,\"guiPreview\":true}]}" + } + }, + "is_hidden": false, + "is_full_width": true, + "type": "Embeddable::EmbeddablePlugin", + "ref_id": "10260-Embeddable::EmbeddablePlugin" + }, + "section": null + }, { + "embeddable": { + "plugin": { + "description": null, + "author_data": "{\"tipType\":\"windowShade\",\"windowShade\":{\"windowShadeType\":\"framing\",\"layout\":\"mediaLeft\",\"initialOpenState\":true,\"content\":\"Watch this video with your class to give students a perspective on the importance of weather and to build weather science career awareness.\",\"content2\":\"\",\"mediaType\":\"video\",\"mediaCaption\":\"Purcell, Jackie. \\\"Lesson 5.\\\" 2019. Good Life Productions. Anchorage, AK.\",\"mediaURL\":\"https://precipitatingchange-resources.concord.org/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/JackieLesson5_88.mp4\"}}", + "approved_script_label": "teacherEditionTips", + "component_label": "windowShade", + "approved_script": { + "name": "Teacher Edition", + "url": "https://teacher-edition-tips-plugin.concord.org/version/v3.6.0/plugin.js", + "label": "teacherEditionTips", + "description": "This plugin provides Teacher Edition components", + "version": 3, + "json_url": "https://teacher-edition-tips-plugin.concord.org/version/v3.6.0/manifest.json", + "authoring_metadata": "{\"components\":[{\"label\":\"windowShade\",\"name\":\"Window Shades\",\"scope\":\"embeddable\",\"guiAuthoring\":true},{\"label\":\"sideTip\",\"name\":\"Side Tips\",\"scope\":\"embeddable\",\"guiAuthoring\":true},{\"label\":\"questionWrapper\",\"name\":\"Question Wrapper\",\"scope\":\"embeddable-decoration\",\"decorates\":[\"Embeddable::MultipleChoice\",\"Embeddable::OpenResponse\",\"Embeddable::ImageQuestion\",\"ManagedInteractive\",\"MwInteractive\",\"ImageInteractive\",\"VideoInteractive\"],\"guiAuthoring\":true,\"guiPreview\":true}]}" + } + }, + "is_hidden": false, + "is_full_width": true, + "type": "Embeddable::EmbeddablePlugin", + "ref_id": "10261-Embeddable::EmbeddablePlugin" + }, + "section": null + }] + }, { + "additional_sections": {}, + "embeddable_display_mode": "stacked", + "id": 143600, + "is_completion": false, + "is_hidden": false, + "layout": "l-full-width", + "name": "What is an air mass?", + "position": 3, + "show_header": true, + "show_info_assessment": true, + "show_interactive": false, + "show_sidebar": false, + "sidebar": null, + "sidebar_title": "Did you know?", + "toggle_info_assessment": false, + "embeddables": [{ + "embeddable": { + "content": "\u003Cp\u003E\u003Cstrong\u003EMeasuring Wind with the Compass\u0026nbsp;\u003C/strong\u003E\u003C/p\u003E\n\u003Cp\u003EOne way wind direction\u0026nbsp;can be measured is with\u0026nbsp;a weather\u0026nbsp;vane or air socks. When the wind blows, the\u0026nbsp;weather\u0026nbsp;vane rotates and lines up with the path the air is flowing. So,\u0026nbsp;wind direction\u0026nbsp;is determined by what direction the wind is blowing and measured in degrees (\u0026deg;).\u003C/p\u003E\n\u003Cp\u003E\u003Cimg class=\"\" style=\"display: block; margin-left: auto; margin-right: auto;\" src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/WindCompass.jpg\" alt=\"\" width=\"323\" height=\"328\" /\u003E\u003C/p\u003E\n\u003Cp\u003EIn this activity, you will use a Wind Table to map the movement of air on a grid representing a region in Alaska. Go to your Science Notebooks, Lesson 5, page 21, for further instructions and to record your observations.\u003C/p\u003E\n\u003Cp\u003E\u003Cstrong\u003EWind Table\u003C/strong\u003E\u003C/p\u003E\n\u003Cp\u003E\u003Cimg style=\"display: block; margin-left: auto; margin-right: auto;\" src=\"https://precipitatingchange-resources.concord.org/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/WindTunnels.png\" width=\"576\" height=\"510\" /\u003E\u003C/p\u003E\n\u003Cp\u003E\u0026nbsp;\u003C/p\u003E", + "is_callout": false, + "is_full_width": true, + "is_hidden": false, + "name": "", + "type": "Embeddable::Xhtml", + "ref_id": "147906-Embeddable::Xhtml" + }, + "section": "header_block" + }, { + "embeddable": { + "plugin": { + "description": "", + "author_data": "{\"tipType\":\"windowShade\",\"questionWrapper\":{\"correctExplanation\":\"correct\",\"distractorsExplanation\":\"distractor\",\"exemplar\":\"exemplar\",\"teacherTip\":\"teacherTip\",\"teacherTipImageOverlay\":\"\"},\"windowShade\":{\"windowShadeType\":\"theoryAndBackground\",\"layout\":\"mediaLeft\",\"initialOpenState\":false,\"content\":\"\\n###Activity 1 - **What is an Air Mass?**\\nIn this activity students explore the patterns of air movement within and between air masses. Using a hands-on \u201cwind table,\u201d they engage in a tangible interaction with wind. By leveraging patterns from the previous activity dataset and the wind table, they will discover that when two air masses meet, the air converges. Weather scientists refer to these regions as fronts. \\n\\n###Wind Table Directions\\n * **1.Introduce the Wind Table.** Wind is one of the first things that atmospheric scientists look at when investigating the weather, but it can be difficult to understand by just looking at data and maps. A hands-on model is helpful to investigate a phenomenon like the wind.\\n\\n\\n * **2.Assign teams:** Assign research teams a Wind Table position number, either #1 or #2. \\n * **3.Wind tunnel position:** Have students place wind tunnel #1 and wind tunnel #2 according to the diagram in their Science Notebook for their assigned Team #.\\n * **4.Reminders:** Read over the things to keep in mind on page 21 in the Science Notebook, together as a class:\\n * **BE CAREFUL NOT TO PUT YOUR FINGERS NEAR THE FAN**\\n * Graph paper represents a region.\\n * A wind vane can be placed anywhere on the graph paper to determine what direction the wind is coming from.\\n * Record the wind direction by drawing an arrow in the direction the wind vane is pointing. (Recall that wind is always recorded showing the direction the wind is coming from.) If there is not a clear determination where the wind is coming from, then leave the square blank.\\n * Place a Styrofoam ball on the wind table to see the interaction between the two air masses.\\n * **5.Analyze air mass interactions** \\n\\n * Once all of the groups have finished mapping the wind direction, ask the students to determine the boundary of the two air masses by drawing a circle around the different air masses. \\n\\n * Ask the students if there was anywhere on the grid that they either had trouble deciding what direction to draw their arrow. Some students might remark that the wind vane wobbles or spins in the region between the two distinct air masses. Instruct the students to identify the diagonal region between the two air masses and circle this area with a green marker. \\n\\n* **6.Connecting the Wind Table to the interpolated map.** Ask students to compare Alaska Weather Stations: 7 pm Interpolated data with the wind map they created on their Wind Table. Lead a class conversation. See possible Discussion Points below. \\n\",\"content2\":\"\",\"mediaType\":\"none\",\"mediaCaption\":\"Last, First. \\\"Title of Work.\\\" Year created. Site Title [OR] Publisher. 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(Note that scientists also include pressure, but pressure is not covered in this unit.)\\n\\n###Wind Table Demonstration \\nThe compass rose describes the direction the wind is blowing in degrees. Wind coming directly from the South has a direction of 180\u00b0, from the East 90\u00b0, from the North 360\u00b0, etc. Place the fan to the \u201cNorth\u201d of the weather vane and turn it on. Move the weather vane so that it's at the center of the rose and have students read the wind direction from the rose. Then, move the fan to other locations. Ask students where you should move the fan to get a wind direction of, for example, 180\u00b0, 90\u00b0, 45\u00b0, etc. Move the fan to check their predictions. \\n\\n**Teacher Note:** Wind direction is determined by what direction the wind is coming from. This is a consequence of how it is measured. 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(cont.)", + "position": 4, + "show_header": true, + "show_info_assessment": true, + "show_interactive": true, + "show_sidebar": false, + "sidebar": null, + "sidebar_title": "Did you know?", + "toggle_info_assessment": false, + "embeddables": [{ + "embeddable": { + "content": "\u003Cp\u003EIDENTIFYING AIR MASSES\u003C/p\u003E\r\n\u003Cp\u003EIn Lesson 5 of your Science Notebook on pages 21-23, you have additional data weather station data and maps that show you the direction of the wind. On page 22, you will find a map that shows you the 7 pm reading from the additional weather stations. The arrows on the map represent the\u0026nbsp;wind direction. The data on page 23 of your Science Notebook, \"Weather Stations 7 pm Interpolated\" comes from an\u0026nbsp;interpolation\u0026nbsp;of wind direction\u0026nbsp;across the mainland of Alaska at 7 pm. See map below. Using the map on page 23, draw a line that splits the map into two parts: one section with the wind coming from the same direction and the other section with the wind coming from a different direction. It is your job to determine where you see that change in the\u0026nbsp;wind direction.\u003C/p\u003E\r\n\u003Cp\u003EStrategy for Identifying Two Air Masses:\u003C/p\u003E\r\n\u003Cp\u003E1. Make Sense of the Map:\u0026nbsp;\u003Cbr /\u003E\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026bull; Look at each row and see if the arrows change direction as you move across the row.\u0026nbsp;\u003Cbr /\u003E\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026bull; Look at each column and see if the arrows change direction as you move down the column.\u0026nbsp;\u003Cbr /\u003E2. Identify where you are going to place your line.\u0026nbsp;\u003Cbr /\u003E3. Draw your line on your paper map.\u003C/p\u003E", + "is_callout": false, + "is_full_width": true, + "is_hidden": false, + "name": "", + "type": "Embeddable::Xhtml", + "ref_id": "147907-Embeddable::Xhtml" + }, + "section": "header_block" + }, { + "embeddable": { + "default_text": "", + "give_prediction_feedback": false, + "hint": "", + "is_full_width": true, + "is_hidden": false, + "is_prediction": false, + "name": "", + "prediction_feedback": "", + "prompt": "\u003Cp\u003EWhy did you draw the line there?\u003C/p\u003E", + "show_in_featured_question_report": true, + "type": "Embeddable::OpenResponse", + "ref_id": "208885-Embeddable::OpenResponse" + }, + "section": null + }, { + "embeddable": { + "aspect_ratio_method": "DEFAULT", + "authored_state": "", + "click_to_play": false, + "click_to_play_prompt": null, + "enable_learner_state": false, + "full_window": false, + "has_report_url": false, + "image_url": null, + "is_full_width": true, + "is_hidden": false, + "model_library_url": null, + "name": "Identifying Air Masses and Fronts", + "native_height": 435, + "native_width": 576, + "no_snapshots": false, + "show_delete_data_button": true, + "show_in_featured_question_report": true, + "url": "https://s3.amazonaws.com/cc-project-resources/precipitatingchange/Models-2021/Lesson5-air-masses.v4.html", + "type": "MwInteractive", + "ref_id": "97692-MwInteractive", + "linked_interactives": [] + }, + "section": "interactive_box" + }] + }, { + "additional_sections": {}, + "embeddable_display_mode": "stacked", + "id": 143602, + "is_completion": false, + "is_hidden": false, + "layout": "l-full-width", + "name": "What is an air mass? (cont.)", + "position": 5, + "show_header": true, + "show_info_assessment": true, + "show_interactive": false, + "show_sidebar": false, + "sidebar": null, + "sidebar_title": "Did you know?", + "toggle_info_assessment": false, + "embeddables": [{ + "embeddable": { + "content": "\u003Cp\u003EThe line that you drew across your map represents a boundary between two\u0026nbsp;air masses. An air mass is a body of air with similar temperature and\u0026nbsp;air moisture\u0026nbsp;content. Identifying air masses and their properties is an important part of the work of atmospheric scientists. On the map you may have noticed a temperature number at the top of the square and an\u0026nbsp;air moisture\u0026nbsp;content number at the bottom of the square.\u003C/p\u003E\n\u003Cp\u003E\u003Cimg style=\"display: block; margin-left: auto; margin-right: auto;\" src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/TempMoisture.jpg\" width=\"212\" height=\"292\" /\u003E\u003C/p\u003E", + "is_callout": false, + "is_full_width": true, + "is_hidden": false, + "name": "", + "type": "Embeddable::Xhtml", + "ref_id": "147908-Embeddable::Xhtml" + }, + "section": "header_block" + }, { + "embeddable": { + "content": "\u003Cp\u003EDevelop a way to define the two air masses using the temperature and\u0026nbsp;air moisture\u0026nbsp;content values provided on the Alaskan Stations: Interpolated at 7 pm Map.\u003C/p\u003E\r\n\u003Cp\u003E\u003Cimg 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#2.\u003C/p\u003E\r\n\u003Cp\u003EAir Mass #1 is:\u003C/p\u003E", + "show_as_menu": false, + "show_in_featured_question_report": true, + "choices": [{ + "choice": "more moist", + "is_correct": false, + "prompt": "" + }, { + "choice": "more dry", + "is_correct": false, + "prompt": "" + }], + "type": "Embeddable::MultipleChoice", + "ref_id": "17141-Embeddable::MultipleChoice" + }, + "section": null + }, { + "embeddable": { + "custom": false, + "enable_check_answer": false, + "give_prediction_feedback": false, + "hint": "", + "is_full_width": true, + "is_hidden": false, + "is_prediction": false, + "layout": "vertical", + "multi_answer": false, + "name": "Multiple Choice Question element", + "prediction_feedback": "", + "prompt": "\u003Cp\u003E\u003Cstrong\u003EAir Mass #2 Properties\u003C/strong\u003E\u003C/p\u003E\r\n\u003Cp\u003ETemperature: Compare Air Mass #2 to Air Mass #1.\u003C/p\u003E\r\n\u003Cp\u003EAir Mass #2 over land is:\u003C/p\u003E", + "show_as_menu": false, + 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are very interested in fronts because they are where the\u0026nbsp;weather\u0026nbsp;can change. Sometimes this change is very sudden.\u003C/p\u003E", + "is_callout": false, + "is_full_width": true, + "is_hidden": false, + "name": "", + "type": "Embeddable::Xhtml", + "ref_id": "147910-Embeddable::Xhtml" + }, + "section": "header_block" + }, { + "embeddable": { + "content": "\u003Cp\u003EGo to page 24 in your Science Notebook and compare the 7 pm interpolated map and the 7 pm radar map.\u003C/p\u003E\r\n\u003Cp\u003E\u003Cimg class=\"\" src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/Lesson5_7pmInterpolatedRADARMAPcomparison.jpg\" alt=\"\" width=\"860\" height=\"300\" /\u003E\u003C/p\u003E\r\n\u003Cp\u003EDiscuss with your research team and write a general statement that answers the question, \u0026ldquo;How do air masses affect where it rains?\"\u0026nbsp;\u0026nbsp;\u003C/p\u003E\r\n\u003Cp\u003E\u0026nbsp;\u003C/p\u003E", + "is_callout": true, + "is_full_width": true, + "is_hidden": false, + "name": "TASK", + "type": "Embeddable::Xhtml", + "ref_id": "147911-Embeddable::Xhtml" + }, + "section": null + }, { + "embeddable": { + "default_text": "", + "give_prediction_feedback": false, + "hint": "\u003Cp\u003E\u0026bull; Where is the front? Where is it raining? How do they compare?\u003Cbr /\u003E\u0026bull; How does the location of the precipitation on the radar map compare to the warm air mass, the cold air mass, and the front?\u003Cbr /\u003E\u0026bull; What is the air like where it is raining?\u003C/p\u003E", + "is_full_width": true, + "is_hidden": false, + "is_prediction": false, + "name": "", + "prediction_feedback": "", + "prompt": "\u003Cp\u003EHow do air masses affect where it rains?\u003C/p\u003E", + "show_in_featured_question_report": true, + "type": "Embeddable::OpenResponse", + "ref_id": "208886-Embeddable::OpenResponse" + }, + "section": null + }, { + "embeddable": { + "content": "\u003Cp\u003EGo to page 25 in your Science Notebook and work with you research team to make a prediction for where you think it could rain at 7 am by drawing on the 7 am weather station map in your notebook.\u003C/p\u003E\r\n\u003Cp\u003E\u003Cimg src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/L4_ACT1_Alaska%20Weather%20Stations_7am%20Interpolated.png\" width=\"437\" height=\"263\" /\u003E\u003C/p\u003E\r\n\u003Cp\u003EAlaska Stations: Interpolated at 7 am\u003C/p\u003E", + "is_callout": true, + "is_full_width": true, + "is_hidden": false, + "name": "TASK", + "type": "Embeddable::Xhtml", + "ref_id": "147912-Embeddable::Xhtml" + }, + "section": null + }, { + "embeddable": { + "default_text": "", + "give_prediction_feedback": false, + "hint": "", + "is_full_width": true, + "is_hidden": false, + "is_prediction": false, + "name": "", + "prediction_feedback": "", + "prompt": "\u003Cp\u003EExplain why you think it could rain in the area you selected.\u003C/p\u003E", + "show_in_featured_question_report": true, + "type": "Embeddable::OpenResponse", + "ref_id": "208887-Embeddable::OpenResponse" + }, + "section": null + }, { + "embeddable": { + "plugin": { + "description": "", + "author_data": "{\"tipType\":\"windowShade\",\"questionWrapper\":{\"correctExplanation\":\"correct\",\"distractorsExplanation\":\"distractor\",\"exemplar\":\"exemplar\",\"teacherTip\":\"teacherTip\",\"teacherTipImageOverlay\":\"\",\"location\":\"bottom\"},\"windowShade\":{\"windowShadeType\":\"discussionPoints\",\"layout\":\"mediaLeft\",\"initialOpenState\":false,\"content\":\"###Identifying Air Masses\\n\\nPossible discussion questions:\\n\\n* How do we identify air masses? 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Sometimes it feels cold; sometimes it feels warm. The wind is what moves air. Weather scientists use\u0026nbsp;wind direction\u0026nbsp;to distinguish multiple air masses. What happens at the boundary of those two air masses? You will explore that question using a new Virtual Model. \u0026nbsp;\u003C/p\u003E", + "is_callout": false, + "is_full_width": true, + "is_hidden": false, + "name": "", + "type": "Embeddable::Xhtml", + "ref_id": "147914-Embeddable::Xhtml" + }, + "section": "header_block" + }, { + "embeddable": { + "content": "\u003Cp\u003EThis model shows wind as moving arrowheads and precipitation as green circles. There are two air masses. Identify where the front is.\u0026nbsp;\u003C/p\u003E\r\n\u003Cp\u003EThen, by trying different settings of the temperature and moisture, see if you can make up a rule for what conditions produce precipitation along the front, and on which side of the front the precipitation will occur.\u0026nbsp;\u003C/p\u003E\r\n\u003Cp\u003EStart by pressing \u003Cstrong\u003ESetup\u003C/strong\u003E and \u003Cstrong\u003ERun\u003C/strong\u003E. As you change temperatures and moisture settings you may want to press \u003Cstrong\u003ESetup\u003C/strong\u003E occasionally to start fresh. Be sure to discuss what you find with your research team.\u003C/p\u003E", + "is_callout": true, + "is_full_width": true, + "is_hidden": false, + "name": "TASK ", + "type": "Embeddable::Xhtml", + "ref_id": "147915-Embeddable::Xhtml" + }, + "section": null + }, { + "embeddable": { + "default_text": "", + "give_prediction_feedback": false, + "hint": "", + "is_full_width": true, + "is_hidden": false, + "is_prediction": false, + "name": "", + "prediction_feedback": "", + "prompt": "\u003Cp\u003EDescribe the position of the front, and explain how you know this.\u003C/p\u003E\r\n\u003Cp\u003EYou may use city names as landmarks.\u003C/p\u003E", + "show_in_featured_question_report": true, + "type": "Embeddable::OpenResponse", + "ref_id": "208890-Embeddable::OpenResponse" + }, + "section": null + }, { + "embeddable": { + "default_text": "", + "give_prediction_feedback": false, + "hint": "\u003Cp\u003E\u0026bull; Look at the temperature values for Air Mass 1 and Air Mass 2\u003Cbr /\u003E\u0026bull; Look at the moisture values for Air Mass 1 and Air Mass 2\u003C/p\u003E", + "is_full_width": true, + "is_hidden": false, + "is_prediction": false, + "name": "", + "prediction_feedback": "", + "prompt": "\u003Cp\u003EWhat are the conditions in the model that result in precipitation happening along a front?\u003C/p\u003E", + "show_in_featured_question_report": true, + "type": "Embeddable::OpenResponse", + "ref_id": "208891-Embeddable::OpenResponse" + }, + "section": null + }, { + "embeddable": { + "default_text": "", + "give_prediction_feedback": false, + "hint": "\u003Cp\u003E\u0026bull; Is the precipitation happening more on the colder side of the front?\u003Cbr /\u003E\u0026bull; Is the precipitation happening more on the warmer side of the front?\u003C/p\u003E", + "is_full_width": true, + "is_hidden": false, + "is_prediction": false, + "name": "", + "prediction_feedback": "", + "prompt": "\u003Cp\u003EDescribe specifically where the precipitation happens within the front.\u003C/p\u003E", + "show_in_featured_question_report": true, + "type": "Embeddable::OpenResponse", + "ref_id": "208892-Embeddable::OpenResponse" + }, + "section": null + }, { + "embeddable": { + "default_text": "", + "give_prediction_feedback": false, + "hint": "\u003Cp\u003EMake sure to use precise language and include both temperature and moisture values.\u003C/p\u003E", + "is_full_width": true, + "is_hidden": false, + "is_prediction": false, + "name": "", + "prediction_feedback": "", + "prompt": "\u003Cp\u003EFinalize your rule statement for \u0026ldquo;How do air masses affect where it rains?\u0026rdquo;\u003C/p\u003E", + "show_in_featured_question_report": true, + "type": "Embeddable::OpenResponse", + "ref_id": "208893-Embeddable::OpenResponse" + }, + "section": null + }, { + "embeddable": { + "plugin": { + "description": null, + "author_data": "{\"tipType\":\"windowShade\",\"windowShade\":{\"windowShadeType\":\"theoryAndBackground\",\"layout\":\"mediaLeft\",\"initialOpenState\":true,\"content\":\"###Activity 3 - How Do Air Masses Affect Precipitation? Virtual Model\\n\\n**Objective:** To build students\u2019 rule refinement skills by experimenting with a model to figure out its built-in weather rules. In this model, precipitation falls under a variety of conditions that can be set by changing temperatures and moisture for two air masses. \\n\\nStudents can vary the temperature and moisture of two air masses in order to better understand how interacting air masses create patterns of rain at a front. Through this process, students will come up with an even more robust rule for predicting rain that involves interacting air masses. The specific computational thinking practice highlighted and practiced in this activity is **Rule Refinement**.\\n\\n**1. Class discussion about air mass properties.**Use the Alaska Weather Stations: 7am Interpolated map! [](https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/Lesson5AirMasses1and2.jpg) to remind students of the properties of the air masses in their regional weather system. See Discussion Points below for possible prompts. \\n\\n**2. Set up the model challenge.** \\n\\n* Have students recall the rule they developed to answer the question \u201cHow do air masses affect where it rains?\u201d \\n\\n* Students will use the Lesson 5 virtual model to help refine their rule.\\n\\n**3. Exploring the Virtual Model.** \\n\\nIntroduce the task, and give students time to explore the model. Then let them tell you what they discovered. They may notice:\\n\\n * The properties of the incoming air can be changed using the sliders on the left and bottom.\\n\\n * The direction of the wind can be seen with arrows and trails that can be turned on or off.\\n\\n * Precipitation appears as green circles with bigger circles meaning heavier rain.\\n\\n * Color of arrows correspond to temperature (Red = Warm, Blue = Cold, Purple = In Between)\\n\\n * Size of arrows correspond to air moisture (Small = dry, Large = moist or humid)\\n\\nYou may want to point out that\\n\\n * Even though the air in the model moves, the model shows airflow for a certain time. Time does not change.\\n\\n**4. Experiment with the Model to find the Rule**\\n\\nTell students that this model has a built-in rule for precipitation made by the model\u2019s programmer. 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Ask students to discuss what they noticed about the model and what they learned from experimenting with it. The model is complex so there can be many viewpoints. The objective of this is to have students feel that they can learn from the model themselves. All observations are valid and up for discussion.\\n\\nPossible topics for discussion:\\n* It may be most valuable to discuss the questions student's answered on this page. An extended discussion could come from the question below.\\n\\n* What do the sizes and colors of the wind arrowheads mean? (The redder the warmer; the bluer the cooler; the larger the more moist; and the smaller the drier.)\\n\\n* Does precipitation fall only near the front? (No, it can fall where the arrowheads converge or come closer together.)\\n\\n* If the south settings and the west setting are the same, is there a front? (No, but the air may still converge.)\\n\\n* Do you see precipitation even where there is no front? What is a rule for it forming? 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their computer model to predict weather in Alaska. Then they tested their model to see how well it worked. They found their predictions were only right about half the time. The students had different ideas for improving the model.\u003C/p\u003E\r\n\u003Cp\u003EHere are the students\u0026rsquo; ideas:\u003C/p\u003E\r\n\u003Ctable cellpadding=\"30\"\u003E\r\n\u003Ctbody\u003E\r\n\u003Ctr\u003E\r\n\u003Cth colspan=\"2\"\u003E\u003Cstrong\u003EAlex\u003C/strong\u003E\u003C/th\u003E\r\n\u003Cth colspan=\"2\"\u003E\u003Cstrong\u003EDelana\u003C/strong\u003E\u003C/th\u003E\r\n\u003C/tr\u003E\r\n\u003Ctr\u003E\r\n\u003Ctd width=\"88\"\u003E\u003Cimg src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/Alex%206.png\" width=\"72\" height=\"90\" align=\"center\" hspace=\"10\" vspace=\"10\" /\u003E\u003C/td\u003E\r\n\u003Ctd style=\"padding: 10px;\" width=\"350\"\u003EWe need to run the model longer. The longer you run a computer model the better the prediction will be.\u003C/td\u003E\r\n\u003Ctd width=\"88\"\u003E\u003Cimg src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/Delana6.png\" width=\"70\" height=\"90\" align=\"center\" hspace=\"10\" vspace=\"10\" /\u003E\u003C/td\u003E\r\n\u003Ctd style=\"padding: 10px;\" width=\"350\"\u003EThere\u0026rsquo;s no way to make a computer model that can predict the weather. 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We suggest teachers review the information and think about ways to scaffold students toward developing knowledge and practice as appropriate for their classes. We also recommend emphasizing the underlying ideas and practices, rather than on vocabulary terms. By discussing the different options, students can engage in productive talk related to these computational thinking concepts without using technical terminology. \\n\\nThis assessment probe is designed to assess and scaffold students in thinking and talking about **Rule Refinement** and, especially, **Rule Testing**. **Rule Refinement** involves refining a rule for use in a modeling environment using scientific principles and incorporating additional data, making the rule more precise, computational, and/or detecting and correcting errors. **Rule Testing** is a process of \\\"calibration\\\" between the modeling environment and the observable world. 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We sometimes see this type of reasoning when students and even adults talk about climate change models. Some people say things like, \u201cthey are just models, so they don\u2019t really tell us what\u2019s going to happen in the real world.\u201d \\n\\nStudents who choose Delana\u2019s response could use support in developing understanding that computer models don\u2019t need to be perfect in order to be useful. No model is perfectly accurate. Models just need to be good enough for a given purpose. Computer modelers set calibration targets that define how close to the actual event they want their prediction to be (e.g., maybe they want their model to predict the correct outcome of rain or no rain for the next day 95% of the time). Uncertainty is also built into weather models for precipitation in other ways (e.g., a forecast of 70% chance of rain for a given day). Knowing that there is a 70% chance of rain tomorrow is better than not having any information about tomorrow\u2019s weather at all. Students who choose Delana\u2019s response (as well as all the other students) could benefit from conversations about and examples of what it means for a model to be \u201cgood enough\u201d to serve a purpose.\\n\\n###Middle Level \\n\u2022\\t**Alex\u2019s response (run the model longer)** suggests awareness that models are not perfect and that they can improve over time. This response may also appeal to some students who know about the idea of computer iteration (i.e., a process in which a set of instructions is repeated in a sequence multiple times or until a condition is met). Sometimes computer models need to run over time through multiple iterations to reach a certain set of criteria for the output. However, in this case, if the computer model is only making a correct prediction about half the time, then the computer needing more time to process the data probably isn\u2019t the problem. \\n\\nStudents who choose Alex\u2019s response could benefit from a discussion about whether or not they think running the model longer would help in this case.\\n\\n\u2022\\t**Kalin\u2019s response (keep working on rules using science)** has some merit. We do want to work on model rules based on scientific principles. However, when modeling a real-world system, it\u2019s not enough to just use the rules of science to make our models. We need to know that our model is actually going to work (i.e., be sufficiently accurate in outputs such as predictions) when it is applied in the real world. Real-world systems are complex. 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Then they tested their model to see how well it worked. They found their predictions were only right about half the time. The students had different ideas for improving the model.\u003C/p\u003E\r\n\u003Cp\u003EHere are the students\u0026rsquo; ideas:\u003C/p\u003E\r\n\u003Ctable cellpadding=\"30\"\u003E\r\n\u003Ctbody\u003E\r\n\u003Ctr\u003E\r\n\u003Cth colspan=\"2\"\u003E\u003Cstrong\u003EAlex\u003C/strong\u003E\u003C/th\u003E\r\n\u003Cth colspan=\"2\"\u003E\u003Cstrong\u003EDelana\u003C/strong\u003E\u003C/th\u003E\r\n\u003C/tr\u003E\r\n\u003Ctr\u003E\r\n\u003Ctd width=\"88\"\u003E\u003Cimg src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/Alex%206.png\" width=\"72\" height=\"90\" align=\"center\" hspace=\"10\" vspace=\"10\" /\u003E\u003C/td\u003E\r\n\u003Ctd style=\"padding: 10px;\" width=\"350\"\u003EWe need to run the model longer. The longer you run a computer model the better the prediction will be.\u003C/td\u003E\r\n\u003Ctd width=\"88\"\u003E\u003Cimg src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/Delana6.png\" width=\"70\" height=\"90\" align=\"center\" hspace=\"10\" vspace=\"10\" /\u003E\u003C/td\u003E\r\n\u003Ctd style=\"padding: 10px;\" width=\"350\"\u003EThere\u0026rsquo;s no way to make a computer model that can predict the weather. 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We suggest teachers review the information and think about ways to scaffold students toward developing knowledge and practice as appropriate for their classes. We also recommend emphasizing the underlying ideas and practices, rather than on vocabulary terms. By discussing the different options, students can engage in productive talk related to these computational thinking concepts without using technical terminology. \\n\\nThis assessment probe is designed to assess and scaffold students in thinking and talking about **Rule Refinement** and, especially, **Rule Testing**. **Rule Refinement** involves refining a rule for use in a modeling environment using scientific principles and incorporating additional data, making the rule more precise, computational, and/or detecting and correcting errors. **Rule Testing** is a process of \\\"calibration\\\" between the modeling environment and the observable world. It involves systematically testing a rule to detect errors and limitations, and analyzing the efficiency of various solutions.\\n\\nThe assessment is situated in the unit context to provide an opportunity for students to make sense about rule refinement and rule testing in a specific, tangible weather problem. While one of the responses makes the most sense from a practical standpoint for this problem, other responses have implicit connections to facets of computational thinking (e.g., using understanding of systems to determine model rules and iteration in modeling). Using an indefinite problem provides space for students to think and talk about different approaches to refining and testing rules for a computer model. 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We sometimes see this type of reasoning when students and even adults talk about climate change models. Some people say things like, \u201cthey are just models, so they don\u2019t really tell us what\u2019s going to happen in the real world.\u201d \\n\\nStudents who choose Delana\u2019s response could use support in developing understanding that computer models don\u2019t need to be perfect in order to be useful. No model is perfectly accurate. Models just need to be good enough for a given purpose. Computer modelers set calibration targets that define how close to the actual event they want their prediction to be (e.g., maybe they want their model to predict the correct outcome of rain or no rain for the next day 95% of the time). Uncertainty is also built into weather models for precipitation in other ways (e.g., a forecast of 70% chance of rain for a given day). Knowing that there is a 70% chance of rain tomorrow is better than not having any information about tomorrow\u2019s weather at all. Students who choose Delana\u2019s response (as well as all the other students) could benefit from conversations about and examples of what it means for a model to be \u201cgood enough\u201d to serve a purpose.\\n\\n###Middle Level \\n\u2022\\t**Alex\u2019s response (run the model longer)** suggests awareness that models are not perfect and that they can improve over time. This response may also appeal to some students who know about the idea of computer iteration (i.e., a process in which a set of instructions is repeated in a sequence multiple times or until a condition is met). Sometimes computer models need to run over time through multiple iterations to reach a certain set of criteria for the output. However, in this case, if the computer model is only making a correct prediction about half the time, then the computer needing more time to process the data probably isn\u2019t the problem. \\n\\nStudents who choose Alex\u2019s response could benefit from a discussion about whether or not they think running the model longer would help in this case.\\n\\n\u2022\\t**Kalin\u2019s response (keep working on rules using science)** has some merit. We do want to work on model rules based on scientific principles. However, when modeling a real-world system, it\u2019s not enough to just use the rules of science to make our models. We need to know that our model is actually going to work (i.e., be sufficiently accurate in outputs such as predictions) when it is applied in the real world. Real-world systems are complex. If we just go by the rules of science, we may be overlooking possible problems with either the rules of the model (e.g., omitting an important variable) or with input data (e.g., perhaps a temperature sensor is faulty or isn\u2019t calibrated correctly). In either case, just working on the rules of the model would not be enough to know that the model really works unless we check our weather model predictions against the weather that actually occurs.\\n\\n###More Formal Ideas\\n\u2022\\t**Sage\u2019s answer (refine and test model predictions using Alaska weather data)** is the only option that acknowledges the importance of using calibration to test model rules, which is essential for establishing confidence in a computer model that is designed to represent or simulate an event or phenomenon in the real world. Weather modelers need to compare their model outputs to real-world data to ascertain how well they are working. 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You are now ready to begin to apply all of that knowledge to the unit challenge:\u0026nbsp;What will the\u0026nbsp;weather\u0026nbsp;be in Anchorage 24 hours from now?\u003C/p\u003E\n\u003Cp\u003EUse the resources from your past lessons to help inform your prediction. Go to page 28 in your Science Notebooks to review the Lesson 1, Weather Radar Maps for the Alaskan Region, to help you.\u003C/p\u003E\n\u003Cp\u003E\u003Cimg src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/L1AKRADARMAPAPRIL21_7am.png\" width=\"303\" height=\"231\" /\u003E\u003Cimg src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/L1AKRADARMAPAPRIL21_1pm.png\" width=\"303\" height=\"231\" /\u003E\u003Cimg src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/L1AKRADARMAPAPRIL21_7pm.png\" width=\"303\" height=\"231\" /\u003E\u003Cimg src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/L1AKRADARMAPAPRIL22_1am.png\" width=\"297\" height=\"230\" /\u003E\u003Cimg src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/L1AKRADARMAPAPRIL22_7am.png\" width=\"303\" height=\"231\" /\u003E\u003C/p\u003E\n\u003Cp\u003E\u0026nbsp;\u003C/p\u003E", + "is_callout": false, + "is_full_width": true, + "is_hidden": false, + "name": "", + "type": "Embeddable::Xhtml", + "ref_id": "147917-Embeddable::Xhtml" + }, + "section": "header_block" + }, { + "embeddable": { + "plugin": { + "description": "", + "author_data": "{\"tipType\":\"windowShade\",\"questionWrapper\":{\"correctExplanation\":\"correct\",\"distractorsExplanation\":\"distractor\",\"exemplar\":\"exemplar\",\"teacherTip\":\"teacherTip\",\"teacherTipImageOverlay\":\"\"},\"windowShade\":{\"windowShadeType\":\"theoryAndBackground\",\"layout\":\"mediaLeft\",\"initialOpenState\":false,\"content\":\"###LESSON 6: MODELING FRONTS\\n**HOW DO FRONTS MOVE?**\\n\\nIn this lesson, students identify the location, direction, and rate of movement of the front. 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In this activity, students use front visualizations from 11 am, 9 pm, and 7 am to see where the air masses are colliding (i.e., the front) at different times and to track the direction of the front. The specific computational thinking skills highlighted and practiced in this activity are **Decomposition**, **Pattern Recognition**, and **Model Evaluation**.\\n\\n###Activity Breakdown\\n\\n1.Play the Lesson 6 Virtual Model tutorial.\\n\\n2.Research teams use the Front Visualizations in their Science Notebooks and the Alaska Map Transparency to describe the direction the front is moving.\\n\\n3.In the student online activity, teams summarize their findings for the direction the front is moving within the region.\",\"content2\":\"\",\"mediaType\":\"none\",\"mediaCaption\":\"Last, First. \\\"Title of Work.\\\" Year created. Site Title [OR] Publisher. 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Strategy Tips \\nThe intention of this task is to provide students with a more open-ended task than seen in Lessons 1 - 4 and to give them an opportunity to apply their CT skills before solving the unit challenge. It is important that students work independently. The goal is to see if students can decompose the mini front challenge on their own. Additionally, this shift in perspective gives the students agency in their own learning to identify which CT skills are key to addressing this question. Students should realize that they know how to identify a front from Lesson 4, and have data at their disposal that can help them figure out the location of the front is at different points in time. Ideally, they will decompose \u201chow the front moves\u201d into two components: direction (which way it is heading) and speed (distance/time). Please see a list of possible discussion prompts to guide students through this process:\\n\\n\\n* Remind students that they learned how to identify a front in the last lesson, and that fronts can be an indicator of complex weather. \\n\\n* Point out that the unit challenge is to make a decision on if they are to continue, cancel, or postpone the Native Youth Olympics (NYO Games) and explain to them that figuring out where this front will be in 24 hours can help improve their prediction.\\n\\n* Raise the question: What do we need to know about the front to predict where it will be in the future? \\n\\n* Ask the research teams to:\\n\\n * Think about the question and brainstorm their ideas as a group.\\n * Identify the computational thinking skills they think will help them address this challenge. \\n\\n * Identify what features in the Virtual Model would help them answer this question. \\n * Identify what data they have from Lessons 1 - 5 that would help them answer this question.\\n* Have research teams answer the online activity questions.\",\"content2\":\"\",\"mediaType\":\"none\",\"mediaCaption\":\"Last, First. \\\"Title of Work.\\\" Year created. 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So you may be wondering when it\u0026rsquo;s going to pass through there. Where the\u0026nbsp;front\u0026nbsp;is at the time of the Alaskan Native Youth Olympics (NYO Games) will greatly affect the\u0026nbsp;weather.\u003C/p\u003E\n\u003Cp\u003ETo best predict where the\u0026nbsp;front\u0026nbsp;will be in 24 hours, you will need to figure out how fast it is moving. This is a calculation of speed (distance over time). Once you know both speed and direction (from Activity 1) of the\u0026nbsp;front, your\u0026nbsp;weather\u0026nbsp;analysis will help you answer the question \u0026ldquo;How fast is the\u0026nbsp;front\u0026nbsp;moving?\u0026rdquo;\u003C/p\u003E\n\u003Cp\u003EYou will have the following tools to help you:\u003C/p\u003E\n\u003Cp\u003E\u0026bull; Your\u0026nbsp;front images from the Virtual Model\u003Cbr /\u003E\u0026bull; A regional map transparency\u003Cbr /\u003E\u0026bull; Rulers and pens\u003C/p\u003E", + "is_callout": false, + "is_full_width": true, + "is_hidden": false, + "name": "", + "type": "Embeddable::Xhtml", + "ref_id": "147919-Embeddable::Xhtml" + }, + "section": "header_block" + }, { + "embeddable": { + "content": "\u003Cp\u003EUsing the available materials, develop a strategy for calculating the rate of the\u0026nbsp;front. Remember that speed equals distance an object moves divided by the time it takes the object to move to its new location.\u003C/p\u003E\r\n\u003Cp style=\"padding-left: 30px;\"\u003E\u003Cstrong\u003E\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Speed = Distance/Time\u003C/strong\u003E\u003C/p\u003E", + "is_callout": true, + "is_full_width": true, + "is_hidden": false, + "name": "TASK ", + "type": "Embeddable::Xhtml", + "ref_id": "147920-Embeddable::Xhtml" + }, + "section": null + }, { + "embeddable": { + "default_text": "", + "give_prediction_feedback": false, + "hint": "\u003Cp\u003E\u0026bull; Your answer should be a rate or speed.\u003C/p\u003E\r\n\u003Cp\u003E\u0026bull; Speed is a measurement of distance over time.\u003C/p\u003E\r\n\u003Cp\u003E\u0026bull; Distance can be measured in units of kilometers, miles, etc.\u003C/p\u003E\r\n\u003Cp\u003E\u0026bull; Time can be measured in hours, days, etc.\u003C/p\u003E", + "is_full_width": true, + "is_hidden": false, + "is_prediction": false, + "name": "", + "prediction_feedback": "", + "prompt": "\u003Cp\u003EHow fast is the\u0026nbsp;front\u0026nbsp;moving? Be as specific as you can.\u003C/p\u003E", + "show_in_featured_question_report": true, + "type": "Embeddable::OpenResponse", + "ref_id": "208896-Embeddable::OpenResponse" + }, + "section": null + }, { + "embeddable": { + "default_text": "", + "give_prediction_feedback": false, + "hint": "\u003Cp\u003E\u0026bull; Explain your strategy.\u003C/p\u003E\r\n\u003Cp\u003E\u0026bull; Talk about what you did to come up with your answer.\u003C/p\u003E", + "is_full_width": true, + "is_hidden": false, + "is_prediction": false, + "name": "", + "prediction_feedback": "", + "prompt": "\u003Cp\u003EDescribe how your team figured out how fast the\u0026nbsp;front\u0026nbsp;is moving.\u003C/p\u003E", + "show_in_featured_question_report": true, + "type": "Embeddable::OpenResponse", + "ref_id": "208897-Embeddable::OpenResponse" + }, + "section": null + }, { + "embeddable": { + "plugin": { + "description": "", + "author_data": "{\"tipType\":\"windowShade\",\"questionWrapper\":{\"correctExplanation\":\"correct\",\"distractorsExplanation\":\"distractor\",\"exemplar\":\"exemplar\",\"teacherTip\":\"teacherTip\",\"teacherTipImageOverlay\":\"\"},\"windowShade\":{\"windowShadeType\":\"theoryAndBackground\",\"layout\":\"mediaLeft\",\"initialOpenState\":false,\"content\":\"###Activity 2 - How Fast is the Front Moving?\\n\\nThe focus of this activity is for students to analyze the visualization data they generated in Activity 1 and to develop a statement defining the speed of the front moving across the region. The activity ends with research teams developing a description of how fast the front is moving and recording it in the student online activity. The specific computational thinking practice highlighted and practiced in this activity is **Pattern Recognition**.\\n\\n\u003Cbr\u003E**1. Calculate the speed the front is moving.**\\n\\n* Pass out to the research teams their Science Notebooks with the front visualizations, Regional Map Transparency, wet erase markers, paper towels, and rulers. \\n\\n* Students may also want to use the [L1A2: Alaska Weather Station Data Sheet](https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/L1A2_WeatherStationDataAK.png) and the [L4A1: Alaska Additional Weather Stations handouts](https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/L4A1_AdditionalWeatherStationsDataSheet_AK.png). \\n\\n* The primary challenge for students will be deciding where on the front to use as a reference point when measuring the distance that it moves from timestamp to timestamp. 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This event has been planned for months and the committee is expecting over 500 people to attend. One of your jobs on this committee is to watch the\u0026nbsp;weather\u0026nbsp;and determine if the event is safe to proceed as\u0026nbsp;planned, or if it should be\u0026nbsp;postponed\u0026nbsp;or\u0026nbsp;even canceled.\u003C/p\u003E\n\u003Cp\u003EIt\u0026rsquo;s time to put your computational thinking skills to work!\u003C/p\u003E", + "is_callout": false, + "is_full_width": true, + "is_hidden": false, + "name": "", + "type": "Embeddable::Xhtml", + "ref_id": "147923-Embeddable::Xhtml" + }, + "section": "header_block" + }, { + "embeddable": { + "plugin": { + "description": "", + "author_data": "{\"tipType\":\"windowShade\",\"questionWrapper\":{\"correctExplanation\":\"correct\",\"distractorsExplanation\":\"distractor\",\"exemplar\":\"exemplar\",\"teacherTip\":\"teacherTip\",\"teacherTipImageOverlay\":\"\"},\"windowShade\":{\"windowShadeType\":\"theoryAndBackground\",\"layout\":\"mediaLeft\",\"initialOpenState\":false,\"content\":\"###LESSON 7: ANALYZING DATA AND MAKING A PREDICTION\\n\\n**What will the local weather be 24 hours from now?**\\n\\nIn this lesson, students revisit the unit challenge and the original question posted to them in Lesson 1, \\\"Should the NYO Games proceed as planned, be postponed or canceled?\\\" Students assume the role of weather forecasters and make a weather prediction for Anchorage on April 23 at 7 am using regional data and models they have been exploring throughout this unit. 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Although we have not named the skill until now, notice in the table below the skills you have used to help decide if the NYO Games should proceed.\u003C/p\u003E\r\n\u003Ctable cellpadding=\"30\"\u003E\r\n\u003Ctbody\u003E\r\n\u003Ctr bgcolor=\"#D3D3D3\"\u003E\r\n\u003Cth style=\"border: 1px solid black;\" colspan=\"1\"\u003E\u003Cstrong\u003EDefinition\u003C/strong\u003E\u003C/th\u003E\r\n\u003Cth style=\"border: 1px solid black;\" colspan=\"1\"\u003E\u0026nbsp;\u003C/th\u003E\r\n\u003Cth style=\"border: 1px solid black;\" colspan=\"1\"\u003E\u003Cstrong\u003EComputational Thinking Skill\u003C/strong\u003E\u003C/th\u003E\r\n\u003C/tr\u003E\r\n\u003Ctr\u003E\r\n\u003Ctd style=\"border: 1px solid black; padding: 20px;\" width=\"300\"\u003E\r\n\u003Cp style=\"text-align: left;\"\u003EOrganizing a large amount of information (data) into smaller more manageable parts.\u003C/p\u003E\r\n\u003C/td\u003E\r\n\u003Ctd style=\"border: 1px solid black; text-align: center;\" width=\"250\"\u003E\u003Cimg src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/Glossary/ct-decomposition.jpg\" width=\"235\" height=\"132\" /\u003E\u003C/td\u003E\r\n\u003Ctd style=\"border: 1px solid black; text-align: center; padding: 20px;\" width=\"300\"\u003E\r\n\u003Cp\u003E\u003Cstrong\u003EDecomposition\u003C/strong\u003E\u003C/p\u003E\r\n\u003Cp\u003EIn \u003Cstrong\u003ELesson 1, \u003C/strong\u003Eyou organized weather station data over a two-day period and radar maps of Alaska every 6 hours to make a prediction.\u003C/p\u003E\r\n\u003C/td\u003E\r\n\u003C/tr\u003E\r\n\u003Ctr style=\"border: 1px solid black; text-align: center;\"\u003E\r\n\u003Ctd style=\"border: 1px solid black; padding: 20px;\" width=\"300\"\u003E\r\n\u003Cp style=\"text-align: left;\"\u003ERecognizing that data or information is repeating in a logical (expected) way.\u003C/p\u003E\r\n\u003C/td\u003E\r\n\u003Ctd style=\"border: 1px solid black;\" width=\"250\"\u003E\u003Cimg src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/Captioned_Videos/new_picts/Lesson_5_new_Embedded_assessment/Netlogo_temp_model.png\" width=\"159\" height=\"181\" /\u003E\u003C/td\u003E\r\n\u003Ctd style=\"border: 1px solid black; padding: 20px;\" width=\"300\"\u003E\r\n\u003Cp style=\"text-align: center;\"\u003E\u003Cstrong\u003EPattern Recognition\u003C/strong\u003E\u003C/p\u003E\r\n\u003Cp\u003EIn \u003Cstrong\u003ELesson 2\u003C/strong\u003E, you ran the model to see temperature data and patterns of data moving across the map. Before and after each run of the model, you interpolated data. You discovered that warm and cold spots on the map are at times on certain sides, and also you saw these spots change location over time.\u003C/p\u003E\r\n\u003Cp\u003EIn\u003Cstrong\u003E Lesson 3 and 4\u003C/strong\u003E, you ran the models to develop a general statement to answer the question \"Where does it rain?\".\u003C/p\u003E\r\n\u003C/td\u003E\r\n\u003C/tr\u003E\r\n\u003Ctr style=\"border: 1px solid black; text-align: center;\"\u003E\r\n\u003Ctd style=\"border: 1px solid black; padding: 20px;\" width=\"300\"\u003E\r\n\u003Cp style=\"text-align: left;\"\u003EEstimating an unknown value based on surrounding information.\u003C/p\u003E\r\n\u003C/td\u003E\r\n\u003Ctd style=\"border: 1px solid black;\" width=\"250\"\u003E\u003Cimg class=\"\" src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/Glossary/interpolation.jpg\" alt=\"\" width=\"206\" height=\"117\" /\u003E\u003C/td\u003E\r\n\u003Ctd style=\"border: 1px solid black; padding: 20px;\" width=\"300\"\u003E\r\n\u003Cp style=\"text-align: center;\"\u003E\u003Cstrong\u003EInterpolation\u003C/strong\u003E\u003C/p\u003E\r\n\u003Cp style=\"text-align: center;\"\u003EIn \u003Cstrong\u003ELesson 2\u003C/strong\u003E, you made best guess estimates of the temperatures that were missing on the map.\u003C/p\u003E\r\n\u003C/td\u003E\r\n\u003C/tr\u003E\r\n\u003Ctr style=\"border: 1px solid black; text-align: center;\"\u003E\r\n\u003Ctd style=\"border: 1px solid black; padding: 20px;\" width=\"300\"\u003E\r\n\u003Cp style=\"text-align: left;\"\u003EFollowing a pattern beyond the known data points.\u003C/p\u003E\r\n\u003C/td\u003E\r\n\u003Ctd style=\"border: 1px solid black;\" width=\"250\"\u003E\u003Cimg src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/Glossary/exptrapolation.jpg\" width=\"205\" height=\"116\" /\u003E\u003C/td\u003E\r\n\u003Ctd style=\"border: 1px solid black; padding: 20px;\" width=\"300\"\u003E\r\n\u003Cp style=\"text-align: center;\"\u003E\u003Cstrong\u003EExtrapolation\u003C/strong\u003E\u003C/p\u003E\r\n\u003Cp style=\"text-align: center;\"\u003EIn \u003Cstrong\u003ELesson 2\u003C/strong\u003E, you predicted future weather based on patterns you observed in the changing temperatures you collected and visualized.\u003C/p\u003E\r\n\u003C/td\u003E\r\n\u003C/tr\u003E\r\n\u003Ctr style=\"border: 1px solid black; text-align: center;\"\u003E\r\n\u003Ctd style=\"border: 1px solid black; 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The students are looking at the map below and have different ideas for estimating the temperature at the location marked X using the recorded temperatures of 31\u02da and 59\u02da.\u003C/p\u003E\r\n\u003Cp\u003E\u003Cimg class=\"\" style=\"display: block; margin-left: auto; margin-right: auto;\" src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/L2AssessmentQ.png\" alt=\"\" width=\"550\" height=\"62\" /\u003E\u003C/p\u003E\r\n\u003Cp\u003EHere are the students\u0026rsquo; ideas:\u003C/p\u003E\r\n\u003Ctable cellpadding=\"30\"\u003E\r\n\u003Ctbody\u003E\r\n\u003Ctr\u003E\r\n\u003Cth colspan=\"2\"\u003E\u003Cstrong\u003EAlex\u003C/strong\u003E\u003C/th\u003E\r\n\u003Cth colspan=\"2\"\u003E\u003Cstrong\u003EDelana\u003C/strong\u003E\u003C/th\u003E\r\n\u003C/tr\u003E\r\n\u003Ctr\u003E\r\n\u003Ctd width=\"88\"\u003E\u003Cimg src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/Alex1.png\" width=\"60\" height=\"88\" align=\"center\" hspace=\"10\" vspace=\"10\" /\u003E\u003C/td\u003E\r\n\u003Ctd style=\"padding: 10px;\" width=\"350\"\u003EWe should use the number that is exactly halfway in between 31\u02daand 59\u02da. That\u0026rsquo;s the most exact way to estimate.\u003C/td\u003E\r\n\u003Ctd width=\"88\"\u003E\u003Cimg src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/Delana1.png\" width=\"65\" height=\"92\" align=\"center\" hspace=\"10\" vspace=\"10\" /\u003E\u003C/td\u003E\r\n\u003Ctd style=\"padding: 10px;\" width=\"350\"\u003EWe should mark a number line along the map with the estimate in each square going up the same amount between 31\u02da and 59\u02da. That\u0026rsquo;d be the best estimate.\u003C/td\u003E\r\n\u003C/tr\u003E\r\n\u003C/tbody\u003E\r\n\u003Ctbody\u003E\r\n\u003Ctr\u003E\r\n\u003Cth colspan=\"2\"\u003E\u003Cstrong\u003EKalin\u003C/strong\u003E\u003C/th\u003E\r\n\u003Cth colspan=\"2\"\u003E\u003Cstrong\u003ESage\u003C/strong\u003E\u003C/th\u003E\r\n\u003C/tr\u003E\r\n\u003Ctr\u003E\r\n\u003Ctd width=\"88\"\u003E\r\n\u003Cp\u003E\u003Cimg src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/Kalin.png\" width=\"65\" height=\"88\" align=\"center\" hspace=\"10\" vspace=\"10\" /\u003E\u003C/p\u003E\r\n\u003C/td\u003E\r\n\u003Ctd style=\"padding: 10px;\" width=\"350\"\u003EIt doesn\u0026rsquo;t make sense to estimate the temperature at the X. We\u0026rsquo;d need to go there and measure the temperature. 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Pre-Assessment*\\nDuring the pre-assessment, each student will view the probe and make an individual choice. The request for explanation will only be on the post-assessment. After students make an individual commitment for the pre-assessment, you can lead a discussion including, for example, a pair/share opportunity and/or full class discussion. \\n\\nAt this time, encourage students to share and discuss their ideas and reasons without indicating that any one answer is better or worse. Let the students know that they should keep thinking about this question and that the class will return to it at the end of the lesson.\\n\",\"content2\":\"\",\"mediaType\":\"none\",\"mediaCaption\":\"Last, First. \\\"Title of Work.\\\" Year created. Site Title [OR] Publisher. 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Review the information and consider ways to scaffold students toward developing knowledge and practice as appropriate for their classes. We also recommend during the first implementation of the probe, you scaffold students to focus on student ideas about this problem, rather than on vocabulary terms such as **interpolation**. By discussing the different options, students can engage in productive talk related to data sense making and computational thinking without using technical terminology. 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The students are looking at the map below and have different ideas for estimating the temperature at the location marked X using the recorded temperatures of 31\u02da and 59\u02da.\u003C/p\u003E\r\n\u003Cp\u003E\u003Cimg class=\"\" style=\"display: block; margin-left: auto; margin-right: auto;\" src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/L2AssessmentQ.png\" alt=\"\" width=\"550\" height=\"62\" /\u003E\u003C/p\u003E\r\n\u003Cp\u003EHere are the students\u0026rsquo; ideas:\u003C/p\u003E\r\n\u003Ctable cellpadding=\"30\"\u003E\r\n\u003Ctbody\u003E\r\n\u003Ctr\u003E\r\n\u003Cth colspan=\"2\"\u003E\u003Cstrong\u003EAlex\u003C/strong\u003E\u003C/th\u003E\r\n\u003Cth colspan=\"2\"\u003E\u003Cstrong\u003EDelana\u003C/strong\u003E\u003C/th\u003E\r\n\u003C/tr\u003E\r\n\u003Ctr\u003E\r\n\u003Ctd width=\"88\"\u003E\u003Cimg src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/Alex1.png\" width=\"60\" height=\"88\" align=\"center\" hspace=\"10\" vspace=\"10\" /\u003E\u003C/td\u003E\r\n\u003Ctd style=\"padding: 10px;\" width=\"350\"\u003EWe should use the number that is exactly halfway in between 31\u02daand 59\u02da. That\u0026rsquo;s the most exact way to estimate.\u003C/td\u003E\r\n\u003Ctd width=\"88\"\u003E\u003Cimg src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/Delana1.png\" width=\"65\" height=\"92\" align=\"center\" hspace=\"10\" vspace=\"10\" /\u003E\u003C/td\u003E\r\n\u003Ctd style=\"padding: 10px;\" width=\"350\"\u003EWe should mark a number line along the map with the estimate in each square going up the same amount between 31\u02da and 59\u02da. 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You can\u0026rsquo;t be confident unless you measure it.\u003C/td\u003E\r\n\u003Ctd width=\"88\"\u003E\r\n\u003Cp\u003E\u003Cimg src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/Sage1.png\" width=\"65\" height=\"92\" align=\"center\" hspace=\"8\" vspace=\"8\" /\u003E\u003C/p\u003E\r\n\u003C/td\u003E\r\n\u003Ctd style=\"padding: 10px;\" width=\"350\"\u003EThe X is closer to the 59\u02da than to the 31\u02da, so let\u0026rsquo;s choose a number closer to 59\u02da. 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Pre-Assessment*\\nDuring the pre-assessment, each student will view the probe and make an individual choice. The request for explanation will only be on the post-assessment. After students make an individual commitment for the pre-assessment, you can lead a discussion including, for example, a pair/share opportunity and/or full class discussion. \\n\\nAt this time, encourage students to share and discuss their ideas and reasons without indicating that any one answer is better or worse. Let the students know that they should keep thinking about this question and that the class will return to it at the end of the lesson.\\n\",\"content2\":\"\",\"mediaType\":\"none\",\"mediaCaption\":\"Last, First. \\\"Title of Work.\\\" Year created. Site Title [OR] Publisher. 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Review the information and consider ways to scaffold students toward developing knowledge and practice as appropriate for their classes. We also recommend during the first implementation of the probe, you scaffold students to focus on student ideas about this problem, rather than on vocabulary terms such as **interpolation**. By discussing the different options, students can engage in productive talk related to data sense making and computational thinking without using technical terminology. 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She will discuss how temperature plays an important part in predicting weather.\u003C/p\u003E", + "is_callout": true, + "is_full_width": true, + "is_hidden": false, + "name": "", + "type": "Embeddable::Xhtml", + "ref_id": "147936-Embeddable::Xhtml" + }, + "section": "header_block" + }, { + "embeddable": { + "name": "", + "url_fragment": null, + "authored_state": "{\"version\":1,\"questionType\":\"iframe_interactive\",\"videoUrl\":\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/Captioned_Videos/JackieLesson2_88_Captioned.mp4\",\"poster\":\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/Captioned_Videos/Posters/Poster_L2_Video.png\"}", + "is_hidden": false, + "is_full_width": true, + "show_in_featured_question_report": true, + "inherit_aspect_ratio_method": true, + "custom_aspect_ratio_method": null, + "inherit_native_width": true, + "custom_native_width": 576, + "inherit_native_height": true, + "custom_native_height": 435, + "inherit_click_to_play": true, + "custom_click_to_play": false, + "inherit_full_window": true, + "custom_full_window": false, + "inherit_click_to_play_prompt": true, + "custom_click_to_play_prompt": null, + "inherit_image_url": true, + "custom_image_url": null, + "library_interactive": { + "hash": "34e1a2a39c058da8ff4ffe5a09ad14af337c4a01", + "data": { + "aspect_ratio_method": "DEFAULT", + "authoring_guidance": "", + "base_url": "https://models-resources.concord.org/question-interactives/version/v1.1.0/video-player/", + "click_to_play": false, + "click_to_play_prompt": null, + "description": "This video player will not have the blue header bar above the interactive.\r\nIt does not save the students position in the video. \r\nIt will not show up in the teacher report.", + "enable_learner_state": false, + "full_window": false, + "has_report_url": false, + "image_url": null, + "name": "Video Player", + "native_height": 435, + "native_width": 576, + "no_snapshots": false, + "show_delete_data_button": false, + "thumbnail_url": "", + "customizable": false, + "authorable": true + } + }, + "type": "ManagedInteractive", + "ref_id": "1705-ManagedInteractive", + "linked_interactives": [] + }, + "section": "header_block" + }] + }, { + "additional_sections": null, + "embeddable_display_mode": "stacked", + "id": 143207, + "is_completion": false, + "is_hidden": false, + "layout": "l-full-width", + "name": "Opening", + "position": 2, + "show_header": true, + "show_info_assessment": true, + "show_interactive": false, + "show_sidebar": false, + "sidebar": null, + "sidebar_title": "Did you know?", + "toggle_info_assessment": false, + "embeddables": [{ + "embeddable": { + "content": "\u003Cp\u003EHave you ever wondered why some temperature displays are in color (for instance, television weather reports), but a thermometer displays temperature in numbers? Or how weather apps can tell you what the temperature is wherever you are? In this lesson, you are going to learn what it means to display temperature for mainland Alaska.\u003C/p\u003E\r\n\u003Cp\u003EAs\u0026nbsp; weather scientists (meteorologists), you will experience a virtual storm event in your classroom. As the virtual storm event occurs, you and your research team will collect and record temperature data.\u0026nbsp;\u003C/p\u003E\r\n\u003Cp\u003EAs part of your lesson challenge, you will need to determine how to capture the data, how to organize the data, and how the data should be displayed. 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A weather station collects data about the current weather at a specific location. The strategic placement of multiple stations and use of digital tools and mathematical concepts allows weather scientists to create a more accurate and complete model/visualization of the weather over a region and analyze it for patterns and trends. \\n\\n**LEARNING GOALS**\\n\\nStudents will be able to:\\n\\n* Take a limited amount of information and develop a more complete picture of the weather (create a weather visualization)\\n\\n* Explain a weather map using traditional weather symbols and codes (weather stations with temperature)\\n\\n* Make minimally informed predictions about future weather events\\n\\n* Explain that weather varies over time\\n\\nComputational Thinking (CT) Skills introduced in this lesson can be found in the table below:\\n\\n| CT Skill | Definition | Use in Lesson |\\n|---------------------|------------------------------------------------------------------------------------------------|-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|\\n| Data Aggregation | Describes the data collection and organization process you use to better understand the topic. | Students will collect temperature data from tablet/laptop and organize the data in charts on the wall. |\\n| Data Abstraction | Simplifying data to make it easier to interpret and find patterns. | Students will come up with a color scheme for temperature and change how the data is represented from numbers to temperature categories, and then to colors. |\\n| Interpolation | Estimating an unknown value based on surrounding information. | Students will make best guess estimates of the temperatures that are missing on the map. |\\n| Pattern Recognition | Recognizing that data or information is repeating in a logical (expected) way. | Students collect data in two rounds and see patterns of data moving across the charts. Before and after each data collection they will interpolate data. They will discover that warm and cold spots on the map are consistently on certain sides, and also see these spots change over time. |\\n| Extrapolation | Following a pattern beyond the known data points. | Students predict future weather based on patterns they observe in the changing temperatures they collected and visualized. |\\n \",\"content2\":\"\",\"mediaType\":\"none\",\"mediaCaption\":\"Last, First. \\\"Title of Work.\\\" Year created. Site Title [OR] Publisher. 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(10 mins)\\n\\n### MATERIALS AND SET-UP\\nActivity 1 - Virtual Storm: Displaying Temperature Data\\n \\nThis activity requires significant setup time and you may want to plan a few hours to transform the classroom into a 7x7 gridded space and to test and set up the iPads/laptops. \\n\\n**Per Research Team (2-4 students):**\\n\\n* Marker\\n* 3\\\" x 3\\\" sticky notes in the following colors: blue, green, yellow, red, purple, orange\\n* Fully charged and connected iPad/laptop that can display the online activity\\n* Set of colored pencils (for individual student sheets)\\n\\n**Per Class:**\\n\\n* Click [HERE](https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/GraphCoordinates_AK.pdf) and print \u201cA-G\u201d and \\\"1-7\\\" coordinates in the largest font possible.\\n\\n* Push desks to walls to get as much open space in your classroom as possible.\\n\\n* Tape labels to the classroom walls, evenly spaced. Make sure the letters are on opposite walls and the numbers on walls opposite, mirroring each other. See image below for an example:\\n\\n\\n\\n* Students should be able to stand in the grid. For example, the smiley face represents a student standing in G6. Adapt the grid points to what you have available in your learning space.\\n\\n**Weather maps:**\\n\\n* Place four large poster-sized sheets of gridded paper on a classroom wall, organizing the chart paper in a row. Each sheet will contain a 7 x 7 grid with axes labeled to match the room set-up. Click [HERE](https://youtu.be/HD_6BAHib1A) to watch a tutorial on how to create weather map grids for your classroom. \\n\\n* Label the top of each sheet with a different time: 7:00 am, 11:00 am, 3:00 pm, and 7:00 pm, and organize them on the wall in order of the time.\\n\\n* Have students track the virtual weather event and record their group's data on the tracking sheet in their Science Notebook.\\n\\n**City Markers:**\\n\\n* Print five city markers by clicking [HERE - PDF](https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/GraphCoordinates_AK.pdf)\\n\\n* Place \\\"City Markers\\\" on the floor in the appropriate classroom grid locations that correspond to the map shown in the image below:\\n\\n\",\"content2\":\"\",\"mediaType\":\"none\",\"mediaCaption\":\"Last, First. \\\"Title of Work.\\\" Year created. Site Title [OR] Publisher. 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Anchorage, AK. \",\"mediaURL\":\"https://precipitatingchange-resources.concord.org/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/JackieLesson2_88.mp4\"}}", + "approved_script_label": "teacherEditionTips", + "component_label": "windowShade", + "approved_script": { + "name": "Teacher Edition", + "url": "https://teacher-edition-tips-plugin.concord.org/version/v3.6.0/plugin.js", + "label": "teacherEditionTips", + "description": "This plugin provides Teacher Edition components", + "version": 3, + "json_url": "https://teacher-edition-tips-plugin.concord.org/version/v3.6.0/manifest.json", + "authoring_metadata": "{\"components\":[{\"label\":\"windowShade\",\"name\":\"Window Shades\",\"scope\":\"embeddable\",\"guiAuthoring\":true},{\"label\":\"sideTip\",\"name\":\"Side Tips\",\"scope\":\"embeddable\",\"guiAuthoring\":true},{\"label\":\"questionWrapper\",\"name\":\"Question Wrapper\",\"scope\":\"embeddable-decoration\",\"decorates\":[\"Embeddable::MultipleChoice\",\"Embeddable::OpenResponse\",\"Embeddable::ImageQuestion\",\"ManagedInteractive\",\"MwInteractive\",\"ImageInteractive\",\"VideoInteractive\"],\"guiAuthoring\":true,\"guiPreview\":true}]}" + } + }, + "is_hidden": true, + "is_full_width": true, + "type": "Embeddable::EmbeddablePlugin", + "ref_id": "9761-Embeddable::EmbeddablePlugin" + }, + "section": null + }] + }, { + "additional_sections": {}, + "embeddable_display_mode": "stacked", + "id": 143208, + "is_completion": false, + "is_hidden": false, + "layout": "l-full-width", + "name": "Weather Station - Data", + "position": 3, + "show_header": true, + "show_info_assessment": true, + "show_interactive": true, + "show_sidebar": false, + "sidebar": null, + "sidebar_title": "Did you know?", + "toggle_info_assessment": false, + "embeddables": [{ + "embeddable": { + "content": "\u003Cp\u003EAs scientists, it is important to record temperature data for analysis and to predict future\u0026nbsp;weather\u0026nbsp;events.\u0026nbsp;\u003C/p\u003E", + "is_callout": false, + "is_full_width": true, + "is_hidden": false, + "name": "Displaying Temperature", + "type": "Embeddable::Xhtml", + "ref_id": "149056-Embeddable::Xhtml" + }, + "section": "header_block" + }, { + "embeddable": { + "content": "\u003Cp\u003EGather information from each weather station shown on the map below. Click\u0026nbsp;\u003Cem\u003ESetup\u003C/em\u003E and \u003Cem\u003ERun.\u003C/em\u003E\u0026nbsp;Then click each weather station to see the temperature observed for the communities across Alaska at the given time.\u003C/p\u003E\r\n\u003Cp\u003EThe boxes on the grid are called \u003Cem\u003Ecells\u003C/em\u003E and are identified with a letter and a number.\u0026nbsp;\u003C/p\u003E", + "is_callout": true, + "is_full_width": true, + "is_hidden": false, + "name": "TASK", + "type": "Embeddable::Xhtml", + "ref_id": "149057-Embeddable::Xhtml" + }, + "section": "header_block" + }, { + "embeddable": { + "plugin": { + "description": "", + "author_data": "{\"tipType\":\"windowShade\",\"questionWrapper\":{\"correctExplanation\":\"correct\",\"distractorsExplanation\":\"distractor\",\"exemplar\":\"exemplar\",\"teacherTip\":\"teacherTip\",\"teacherTipImageOverlay\":\"\"},\"windowShade\":{\"windowShadeType\":\"theoryAndBackground\",\"layout\":\"mediaLeft\",\"initialOpenState\":false,\"content\":\"### Activity 1 - Virtual Storm: Visualizing Temperature \\n\\nIn this activity, students simulate the experience of a weather scientist collecting weather data for a large area and organizing it into useful maps to predict a future weather event. Students collaboratively negotiate what the data means, as well as how to accurately record the data and represent it so they can use the emerging pattern to predict a future weather event. The specific computational thinking practices highlighted and practiced in this activity are **Data Aggregation**, **Abstraction**, and **Interpolation**.\\n\\n###Activity Breakdown\\n**1. Setting the stage for the virtual storm.** The grid in the classroom represents a smaller region in Alaska than the area covered in the Lesson 1 radar images. This area includes the following cities: Bettles, Gelena, Nome, Noorvik, and St. Mary\u2019s. In their research teams, students collect temperature data every four hours throughout the region for an eight-hour period of time. \\n\\n* Have a student stand in a square and ask the class to identify the coordinates of where they are standing. Repeat until clear.\\n\\n**2. Round 1 - Starting the Virtual Storm technology. **\\n\\n* Ask research teams to select a student from their team to move to an unoccupied grid cell. \\n\\n* Launch the Virtual Storm technology and have another student from the team record the temperature in the selected cell onto the poster sheet labeled \\\"7:00 am.\\\" \\n\\n* Click \\\"PLAY\\\" on the Virtual Storm technology. Instruct the students to watch the clock in the Weather Sensor, and every four hours record the temperature readings onto the corresponding poster sheets on the walls (7:00 am, 11:00 am, 3:00 pm). After this round, all posters should have eight squares filled in. \\n\\n**3. Round 2 - Students gaining practice by repeating the process.**\\n\\n* Click the \u201cRESET\u201d button. Ask research groups to choose new positions on the grid. \\n* Run the simulation and encourage students to collect and record the data on the three maps again. At the end of this round, each chart should have 16 squares filled in on each chart.\\n\\n**4. Round 3 - Be more strategic.**\\n\\n* Let the research teams rethink their position and either stay or move to a more strategically chosen position.\\n\\n* Run the simulation again, asking students to record the data on three charts. At the end of this round, 24 squares should be filled in with temperature data.\\n\\n** 5. Class Discussion - Emerging patterns \u0026 abstraction.**\\n\\n* Help students develop a color scheme of their choosing, and suggest colored sticky notes for the scheme. Honor the way students want to do it and post the scheme on the wall. For example, students might come up with six temperature categories:\\n * 10-19\u00b0F/-12.2 to -7.2\u00b0C: purple (extremely cold)\\n * 20-29\u00b0F/-6.7 to -1.7\u00b0C: blue (very cold)\\n * 30-39\u00b0F/-1.1 to 3.9\u00b0C: green (cold)\\n * 40-49\u00b0F/4.4 to 9.4\u00b0C: yellow (cool)\\n * 50-59\u00b0F/10 to 15\u00b0C: orange (warm)\\n * 60-69\u00b0F/15.6 to 20.6\u00b0C: red (very warm)\\n\\n* Before going on, have students place the colored sticky notes with the temperatures written on them over the original temperatures. Each team is responsible for their first three postings. \\n\\n** 6. Round 4 - Interpolation test.** \\n\\n* Direct the research teams to choose a new positions on the grid and ask them to take a **\\\"GUESS\\\"** of what the temperature will be for each of the charts.\\n\\n* Run the simulation. Students use the correct colored post-it note for the actual temperature and write **\u201cACTUAL\u201d** on the note and place it over their previous guesses. 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Scientists have many methods for constructing unknown data between known data points. This is called data\u0026nbsp;interpolation.\u003C/p\u003E\n\u003Cp\u003EThere are many different methods to interpolate data. Let\u0026rsquo;s look at the three\u0026nbsp;interpolation\u0026nbsp;methods used to make these maps.\u003C/p\u003E\n\u003Cp\u003E\u003Cimg class=\"\" src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/images/AKABCinterpolationtemp.jpg\" alt=\"\" width=\"484\" height=\"383\" /\u003E\u003C/p\u003E\n\u003Cp\u003E\u003Cstrong\u003ENearest Neighbor Interpolation\u003C/strong\u003E\u003C/p\u003E\n\u003Cp\u003EFor Square A, you may have guessed 54\u0026deg;F degrees or something very close to that. This is the simplest\u0026nbsp;interpolation\u0026nbsp;method. It is called\u0026nbsp;\u003Cstrong\u003ENearest Neighbor\u003C/strong\u003E. With this method, you find the nearest\u0026nbsp;weather station to the unknown point and assume it has a similar temperature.\u003C/p\u003E\n\u003Cp\u003E\u003Cbr /\u003E\u003Cstrong\u003ELinear Interpolation\u003C/strong\u003E\u003C/p\u003E\n\u003Cp\u003EFor Square B, you may have guessed between 38\u0026deg;F and 50\u0026deg;F, but closer to 50\u0026deg;F. Since this square is between two known temperatures, the unknown temperature is probably between 38\u0026deg;F and 50\u0026deg;F. To be even closer, you can think of it like a number line with temperature in each square increasing by four degrees.\u003C/p\u003E\n\u003Cp\u003E\u003Cimg class=\"\" src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/images/AKlinearinterpolation.jpg\" alt=\"\" width=\"310\" height=\"151\" /\u003E\u003C/p\u003E\n\u003Cp\u003EThis method is called\u003Cstrong\u003E Linear Interpolation\u003C/strong\u003E.\u003C/p\u003E\n\u003Cp\u003E\u003Cbr /\u003E\u003Cstrong\u003EWeighted Average Interpolation\u003C/strong\u003E\u003C/p\u003E\n\u003Cp\u003EFor Square C, the square is between other squares at 30\u0026deg;F, 48\u0026deg;F, and 50\u0026deg;F. You could average the three numbers and get approximately 43\u0026deg;F. Or you could try to be even more precise. The unknown square is closer to the 50\u0026deg;F square than to the others. Therefore, you can estimate the temperature to be a little higher than the average (maybe 45\u0026deg;F or 46\u0026deg;F). 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You will need to make a plan or \u003Cem\u003Estrategy\u003C/em\u003E to make a good prediction.\u003C/p\u003E", + "is_callout": false, + "is_full_width": true, + "is_hidden": false, + "name": "", + "type": "Embeddable::Xhtml", + "ref_id": "147945-Embeddable::Xhtml" + }, + "section": "header_block" + }, { + "embeddable": { + "content": "\u003Cp\u003EThe map below shows temperature for three times separated by 4 hours.\u003C/p\u003E\r\n\u003Cp\u003E\u003Cem\u003EYour job will be to predict the temperature for\u0026nbsp;\u003C/em\u003E\u003Cem\u003E\u003Cstrong\u003E4 hours after the last measurement shown.\u003C/strong\u003E\u003C/em\u003E\u003C/p\u003E\r\n\u003Cp\u003EThings to do and look for:\u003C/p\u003E\r\n\u003Cul\u003E\r\n\u003Cli\u003EUse the slider to see temperatures from 7am to 3pm.\u003C/li\u003E\r\n\u003Cli\u003ELook for patterns of temperature changes over time.\u003C/li\u003E\r\n\u003Cli\u003ETo see patterns, it may help to turn on and off the temperature data or the color key.\u003C/li\u003E\r\n\u003C/ul\u003E\r\n\u003Cp\u003ERemember: always start by clicking \u003Cstrong\u003E\u003Cem\u003ESetup\u003C/em\u003E \u003C/strong\u003Eand \u003Cstrong\u003Ethen\u0026nbsp;\u003Cem\u003ERun\u003C/em\u003E\u003C/strong\u003E.\u003C/p\u003E", + "is_callout": true, + "is_full_width": true, + "is_hidden": false, + "name": "TASK", + "type": "Embeddable::Xhtml", + "ref_id": "149059-Embeddable::Xhtml" + }, + "section": "header_block" + }, { + "embeddable": { + "name": "Noorvik patterns", + "url_fragment": null, + "authored_state": "{\"version\":1,\"questionType\":\"iframe_interactive\",\"blanks\":[{\"id\":\"[blank-Noorvik11am]\",\"size\":5},{\"id\":\"[blank-Noorvik3pm]\",\"size\":5},{\"id\":\"[blank-Noorvik7am]\",\"size\":5}],\"prompt\":\"\u003Cp\u003EEnter the temperature in Noorvik (cell C-2) for 7am [blank-Noorvik7am], 11am [blank-Noorvik11am], and 3pm [blank-Noorvik3pm].\u003C/p\u003E\",\"hint\":\"\"}", + "is_hidden": false, + "is_full_width": true, + "show_in_featured_question_report": true, + "inherit_aspect_ratio_method": true, + "custom_aspect_ratio_method": "DEFAULT", + "inherit_native_width": true, + "custom_native_width": 576, + "inherit_native_height": true, + "custom_native_height": 435, + "inherit_click_to_play": true, + "custom_click_to_play": false, + "inherit_full_window": true, + "custom_full_window": false, + "inherit_click_to_play_prompt": true, + "custom_click_to_play_prompt": null, + "inherit_image_url": true, + "custom_image_url": null, + "library_interactive": { + "hash": "aace5b2f57919f26891d77ac3e14744470800215", + "data": { + "aspect_ratio_method": "DEFAULT", + "authoring_guidance": "", + "base_url": "https://models-resources.concord.org/question-interactives/version/v1.1.0/fill-in-the-blank/", + "click_to_play": false, + "click_to_play_prompt": null, + "description": "", + "enable_learner_state": true, + "full_window": false, + "has_report_url": false, + "image_url": null, + "name": "Fill In The Blank", + "native_height": 435, + "native_width": 576, + "no_snapshots": false, + "show_delete_data_button": false, + "thumbnail_url": "", + "customizable": true, + "authorable": true + } + }, + "type": "ManagedInteractive", + "ref_id": "2143-ManagedInteractive", + "linked_interactives": [] + }, + "section": null + }, { + "embeddable": { + "name": "Noorvik prediction", + "url_fragment": null, + "authored_state": "{\"version\":1,\"questionType\":\"iframe_interactive\",\"blanks\":[{\"id\":\"[blank-1]\",\"size\":5}],\"prompt\":\"\u003Cp\u003EEnter a prediction for the temperature in Noorvik at 7pm. 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All five weather station observations were made at the same time on the same day. The map also shows some temperatures that were estimated using the weather station observation data (estimated temperatures are in parentheses).\u003C/p\u003E\r\n\u003Cp\u003E\u003Cimg style=\"display: block; margin-left: auto; margin-right: auto;\" src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/L3AssessmentProbeMap.png\" width=\"555\" height=\"444\" /\u003E\u003C/p\u003E\r\n\u003Cp\u003EMs. Tevuk asks the students which of the estimated temperatures they are LEAST CERTAIN (MOST UNSURE) about.\u003C/p\u003E\r\n\u003Cp\u003EHere are the students\u0026rsquo; ideas. (Each student\u0026rsquo;s estimated temperature choice is in \u003Cstrong\u003Ebold\u003C/strong\u003E to make it easier to find.)\u003C/p\u003E\r\n\u003Ctable cellpadding=\"30\"\u003E\r\n\u003Ctbody\u003E\r\n\u003Ctr\u003E\r\n\u003Cth colspan=\"2\"\u003E\u003Cstrong\u003EAlex\u003C/strong\u003E\u003C/th\u003E\r\n\u003Cth colspan=\"2\"\u003E\u003Cstrong\u003EDelana\u003C/strong\u003E\u003C/th\u003E\r\n\u003C/tr\u003E\r\n\u003Ctr\u003E\r\n\u003Ctd width=\"88\"\u003E\u003Cimg src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/Alex1-1.png\" width=\"80\" height=\"100\" align=\"center\" hspace=\"10\" vspace=\"10\" /\u003E\u003C/td\u003E\r\n\u003Ctd style=\"padding: 10px;\" width=\"350\"\u003E\r\n\u003Cp\u003EI\u0026rsquo;m least certain about the estimate of \u003Cstrong\u003E53\u02da\u003C/strong\u003E because it\u0026rsquo;s furthest outside of the temperatures that were actually measured at a weather station.\u003C/p\u003E\r\n\u003Cp\u003E\u003Cimg style=\"display: block; margin-left: auto; margin-right: auto;\" src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/Lesson3AlexsChoice.png\" width=\"223\" height=\"200\" /\u003E\u003C/p\u003E\r\n\u003C/td\u003E\r\n\u003Ctd width=\"88\"\u003E\u003Cimg src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/Delana2.png\" width=\"80\" height=\"100\" align=\"center\" hspace=\"10\" vspace=\"10\" /\u003E\u003C/td\u003E\r\n\u003Ctd style=\"padding: 10px;\" width=\"350\"\u003E\r\n\u003Cp\u003EI\u0026rsquo;m least certain about the estimate of \u003Cstrong\u003E43\u02da\u003C/strong\u003E because it\u0026rsquo;s far away from any temperatures measured at a weather station.\u0026nbsp;\u003C/p\u003E\r\n\u003Cp\u003E\u003Cimg style=\"display: block; margin-left: auto; margin-right: auto;\" src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/Lesson3DelanasChoice.png\" width=\"222\" height=\"200\" /\u003E\u003C/p\u003E\r\n\u003C/td\u003E\r\n\u003C/tr\u003E\r\n\u003C/tbody\u003E\r\n\u003Ctbody\u003E\r\n\u003Ctr\u003E\r\n\u003Cth colspan=\"2\"\u003E\u003Cstrong\u003EKalin\u003C/strong\u003E\u003C/th\u003E\r\n\u003Cth colspan=\"2\"\u003E\u003Cstrong\u003ESage\u003C/strong\u003E\u003C/th\u003E\r\n\u003C/tr\u003E\r\n\u003Ctr\u003E\r\n\u003Ctd width=\"88\"\u003E\r\n\u003Cp\u003E\u003Cimg src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/Kalin3.png\" width=\"80\" height=\"100\" align=\"center\" hspace=\"10\" vspace=\"10\" /\u003E\u003C/p\u003E\r\n\u003C/td\u003E\r\n\u003Ctd style=\"padding: 10px;\" width=\"350\"\u003E\r\n\u003Cp\u003EI\u0026rsquo;m least certain about the estimate of \u003Cstrong\u003E39\u02da\u003C/strong\u003E because there aren\u0026rsquo;t any other estimated temperatures near the 39\u02da estimate.\u003C/p\u003E\r\n\u003Cp\u003E\u003Cimg style=\"display: block; margin-left: auto; margin-right: auto;\" src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/Lesson3KalinsChoice.png\" width=\"230\" height=\"204\" /\u003E\u003C/p\u003E\r\n\u003C/td\u003E\r\n\u003Ctd width=\"88\"\u003E\r\n\u003Cp\u003E\u003Cimg src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/Lesson3SageAvatar.png\" width=\"80\" height=\"100\" align=\"center\" hspace=\"8\" vspace=\"8\" /\u003E\u003C/p\u003E\r\n\u003C/td\u003E\r\n\u003Ctd style=\"padding: 10px;\" width=\"350\"\u003E\r\n\u003Cp\u003EI\u0026rsquo;m least certain about the estimate of \u003Cstrong\u003E37\u02da\u003C/strong\u003E because weather usually moves from west to east, so I\u0026rsquo;m unsure about estimates on the west side of the map.\u003C/p\u003E\r\n\u003Cp\u003E\u003Cimg class=\"\" style=\"display: block; margin-left: auto; margin-right: auto;\" src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/Lesson3SagesChoice.png\" alt=\"\" width=\"230\" height=\"206\" /\u003E\u003C/p\u003E\r\n\u003C/td\u003E\r\n\u003C/tr\u003E\r\n\u003C/tbody\u003E\r\n\u003C/table\u003E", + "is_callout": false, + "is_full_width": true, + "is_hidden": false, + "name": "", + "type": "Embeddable::Xhtml", + "ref_id": "147898-Embeddable::Xhtml" + }, + "section": "header_block" + }, { + "embeddable": { + "plugin": { + "description": null, + "author_data": "{\"tipType\":\"windowShade\",\"windowShade\":{\"windowShadeType\":\"teacherTip\",\"layout\":\"mediaLeft\",\"initialOpenState\":true,\"content\":\"###Pre-Assessment Implementation\\n*Lesson 3, Opening: Which Estimates Should We Trust? Pre-Assessment*\\nDuring the pre-assessment, each student will view the probe and make an individual choice. The request for explanation will only be on the post-assessment implementation. After students make an individual choice for the pre-assessment, you can lead discussion including, for example, a pair/share opportunity and/or full class discussion. \\n\\nAt this time, encourage students to share and discuss their ideas and reasons without indicating that any one answer is better or worse. Let the students know that they should keep thinking about this question and that the class will return to it at the end of the lesson.\",\"content2\":\"\",\"mediaType\":\"none\",\"mediaCaption\":\"Last, First. \\\"Title of Work.\\\" Year created. Site Title [OR] Publisher. 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Review the information below and think about ways to scaffold students toward developing knowledge and practice as appropriate for their classes. Also, we recommend that during the first implementation of the probe, that you scaffold students to focus on their own ideas about this problem, rather than on vocabulary terms such as **interpolation** and **extrapolation**. By discussing the different options, students can engage in productive talk related to these data sense making and computational thinking concepts without necessarily using technical terminology. During the ensuing lesson and the second implementation of the probe, the terms **interpolation** and **extrapolation** can be used, if appropriate.\\n\\nThis assessment probe is designed to assess and scaffold students in thinking and talking about **interpolation** and **extrapolation**. **Interpolation** means finding an estimation of a value between ones that are known or tabulated using surrounding points or values (that is, estimating an unknown value based on surrounding information). **Extrapolation** means finding or concluding something by assuming that existing trends will continue, or a current method will remain applicable beyond existing known values (that is, following a pattern beyond the known data points). \\n\\nInterpolation and extrapolation are similar, but because extrapolation involves estimating beyond the known data points, this approach is subject to greater uncertainty and has a higher risk of producing more imprecise or potentially even meaningless results compared with interpolation. \\n\\nThe assessment is situated in the unit context to provide an opportunity for students to make sense about extrapolation and interpolation of a specific, tangible weather problem (i.e., temperatures in a two-dimensional area at one point in time). While extrapolation is associated with higher levels of uncertainty, it\u2019s also sometimes necessary. This is true, for example, for forecasting (prediction). Prediction of future weather will always involve extrapolation (i.e., extending the pattern of weather data into the future given that observed data cannot be obtained for the future until time passes and the future becomes the present!). Uncertainty associated with extrapolation is why there\u2019s always some level of uncertainty in weather forecasts. Basically, this is why weather forecasts are sometimes wrong. There is always some uncertainty associated with interpolation too, though generally it is less so than with extrapolation.\\n\\nThis assessment also relates to **pattern recognition** and **data aggregation**. **Pattern recognition** involves identifying patterns and trends within and across groups of data/information as seen in the observable world. Students employ **pattern recognition** in this assessment as they view the distribution of temperatures in the map grid and make sense of patterns and trends across the grid (in both observed and estimated values) to think about the question. **Data aggregation** involves determining the appropriate data to collect or generate in order to study the identified phenomenon. Students should consider more and less appropriate ways to aggregate data in the map grid as they figure out which response they think is best. For example, students should be think about which cells in the grid have enough data to estimate temperatures for from collected data, and which temperatures might be problematic to estimate \u2013 meaning we might need to collect more data to generate a good estimate for temperatures in those cells. \\n\\nWhile one of the responses makes the most sense from a practical standpoint for this particular problem, there\u2019s no absolutely correct answer. Using an indefinite problem provides space for students to think and talk about how much confidence we can have in different interpolated and extrapolated values. \",\"content2\":\"\",\"mediaType\":\"none\",\"mediaCaption\":\"Last, First. \\\"Title of Work.\\\" Year created. Site Title [OR] Publisher. 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The values in parentheses are all estimated, so having other estimated values near the value that Kalin chooses would not necessarily make us more confident about Kalin\u2019s choice. If there were additional observed values near the cell that Kalin chose, that would help boost our confidence. We can feel more confident about interpolated values for data the more observed data values we have for a given area. \\n\\nStudents who choose 39\u00b0 as the most uncertain value could benefit from discussions about the difference between observed data points and estimated data points. Students can think about which types of values are more trustworthy and why (e.g., local conditions like elevation changes or water bodies could affect local values, making estimated temperatures less reliable than observed values). Students may come up with potential problems with observed values too (e.g., a faulty thermometer), which is fine. \\n\\n\\n###Middle Level\\n\u2022\\t**Sage\u2019s response (37\u00b0)** suggests that she may be thinking beyond interpolation to also consider weather processes (e.g., movement of air masses across Alaska). While that shows some good thinking, the values on the assessment probe map all represent one point in time, so we would be less concerned about air movement over time and issues like east versus west in Alaska for this particular problem. \\n\\nLater in the unit, students who chose 37\u00b0 may benefit from discussions that emphasize the difference between interpolating data from known values at one point in time versus doing things like making predictions into the future across a two-dimensional area based on known information such as wind speed, wind direction, etc. \\n\\n\\n###Upper Middle Level\\n\u2022\\t**Delana\u2019s response (43\u00b0)** suggests that she understands that we can be more confident about estimates when we have observed values nearby. We should be less confident about interpolated data (there are many estimated values near the 43\u00b0 cell) nearby in comparison with nearby observed data.\\n\\nWhile students who choose Delana\u2019s response have useful ideas about confidence and interpolation, they could also benefit from some scaffolding to reason more deeply about interpolation versus extrapolation. Moving beyond the area of known data points (i.e., extrapolation) is generally associated with higher uncertainty compared with interpolation. For example, if there is a weather front just to the east of the 46\u00b0 and 51\u00b0 measured temperature values, the 53\u00b0 estimated value could be quite different from what an actual observed measurement taken at that location would be. \\n\\n\\n###More Formal Idea\\n\u2022\\t**Alex\u2019s response (53\u00b0)** and rationale recognizes the problems associated with extrapolation beyond known data points. 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All five weather station observations were made at the same time on the same day. The map also shows some temperatures that were estimated using the weather station observation data (estimated temperatures are in parentheses).\u003C/p\u003E\r\n\u003Cp\u003E\u003Cimg style=\"display: block; margin-left: auto; margin-right: auto;\" src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/L3AssessmentProbeMap.png\" width=\"555\" height=\"444\" /\u003E\u003C/p\u003E\r\n\u003Cp\u003EMs. Tevuk asks the students which of the estimated temperatures they are LEAST CERTAIN (MOST UNSURE) about.\u003C/p\u003E\r\n\u003Cp\u003EHere are the students\u0026rsquo; ideas. (Each student\u0026rsquo;s estimated temperature choice is in \u003Cstrong\u003Ebold\u003C/strong\u003E to make it easier to find.)\u003C/p\u003E\r\n\u003Ctable cellpadding=\"30\"\u003E\r\n\u003Ctbody\u003E\r\n\u003Ctr\u003E\r\n\u003Cth colspan=\"2\"\u003E\u003Cstrong\u003EAlex\u003C/strong\u003E\u003C/th\u003E\r\n\u003Cth colspan=\"2\"\u003E\u003Cstrong\u003EDelana\u003C/strong\u003E\u003C/th\u003E\r\n\u003C/tr\u003E\r\n\u003Ctr\u003E\r\n\u003Ctd width=\"88\"\u003E\u003Cimg src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/Alex1-1.png\" width=\"80\" height=\"100\" align=\"center\" hspace=\"10\" vspace=\"10\" /\u003E\u003C/td\u003E\r\n\u003Ctd style=\"padding: 10px;\" width=\"350\"\u003E\r\n\u003Cp\u003EI\u0026rsquo;m least certain about the estimate of \u003Cstrong\u003E53\u02da\u003C/strong\u003E because it\u0026rsquo;s furthest outside of the temperatures that were actually measured at a weather station.\u003C/p\u003E\r\n\u003Cp\u003E\u003Cimg style=\"display: block; margin-left: auto; margin-right: auto;\" src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/Lesson3AlexsChoice.png\" width=\"223\" height=\"200\" /\u003E\u003C/p\u003E\r\n\u003C/td\u003E\r\n\u003Ctd width=\"88\"\u003E\u003Cimg src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/Delana2.png\" width=\"80\" height=\"100\" align=\"center\" hspace=\"10\" vspace=\"10\" /\u003E\u003C/td\u003E\r\n\u003Ctd style=\"padding: 10px;\" width=\"350\"\u003E\r\n\u003Cp\u003EI\u0026rsquo;m least certain about the estimate of \u003Cstrong\u003E43\u02da\u003C/strong\u003E because it\u0026rsquo;s far away from any temperatures measured at a weather station.\u0026nbsp;\u003C/p\u003E\r\n\u003Cp\u003E\u003Cimg style=\"display: block; margin-left: auto; margin-right: auto;\" src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/Lesson3DelanasChoice.png\" width=\"222\" height=\"200\" /\u003E\u003C/p\u003E\r\n\u003C/td\u003E\r\n\u003C/tr\u003E\r\n\u003C/tbody\u003E\r\n\u003Ctbody\u003E\r\n\u003Ctr\u003E\r\n\u003Cth colspan=\"2\"\u003E\u003Cstrong\u003EKalin\u003C/strong\u003E\u003C/th\u003E\r\n\u003Cth colspan=\"2\"\u003E\u003Cstrong\u003ESage\u003C/strong\u003E\u003C/th\u003E\r\n\u003C/tr\u003E\r\n\u003Ctr\u003E\r\n\u003Ctd width=\"88\"\u003E\r\n\u003Cp\u003E\u003Cimg src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/Kalin3.png\" width=\"80\" height=\"100\" align=\"center\" hspace=\"10\" vspace=\"10\" /\u003E\u003C/p\u003E\r\n\u003C/td\u003E\r\n\u003Ctd style=\"padding: 10px;\" width=\"350\"\u003E\r\n\u003Cp\u003EI\u0026rsquo;m least certain about the estimate of \u003Cstrong\u003E39\u02da\u003C/strong\u003E because there aren\u0026rsquo;t any other estimated temperatures near the 39\u02da estimate.\u003C/p\u003E\r\n\u003Cp\u003E\u003Cimg style=\"display: block; margin-left: auto; margin-right: auto;\" src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/Lesson3KalinsChoice.png\" width=\"230\" height=\"204\" /\u003E\u003C/p\u003E\r\n\u003C/td\u003E\r\n\u003Ctd width=\"88\"\u003E\r\n\u003Cp\u003E\u003Cimg src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/Lesson3SageAvatar.png\" width=\"80\" height=\"100\" align=\"center\" hspace=\"8\" vspace=\"8\" /\u003E\u003C/p\u003E\r\n\u003C/td\u003E\r\n\u003Ctd style=\"padding: 10px;\" width=\"350\"\u003E\r\n\u003Cp\u003EI\u0026rsquo;m least certain about the estimate of \u003Cstrong\u003E37\u02da\u003C/strong\u003E because weather usually moves from west to east, so I\u0026rsquo;m unsure about estimates on the west side of the map.\u003C/p\u003E\r\n\u003Cp\u003E\u003Cimg class=\"\" style=\"display: block; margin-left: auto; margin-right: auto;\" src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/Lesson3SagesChoice.png\" alt=\"\" width=\"230\" height=\"206\" /\u003E\u003C/p\u003E\r\n\u003C/td\u003E\r\n\u003C/tr\u003E\r\n\u003C/tbody\u003E\r\n\u003C/table\u003E", + "is_callout": false, + "is_full_width": true, + "is_hidden": false, + "name": "", + "type": "Embeddable::Xhtml", + "ref_id": "147895-Embeddable::Xhtml" + }, + "section": "header_block" + }, { + "embeddable": { + "plugin": { + "description": null, + "author_data": "{\"tipType\":\"windowShade\",\"windowShade\":{\"windowShadeType\":\"teacherTip\",\"layout\":\"mediaLeft\",\"initialOpenState\":true,\"content\":\"###Pre-Assessment Implementation\\n*Lesson 3, Opening: Which Estimates Should We Trust? Pre-Assessment*\\nDuring the pre-assessment, each student will view the probe and make an individual choice. The request for explanation will only be on the post-assessment implementation. After students make an individual choice for the pre-assessment, you can lead discussion including, for example, a pair/share opportunity and/or full class discussion. \\n\\nAt this time, encourage students to share and discuss their ideas and reasons without indicating that any one answer is better or worse. Let the students know that they should keep thinking about this question and that the class will return to it at the end of the lesson.\",\"content2\":\"\",\"mediaType\":\"none\",\"mediaCaption\":\"Last, First. \\\"Title of Work.\\\" Year created. Site Title [OR] Publisher. Gallery [OR] Location. http://www.url.com.\",\"mediaURL\":\"\"}}", + "approved_script_label": "teacherEditionTips", + "component_label": "windowShade", + "approved_script": { + "name": "Teacher Edition", + "url": "https://teacher-edition-tips-plugin.concord.org/version/v3.6.0/plugin.js", + "label": "teacherEditionTips", + "description": "This plugin provides Teacher Edition components", + "version": 3, + "json_url": "https://teacher-edition-tips-plugin.concord.org/version/v3.6.0/manifest.json", + "authoring_metadata": "{\"components\":[{\"label\":\"windowShade\",\"name\":\"Window Shades\",\"scope\":\"embeddable\",\"guiAuthoring\":true},{\"label\":\"sideTip\",\"name\":\"Side Tips\",\"scope\":\"embeddable\",\"guiAuthoring\":true},{\"label\":\"questionWrapper\",\"name\":\"Question Wrapper\",\"scope\":\"embeddable-decoration\",\"decorates\":[\"Embeddable::MultipleChoice\",\"Embeddable::OpenResponse\",\"Embeddable::ImageQuestion\",\"ManagedInteractive\",\"MwInteractive\",\"ImageInteractive\",\"VideoInteractive\"],\"guiAuthoring\":true,\"guiPreview\":true}]}" + } + }, + "is_hidden": false, + "is_full_width": true, + "type": "Embeddable::EmbeddablePlugin", + "ref_id": "10237-Embeddable::EmbeddablePlugin" + }, + "section": null + }, { + "embeddable": { + "plugin": { + "description": null, + "author_data": "{\"tipType\":\"windowShade\",\"windowShade\":{\"windowShadeType\":\"theoryAndBackground\",\"layout\":\"mediaLeft\",\"initialOpenState\":true,\"content\":\"###Computational Thinking Concepts and Practices:\\n- Interpolation\\n- Extrapolation\\n- Pattern Recognition\\n- Data Aggregation\\n\\n###What is the Purpose of this Assessment Probe?\\nThe following information provides background for teachers and is not necessarily representative of the learning goals for everything students should understand. Review the information below and think about ways to scaffold students toward developing knowledge and practice as appropriate for their classes. Also, we recommend that during the first implementation of the probe, that you scaffold students to focus on their own ideas about this problem, rather than on vocabulary terms such as **interpolation** and **extrapolation**. By discussing the different options, students can engage in productive talk related to these data sense making and computational thinking concepts without necessarily using technical terminology. During the ensuing lesson and the second implementation of the probe, the terms **interpolation** and **extrapolation** can be used, if appropriate.\\n\\nThis assessment probe is designed to assess and scaffold students in thinking and talking about **interpolation** and **extrapolation**. **Interpolation** means finding an estimation of a value between ones that are known or tabulated using surrounding points or values (that is, estimating an unknown value based on surrounding information). **Extrapolation** means finding or concluding something by assuming that existing trends will continue, or a current method will remain applicable beyond existing known values (that is, following a pattern beyond the known data points). \\n\\nInterpolation and extrapolation are similar, but because extrapolation involves estimating beyond the known data points, this approach is subject to greater uncertainty and has a higher risk of producing more imprecise or potentially even meaningless results compared with interpolation. \\n\\nThe assessment is situated in the unit context to provide an opportunity for students to make sense about extrapolation and interpolation of a specific, tangible weather problem (i.e., temperatures in a two-dimensional area at one point in time). While extrapolation is associated with higher levels of uncertainty, it\u2019s also sometimes necessary. This is true, for example, for forecasting (prediction). Prediction of future weather will always involve extrapolation (i.e., extending the pattern of weather data into the future given that observed data cannot be obtained for the future until time passes and the future becomes the present!). Uncertainty associated with extrapolation is why there\u2019s always some level of uncertainty in weather forecasts. Basically, this is why weather forecasts are sometimes wrong. There is always some uncertainty associated with interpolation too, though generally it is less so than with extrapolation.\\n\\nThis assessment also relates to **pattern recognition** and **data aggregation**. **Pattern recognition** involves identifying patterns and trends within and across groups of data/information as seen in the observable world. Students employ **pattern recognition** in this assessment as they view the distribution of temperatures in the map grid and make sense of patterns and trends across the grid (in both observed and estimated values) to think about the question. **Data aggregation** involves determining the appropriate data to collect or generate in order to study the identified phenomenon. Students should consider more and less appropriate ways to aggregate data in the map grid as they figure out which response they think is best. For example, students should be think about which cells in the grid have enough data to estimate temperatures for from collected data, and which temperatures might be problematic to estimate \u2013 meaning we might need to collect more data to generate a good estimate for temperatures in those cells. \\n\\nWhile one of the responses makes the most sense from a practical standpoint for this particular problem, there\u2019s no absolutely correct answer. Using an indefinite problem provides space for students to think and talk about how much confidence we can have in different interpolated and extrapolated values. \",\"content2\":\"\",\"mediaType\":\"none\",\"mediaCaption\":\"Last, First. \\\"Title of Work.\\\" Year created. Site Title [OR] Publisher. 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The values in parentheses are all estimated, so having other estimated values near the value that Kalin chooses would not necessarily make us more confident about Kalin\u2019s choice. If there were additional observed values near the cell that Kalin chose, that would help boost our confidence. We can feel more confident about interpolated values for data the more observed data values we have for a given area. \\n\\nStudents who choose 39\u00b0 as the most uncertain value could benefit from discussions about the difference between observed data points and estimated data points. Students can think about which types of values are more trustworthy and why (e.g., local conditions like elevation changes or water bodies could affect local values, making estimated temperatures less reliable than observed values). Students may come up with potential problems with observed values too (e.g., a faulty thermometer), which is fine. \\n\\n\\n###Middle Level\\n\u2022\\t**Sage\u2019s response (37\u00b0)** suggests that she may be thinking beyond interpolation to also consider weather processes (e.g., movement of air masses across Alaska). While that shows some good thinking, the values on the assessment probe map all represent one point in time, so we would be less concerned about air movement over time and issues like east versus west in Alaska for this particular problem. \\n\\nLater in the unit, students who chose 37\u00b0 may benefit from discussions that emphasize the difference between interpolating data from known values at one point in time versus doing things like making predictions into the future across a two-dimensional area based on known information such as wind speed, wind direction, etc. \\n\\n\\n###Upper Middle Level\\n\u2022\\t**Delana\u2019s response (43\u00b0)** suggests that she understands that we can be more confident about estimates when we have observed values nearby. We should be less confident about interpolated data (there are many estimated values near the 43\u00b0 cell) nearby in comparison with nearby observed data.\\n\\nWhile students who choose Delana\u2019s response have useful ideas about confidence and interpolation, they could also benefit from some scaffolding to reason more deeply about interpolation versus extrapolation. Moving beyond the area of known data points (i.e., extrapolation) is generally associated with higher uncertainty compared with interpolation. For example, if there is a weather front just to the east of the 46\u00b0 and 51\u00b0 measured temperature values, the 53\u00b0 estimated value could be quite different from what an actual observed measurement taken at that location would be. \\n\\n\\n###More Formal Idea\\n\u2022\\t**Alex\u2019s response (53\u00b0)** and rationale recognizes the problems associated with extrapolation beyond known data points. 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She will discuss how air moisture plays an important part in forming precipitation.\u003C/p\u003E", + "is_callout": true, + "is_full_width": true, + "is_hidden": false, + "name": "", + "type": "Embeddable::Xhtml", + "ref_id": "148013-Embeddable::Xhtml" + }, + "section": "header_block" + }, { + "embeddable": { + "name": "", + "url_fragment": null, + "authored_state": "{\"version\":1,\"questionType\":\"iframe_interactive\",\"videoUrl\":\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/Captioned_Videos/JackieLesson3_88_Captioned.mp4\",\"poster\":\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/Captioned_Videos/Posters/Poster_L3_Video.png\"}", + "is_hidden": false, + "is_full_width": true, + "show_in_featured_question_report": true, + "inherit_aspect_ratio_method": true, + "custom_aspect_ratio_method": null, + "inherit_native_width": true, + "custom_native_width": 576, + "inherit_native_height": true, + "custom_native_height": 435, + "inherit_click_to_play": true, + "custom_click_to_play": false, + "inherit_full_window": true, + "custom_full_window": false, + "inherit_click_to_play_prompt": true, + "custom_click_to_play_prompt": null, + "inherit_image_url": true, + "custom_image_url": null, + "library_interactive": { + "hash": "34e1a2a39c058da8ff4ffe5a09ad14af337c4a01", + "data": { + "aspect_ratio_method": "DEFAULT", + "authoring_guidance": "", + "base_url": "https://models-resources.concord.org/question-interactives/version/v1.1.0/video-player/", + "click_to_play": false, + "click_to_play_prompt": null, + "description": "This video player will not have the blue header bar above the interactive.\r\nIt does not save the students position in the video. \r\nIt will not show up in the teacher report.", + "enable_learner_state": false, + "full_window": false, + "has_report_url": false, + "image_url": null, + "name": "Video Player", + "native_height": 435, + "native_width": 576, + "no_snapshots": false, + "show_delete_data_button": false, + "thumbnail_url": "", + "customizable": false, + "authorable": true + } + }, + "type": "ManagedInteractive", + "ref_id": "1765-ManagedInteractive", + "linked_interactives": [] + }, + "section": "header_block" + }] + }, { + "additional_sections": {}, + "embeddable_display_mode": "stacked", + "id": 143588, + "is_completion": false, + "is_hidden": false, + "layout": "l-full-width", + "name": "Opening", + "position": 2, + "show_header": true, + "show_info_assessment": true, + "show_interactive": false, + "show_sidebar": false, + "sidebar": null, + "sidebar_title": "Did you know?", + "toggle_info_assessment": false, + "embeddables": [{ + "embeddable": { + "content": "\u003Cp\u003EHave you ever been caught without your parka or boots when you needed them? Predicting rain or snow\u0026nbsp;is a special challenge for weather scientists. Watch the video below to learn more about forecasting the weather in Alaska.\u003C/p\u003E\r\n\u003Cp\u003EAs weather scientists, you will continue to explore weather maps. Now, you will add two additional pieces of information to each square: precipitation (a symbol) and air moisture content (a number). 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"sidebar": null, + "sidebar_title": "Did you know?", + "toggle_info_assessment": false, + "embeddables": [{ + "embeddable": { + "content": "\u003Cp\u003E\u003Cstrong\u003EWhat Are the Rules for Fronts and Precipitation?\u003C/strong\u003E\u003C/p\u003E\r\n\u003Cp\u003EMs. Tevuk\u0026rsquo;s students need to write a rule for their computer model to predict areas of precipitation on a map showing weather fronts. They have different ideas for what the rule should be.\u003C/p\u003E\r\n\u003Cp\u003EHere are the students\u0026rsquo; ideas: The rule should be that precipitation happens\u0026hellip;\u003C/p\u003E\r\n\u003Ctable cellpadding=\"30\"\u003E\r\n\u003Ctbody\u003E\r\n\u003Ctr\u003E\r\n\u003Cth colspan=\"2\"\u003E\u003Cstrong\u003EAlex\u003C/strong\u003E\u003C/th\u003E\r\n\u003Cth colspan=\"2\"\u003E\u003Cstrong\u003EDelana\u003C/strong\u003E\u003C/th\u003E\r\n\u003C/tr\u003E\r\n\u003Ctr\u003E\r\n\u003Ctd width=\"88\"\u003E\u003Cimg src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/Alex4.png\" width=\"72\" height=\"90\" align=\"center\" hspace=\"10\" vspace=\"10\" /\u003E\u003C/td\u003E\r\n\u003Ctd style=\"padding: 10px;\" width=\"350\"\u003E\u003Cstrong\u003Ewith a warm front coming in\u003C/strong\u003E because warm air moves in and mixes with cold air, which leads to precipitation. You don\u0026rsquo;t get precipitation with a cold front because cold air is dry.\u003C/td\u003E\r\n\u003Ctd width=\"88\"\u003E\u003Cimg src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/Delana4.png\" width=\"70\" height=\"90\" align=\"center\" hspace=\"10\" vspace=\"10\" /\u003E\u003C/td\u003E\r\n\u003Ctd style=\"padding: 10px;\" width=\"350\"\u003E\u003Cstrong\u003Ewith both cold fronts and warm fronts coming in\u003C/strong\u003E because in both cases warm air and cold air meet, leading to condensation and precipitation.\u003C/td\u003E\r\n\u003C/tr\u003E\r\n\u003C/tbody\u003E\r\n\u003Ctbody\u003E\r\n\u003Ctr\u003E\r\n\u003Cth colspan=\"2\"\u003E\u003Cstrong\u003EKalin\u003C/strong\u003E\u003C/th\u003E\r\n\u003Cth colspan=\"2\"\u003E\u003Cstrong\u003ESage\u003C/strong\u003E\u003C/th\u003E\r\n\u003C/tr\u003E\r\n\u003Ctr\u003E\r\n\u003Ctd width=\"88\"\u003E\r\n\u003Cp\u003E\u003Cimg src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/Kalin6.png\" width=\"72\" height=\"90\" align=\"center\" hspace=\"10\" vspace=\"10\" /\u003E\u003C/p\u003E\r\n\u003C/td\u003E\r\n\u003Ctd style=\"padding: 10px;\" width=\"350\"\u003E\u003Cstrong\u003Ewith a cold front coming in\u003C/strong\u003E because it\u0026rsquo;s usually rainy or snowy when it\u0026rsquo;s cold out. You don\u0026rsquo;t get precipitation with a warm front because it\u0026rsquo;s warm when the sun is shining.\u003C/td\u003E\r\n\u003Ctd width=\"88\"\u003E\r\n\u003Cp\u003E\u003Cimg src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/Sage2.png\" width=\"72\" height=\"90\" align=\"center\" hspace=\"8\" vspace=\"8\" /\u003E\u003C/p\u003E\r\n\u003C/td\u003E\r\n\u003Ctd style=\"padding: 10px;\" width=\"350\"\u003E\u003Cstrong\u003Eafter a cold front has passed by\u003C/strong\u003E because the cold air the front leaves behind is humid, which leads to precipitation.\u003C/td\u003E\r\n\u003C/tr\u003E\r\n\u003C/tbody\u003E\r\n\u003C/table\u003E", + "is_callout": false, + "is_full_width": true, + "is_hidden": false, + "name": "", + "type": "Embeddable::Xhtml", + "ref_id": "147904-Embeddable::Xhtml" + }, + "section": "header_block" + }, { + "embeddable": { + "plugin": { + "description": null, + "author_data": "{\"tipType\":\"windowShade\",\"windowShade\":{\"windowShadeType\":\"teacherTip\",\"layout\":\"mediaLeft\",\"initialOpenState\":true,\"content\":\"###Pre-Assessment Implementation\\n*Lesson 4, Opening: What Are the Rules for Fronts and Precipitation? Pre-Assessment*\\nDuring the pre-assessment, each student will view the probe and make an individual choice. The request for explanation will only be on the post-assessment. After students make an individual choice for the pre-assessment, the teacher can lead discussion including, for example, a pair/share opportunity and/or full class discussion. \\n\\nAt this time, encourage students to share and discuss their ideas and reasons without indicating that any one answer is better or worse. Let the students know that they should keep thinking about this question and that the class will return to it at the end of the next lesson (Lesson 5).\",\"content2\":\"\",\"mediaType\":\"none\",\"mediaCaption\":\"Last, First. \\\"Title of Work.\\\" Year created. Site Title [OR] Publisher. 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We suggest teachers review the information below and think about ways to scaffold students toward developing knowledge and practice as appropriate for their classes. Also, we recommend that during the first implementation of the probe, teachers scaffold students to focus on students\u2019 own ideas about this problem. By discussing the different options, students can engage in productive talk related to the different response patterns, priming them to look for productive patterns to associate with precipitation in the upcoming lessons. \\n\\nDuring the ensuing two lessons and the second implementation of the probe, students should be able to use the data from the virtual storm to identify the patterns of temperature, humidity, and movement that are associated with precipitation.\\n\\nThis assessment probe is designed to assess and scaffold students in thinking and talking about how patterns of data (i.e., temperature, humidity, and air movement) are associated with precipitation in a location. To keep things simple, we only focus on two types of fronts: cold fronts and warm fronts. Both types of fronts can be associated with precipitation. Identifying patterns associated with precipitation is an example of the computational thinking practice of **Pattern Recognition**. Once patterns associated with precipitation are identified, they can be used in conjunction with data to make a **Data-based Prediction**, which is what Ms. Tevuk\u2019s students are trying to do in the scenario for this assessment probe. **Data-based Prediction** involves identifying patterns and trends within and across groups of data/information as seen in the observable world. The patterns of data associated with precipitation in turn can be used to create rules for the computer model in a process of **Rule Abstraction**. **Rule abstraction** involves creating a general statement derived from exploring patterns in data in order to establish rule(s) or principles. In other words, if you know the patterns of variable values associated with precipitation, you can use those patterns to write rules for predicting precipitation.\\n\\nAs a **cold front** moves into an area, the heavier cool air pushes under the lighter warm air. The air behind a cold front is colder and usually drier than the warm air in front. The warm air in front becomes cooler as it is pushed upward by the entering cold air. If the warm air is humid enough, the water vapor it contains will condense into clouds as it rises, and precipitation may fall. \\n\u003Cimg src=\\\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/L4L5AssessmentTeacherGuideImage2.png\\\" width=\\\"850\\\" height=\\\"180\\\" /\u003E\\n \\n\\nWhen a **warm front** moves into an area, warm air moves above a cool air mass. As the warm air rises, it condenses, often forming clouds and precipitation. \\n\u003Cimg src=\\\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/L4L5AssessmentTeacherGuideImage1.png\\\" width=\\\"850\\\" height=\\\"180\\\" /\u003E\\n\\nThe assessment is situated in the unit context to provide an opportunity for students to make sense about patterns when reasoning about air masses, fronts, and precipitation. In this assessment, one of the responses is scientifically correct while the other responses that relate to some informal ideas about weather that students may hold. \",\"content2\":\"\",\"mediaType\":\"none\",\"mediaCaption\":\"Last, First. \\\"Title of Work.\\\" Year created. Site Title [OR] Publisher. 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Students may associate sun with warm, and rain and snow with cold. Based on that experience, they may think that a cold front is connected to precipitation.\\n\\nStudents who choose Kalin\u2019s response could benefit from having experiences that challenge their simple association idea. For example, looking at weather maps that show warmer air often has more moisture in it and colder air is often drier can help these students develop understanding that relationships might not be as simple as they think. Students who choose Kalin\u2019s response may not think about weather as something that happens with matter. Instead, they may just think of weather in terms of the actions of natural \\\"actors\\\" (e.g., the sun makes it warm, the wind makes it cold). These students could use help in learning that air masses are matter (they are made up of molecules and have mass). If we didn\u2019t have air masses made of matter on Earth, then we wouldn\u2019t have weather. You might talk with students about concrete examples that they can extend to think about air masses as entities made of stuff \u2013 for example, they could compare an empty balloon, a balloon filled with warm air, and a balloon filled with cold air. There is very little stuff (matter or molecules of air) in the empty balloon, while there is more stuff (matter) in the balloons filled with warm and cold air.\\n\\n###Middle Level \\n\u2022\\t**Both Alex\u2019s response (precipitation occurs with a warm front coming in)** and **Sage\u2019s response (precipitation occurs after a cold front has passed by an area)** suggest that they are aware that precipitation is associated with bodies of air moving and with the different conditions in those bodies of air (i.e., temperature, levels of humidity). However, both Sage\u2019s and Alex\u2019s ideas include some incorrect patterns that lead to problematic rules. \\n\\n\u2022\\t**Alex** thinks that cold air and warm air mixing causes precipitation. However, warm and cold air masses don\u2019t mix very readily, and it is instead actually warm air rising, expanding, and condensing that generally leads to precipitation. In addition, while Alex knows that cold fronts can be drier than warm fronts, that doesn\u2019t mean that there won\u2019t be any precipitation with cold fronts. Precipitation can occur with a cold front when warm air is pushed up, expands, and condenses.\\n\\nStudents who choose Alex\u2019s response could benefit from working with data to observe the following patterns: (1) precipitation can occur with a cold front and (2) fronts do not necessarily mix.\\n\\n\u2022\\t**Sage** thinks that cold air is humid, which leads to condensation and precipitation. However, warm air masses often have a higher level of humidity compared with cold air masses. It can be confusing that condensation occurs with rising, expanding, and cooling. The unit does not go into this in depth, however. For students who choose Sage\u2019s response, it is probably sufficient here to scaffold experiences with data and virtual storm showing the general pattern of warm air masses having higher levels of humidity than cool air masses.\\n\\n\u2022\\tStudents who choose Alex or Sage\u2019s response can also benefit from discussion and emphasis on the importance of getting the rule right (enough) in order to create a computational model that works. The students working on their weather model will not be able to predict weather with any consistency or accuracy if there is a big problem with the rule (algorithm) they have written into their computer model. \\n\\n###More Formal Idea\\n\u2022\\t**Delana\u2019s response (precipitation occurs with both cold fronts and warm fronts coming in)** is the best answer. Delana\u2019s explanation does not include a more complete mechanistic sequence involving cold air pushing warm air up; warm air rising, expanding, and condensing; and precipitation occurring as a result. This is because the Precipitating Change curriculum simplifies weather phenomena by emphasizing important patterns and de-emphasizing complicated mechanisms. This focus allows the curriculum to scaffold students in connecting observed patterns with rules that can be used to create predictive weather forecasting computer models. 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They have different ideas for what the rule should be.\u003C/p\u003E\r\n\u003Cp\u003EHere are the students\u0026rsquo; ideas: The rule should be that precipitation happens\u0026hellip;\u003C/p\u003E\r\n\u003Ctable cellpadding=\"30\"\u003E\r\n\u003Ctbody\u003E\r\n\u003Ctr\u003E\r\n\u003Cth colspan=\"2\"\u003E\u003Cstrong\u003EAlex\u003C/strong\u003E\u003C/th\u003E\r\n\u003Cth colspan=\"2\"\u003E\u003Cstrong\u003EDelana\u003C/strong\u003E\u003C/th\u003E\r\n\u003C/tr\u003E\r\n\u003Ctr\u003E\r\n\u003Ctd width=\"88\"\u003E\u003Cimg src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/Alex4.png\" width=\"72\" height=\"90\" align=\"center\" hspace=\"10\" vspace=\"10\" /\u003E\u003C/td\u003E\r\n\u003Ctd style=\"padding: 10px;\" width=\"350\"\u003E\u003Cstrong\u003Ewith a warm front coming in\u003C/strong\u003E because warm air moves in and mixes with cold air, which leads to precipitation. You don\u0026rsquo;t get precipitation with a cold front because cold air is dry.\u003C/td\u003E\r\n\u003Ctd width=\"88\"\u003E\u003Cimg src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/Delana4.png\" width=\"70\" height=\"90\" align=\"center\" hspace=\"10\" vspace=\"10\" /\u003E\u003C/td\u003E\r\n\u003Ctd style=\"padding: 10px;\" width=\"350\"\u003E\u003Cstrong\u003Ewith both cold fronts and warm fronts coming in\u003C/strong\u003E because in both cases warm air and cold air meet, leading to condensation and precipitation.\u003C/td\u003E\r\n\u003C/tr\u003E\r\n\u003C/tbody\u003E\r\n\u003Ctbody\u003E\r\n\u003Ctr\u003E\r\n\u003Cth colspan=\"2\"\u003E\u003Cstrong\u003EKalin\u003C/strong\u003E\u003C/th\u003E\r\n\u003Cth colspan=\"2\"\u003E\u003Cstrong\u003ESage\u003C/strong\u003E\u003C/th\u003E\r\n\u003C/tr\u003E\r\n\u003Ctr\u003E\r\n\u003Ctd width=\"88\"\u003E\r\n\u003Cp\u003E\u003Cimg src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/Kalin6.png\" width=\"72\" height=\"90\" align=\"center\" hspace=\"10\" vspace=\"10\" /\u003E\u003C/p\u003E\r\n\u003C/td\u003E\r\n\u003Ctd style=\"padding: 10px;\" width=\"350\"\u003E\u003Cstrong\u003Ewith a cold front coming in\u003C/strong\u003E because it\u0026rsquo;s usually rainy or snowy when it\u0026rsquo;s cold out. You don\u0026rsquo;t get precipitation with a warm front because it\u0026rsquo;s warm when the sun is shining.\u003C/td\u003E\r\n\u003Ctd width=\"88\"\u003E\r\n\u003Cp\u003E\u003Cimg src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/Sage2.png\" width=\"72\" height=\"90\" align=\"center\" hspace=\"8\" vspace=\"8\" /\u003E\u003C/p\u003E\r\n\u003C/td\u003E\r\n\u003Ctd style=\"padding: 10px;\" width=\"350\"\u003E\u003Cstrong\u003Eafter a cold front has passed by\u003C/strong\u003E because the cold air the front leaves behind is humid, which leads to precipitation.\u003C/td\u003E\r\n\u003C/tr\u003E\r\n\u003C/tbody\u003E\r\n\u003C/table\u003E", + "is_callout": false, + "is_full_width": true, + "is_hidden": false, + "name": "", + "type": "Embeddable::Xhtml", + "ref_id": "147903-Embeddable::Xhtml" + }, + "section": "header_block" + }, { + "embeddable": { + "plugin": { + "description": null, + "author_data": "{\"tipType\":\"windowShade\",\"windowShade\":{\"windowShadeType\":\"teacherTip\",\"layout\":\"mediaLeft\",\"initialOpenState\":true,\"content\":\"###Pre-Assessment Implementation\\n*Lesson 4, Opening: What Are the Rules for Fronts and Precipitation? Pre-Assessment*\\nDuring the pre-assessment, each student will view the probe and make an individual choice. The request for explanation will only be on the post-assessment. After students make an individual choice for the pre-assessment, the teacher can lead discussion including, for example, a pair/share opportunity and/or full class discussion. \\n\\nAt this time, encourage students to share and discuss their ideas and reasons without indicating that any one answer is better or worse. Let the students know that they should keep thinking about this question and that the class will return to it at the end of the next lesson (Lesson 5).\",\"content2\":\"\",\"mediaType\":\"none\",\"mediaCaption\":\"Last, First. \\\"Title of Work.\\\" Year created. Site Title [OR] Publisher. Gallery [OR] Location. http://www.url.com.\",\"mediaURL\":\"\"}}", + "approved_script_label": "teacherEditionTips", + "component_label": "windowShade", + "approved_script": { + "name": "Teacher Edition", + "url": "https://teacher-edition-tips-plugin.concord.org/version/v3.6.0/plugin.js", + "label": "teacherEditionTips", + "description": "This plugin provides Teacher Edition components", + "version": 3, + "json_url": "https://teacher-edition-tips-plugin.concord.org/version/v3.6.0/manifest.json", + "authoring_metadata": "{\"components\":[{\"label\":\"windowShade\",\"name\":\"Window Shades\",\"scope\":\"embeddable\",\"guiAuthoring\":true},{\"label\":\"sideTip\",\"name\":\"Side Tips\",\"scope\":\"embeddable\",\"guiAuthoring\":true},{\"label\":\"questionWrapper\",\"name\":\"Question Wrapper\",\"scope\":\"embeddable-decoration\",\"decorates\":[\"Embeddable::MultipleChoice\",\"Embeddable::OpenResponse\",\"Embeddable::ImageQuestion\",\"ManagedInteractive\",\"MwInteractive\",\"ImageInteractive\",\"VideoInteractive\"],\"guiAuthoring\":true,\"guiPreview\":true}]}" + } + }, + "is_hidden": false, + "is_full_width": true, + "type": "Embeddable::EmbeddablePlugin", + "ref_id": "10253-Embeddable::EmbeddablePlugin" + }, + "section": null + }, { + "embeddable": { + "plugin": { + "description": null, + "author_data": "{\"tipType\":\"windowShade\",\"windowShade\":{\"windowShadeType\":\"theoryAndBackground\",\"layout\":\"mediaLeft\",\"initialOpenState\":true,\"content\":\"###Computational Thinking Concepts and Practices:\\n* Pattern Recognition\\n* Data-based Prediction\\n* Rule Abstraction\\n\\n###What is the Purpose of this Assessment Probe?\\nThe following information provides background for teachers. We suggest teachers review the information below and think about ways to scaffold students toward developing knowledge and practice as appropriate for their classes. Also, we recommend that during the first implementation of the probe, teachers scaffold students to focus on students\u2019 own ideas about this problem. By discussing the different options, students can engage in productive talk related to the different response patterns, priming them to look for productive patterns to associate with precipitation in the upcoming lessons. \\n\\nDuring the ensuing two lessons and the second implementation of the probe, students should be able to use the data from the virtual storm to identify the patterns of temperature, humidity, and movement that are associated with precipitation.\\n\\nThis assessment probe is designed to assess and scaffold students in thinking and talking about how patterns of data (i.e., temperature, humidity, and air movement) are associated with precipitation in a location. To keep things simple, we only focus on two types of fronts: cold fronts and warm fronts. Both types of fronts can be associated with precipitation. Identifying patterns associated with precipitation is an example of the computational thinking practice of **Pattern Recognition**. Once patterns associated with precipitation are identified, they can be used in conjunction with data to make a **Data-based Prediction**, which is what Ms. Tevuk\u2019s students are trying to do in the scenario for this assessment probe. **Data-based Prediction** involves identifying patterns and trends within and across groups of data/information as seen in the observable world. The patterns of data associated with precipitation in turn can be used to create rules for the computer model in a process of **Rule Abstraction**. **Rule abstraction** involves creating a general statement derived from exploring patterns in data in order to establish rule(s) or principles. In other words, if you know the patterns of variable values associated with precipitation, you can use those patterns to write rules for predicting precipitation.\\n\\nAs a **cold front** moves into an area, the heavier cool air pushes under the lighter warm air. The air behind a cold front is colder and usually drier than the warm air in front. The warm air in front becomes cooler as it is pushed upward by the entering cold air. If the warm air is humid enough, the water vapor it contains will condense into clouds as it rises, and precipitation may fall. \\n\u003Cimg src=\\\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/L4L5AssessmentTeacherGuideImage2.png\\\" width=\\\"850\\\" height=\\\"180\\\" /\u003E\\n \\n\\nWhen a **warm front** moves into an area, warm air moves above a cool air mass. As the warm air rises, it condenses, often forming clouds and precipitation. \\n\u003Cimg src=\\\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/L4L5AssessmentTeacherGuideImage1.png\\\" width=\\\"850\\\" height=\\\"180\\\" /\u003E\\n\\nThe assessment is situated in the unit context to provide an opportunity for students to make sense about patterns when reasoning about air masses, fronts, and precipitation. In this assessment, one of the responses is scientifically correct while the other responses that relate to some informal ideas about weather that students may hold. \",\"content2\":\"\",\"mediaType\":\"none\",\"mediaCaption\":\"Last, First. \\\"Title of Work.\\\" Year created. Site Title [OR] Publisher. Gallery [OR] Location. http://www.url.com.\",\"mediaURL\":\"\"}}", + "approved_script_label": "teacherEditionTips", + "component_label": "windowShade", + "approved_script": { + "name": "Teacher Edition", + "url": "https://teacher-edition-tips-plugin.concord.org/version/v3.6.0/plugin.js", + "label": "teacherEditionTips", + "description": "This plugin provides Teacher Edition components", + "version": 3, + "json_url": "https://teacher-edition-tips-plugin.concord.org/version/v3.6.0/manifest.json", + "authoring_metadata": "{\"components\":[{\"label\":\"windowShade\",\"name\":\"Window Shades\",\"scope\":\"embeddable\",\"guiAuthoring\":true},{\"label\":\"sideTip\",\"name\":\"Side Tips\",\"scope\":\"embeddable\",\"guiAuthoring\":true},{\"label\":\"questionWrapper\",\"name\":\"Question Wrapper\",\"scope\":\"embeddable-decoration\",\"decorates\":[\"Embeddable::MultipleChoice\",\"Embeddable::OpenResponse\",\"Embeddable::ImageQuestion\",\"ManagedInteractive\",\"MwInteractive\",\"ImageInteractive\",\"VideoInteractive\"],\"guiAuthoring\":true,\"guiPreview\":true}]}" + } + }, + "is_hidden": false, + "is_full_width": true, + "type": "Embeddable::EmbeddablePlugin", + "ref_id": "10254-Embeddable::EmbeddablePlugin" + }, + "section": null + }, { + "embeddable": { + "plugin": { + "description": null, + "author_data": "{\"tipType\":\"windowShade\",\"windowShade\":{\"windowShadeType\":\"discussionPoints\",\"layout\":\"mediaLeft\",\"initialOpenState\":true,\"content\":\"###What Are Common Student Ideas and What Supports Could Help Students?\\nBelow are some issues to consider in assessing students\u2019 ideas, and some suggestions of ways to support students in developing more formal reasoning about patterns associated with fronts and precipitation.\\n\\n###Less Formal Ideas\\n\u2022\\t**Kalin\u2019s response (precipitation with a cold front coming in)** suggests that Kalin may just be thinking about patterns of familiar things going together (cold and wet, warm and sunny) rather than thinking about patterns associated with different types of air masses interacting with one another. Students may associate sun with warm, and rain and snow with cold. Based on that experience, they may think that a cold front is connected to precipitation.\\n\\nStudents who choose Kalin\u2019s response could benefit from having experiences that challenge their simple association idea. For example, looking at weather maps that show warmer air often has more moisture in it and colder air is often drier can help these students develop understanding that relationships might not be as simple as they think. Students who choose Kalin\u2019s response may not think about weather as something that happens with matter. Instead, they may just think of weather in terms of the actions of natural \\\"actors\\\" (e.g., the sun makes it warm, the wind makes it cold). These students could use help in learning that air masses are matter (they are made up of molecules and have mass). If we didn\u2019t have air masses made of matter on Earth, then we wouldn\u2019t have weather. You might talk with students about concrete examples that they can extend to think about air masses as entities made of stuff \u2013 for example, they could compare an empty balloon, a balloon filled with warm air, and a balloon filled with cold air. There is very little stuff (matter or molecules of air) in the empty balloon, while there is more stuff (matter) in the balloons filled with warm and cold air.\\n\\n###Middle Level \\n\u2022\\t**Both Alex\u2019s response (precipitation occurs with a warm front coming in)** and **Sage\u2019s response (precipitation occurs after a cold front has passed by an area)** suggest that they are aware that precipitation is associated with bodies of air moving and with the different conditions in those bodies of air (i.e., temperature, levels of humidity). However, both Sage\u2019s and Alex\u2019s ideas include some incorrect patterns that lead to problematic rules. \\n\\n\u2022\\t**Alex** thinks that cold air and warm air mixing causes precipitation. However, warm and cold air masses don\u2019t mix very readily, and it is instead actually warm air rising, expanding, and condensing that generally leads to precipitation. In addition, while Alex knows that cold fronts can be drier than warm fronts, that doesn\u2019t mean that there won\u2019t be any precipitation with cold fronts. Precipitation can occur with a cold front when warm air is pushed up, expands, and condenses.\\n\\nStudents who choose Alex\u2019s response could benefit from working with data to observe the following patterns: (1) precipitation can occur with a cold front and (2) fronts do not necessarily mix.\\n\\n\u2022\\t**Sage** thinks that cold air is humid, which leads to condensation and precipitation. However, warm air masses often have a higher level of humidity compared with cold air masses. It can be confusing that condensation occurs with rising, expanding, and cooling. The unit does not go into this in depth, however. For students who choose Sage\u2019s response, it is probably sufficient here to scaffold experiences with data and virtual storm showing the general pattern of warm air masses having higher levels of humidity than cool air masses.\\n\\n\u2022\\tStudents who choose Alex or Sage\u2019s response can also benefit from discussion and emphasis on the importance of getting the rule right (enough) in order to create a computational model that works. The students working on their weather model will not be able to predict weather with any consistency or accuracy if there is a big problem with the rule (algorithm) they have written into their computer model. \\n\\n###More Formal Idea\\n\u2022\\t**Delana\u2019s response (precipitation occurs with both cold fronts and warm fronts coming in)** is the best answer. Delana\u2019s explanation does not include a more complete mechanistic sequence involving cold air pushing warm air up; warm air rising, expanding, and condensing; and precipitation occurring as a result. This is because the Precipitating Change curriculum simplifies weather phenomena by emphasizing important patterns and de-emphasizing complicated mechanisms. This focus allows the curriculum to scaffold students in connecting observed patterns with rules that can be used to create predictive weather forecasting computer models. 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She will discuss how\u0026nbsp;making sense of the weather data helps in predicting\u0026nbsp;weather.\u003C/p\u003E", + "is_callout": true, + "is_full_width": true, + "is_hidden": false, + "name": "", + "type": "Embeddable::Xhtml", + "ref_id": "148014-Embeddable::Xhtml" + }, + "section": "header_block" + }, { + "embeddable": { + "name": "", + "url_fragment": null, + "authored_state": "{\"version\":1,\"questionType\":\"iframe_interactive\",\"poster\":\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/Captioned_Videos/Posters/Poster_L4_Video.png\",\"videoUrl\":\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/Captioned_Videos/JackieLesson4_88_Captioned.mp4\"}", + "is_hidden": false, + "is_full_width": true, + "show_in_featured_question_report": true, + "inherit_aspect_ratio_method": true, + "custom_aspect_ratio_method": null, + "inherit_native_width": true, + "custom_native_width": 576, + "inherit_native_height": true, + "custom_native_height": 435, + "inherit_click_to_play": true, + "custom_click_to_play": false, + "inherit_full_window": true, + "custom_full_window": false, + "inherit_click_to_play_prompt": true, + "custom_click_to_play_prompt": null, + "inherit_image_url": true, + "custom_image_url": null, + "library_interactive": { + "hash": "34e1a2a39c058da8ff4ffe5a09ad14af337c4a01", + "data": { + "aspect_ratio_method": "DEFAULT", + "authoring_guidance": "", + "base_url": "https://models-resources.concord.org/question-interactives/version/v1.1.0/video-player/", + "click_to_play": false, + "click_to_play_prompt": null, + "description": "This video player will not have the blue header bar above the interactive.\r\nIt does not save the students position in the video. \r\nIt will not show up in the teacher report.", + "enable_learner_state": false, + "full_window": false, + "has_report_url": false, + "image_url": null, + "name": "Video Player", + "native_height": 435, + "native_width": 576, + "no_snapshots": false, + "show_delete_data_button": false, + "thumbnail_url": "", + "customizable": false, + "authorable": true + } + }, + "type": "ManagedInteractive", + "ref_id": "1766-ManagedInteractive", + "linked_interactives": [] + }, + "section": "header_block" + }] + }, { + "additional_sections": {}, + "embeddable_display_mode": "stacked", + "id": 143593, + "is_completion": false, + "is_hidden": false, + "layout": "l-full-width", + "name": "Opening", + "position": 2, + "show_header": true, + "show_info_assessment": true, + "show_interactive": false, + "show_sidebar": false, + "sidebar": null, + "sidebar_title": "Did you know?", + "toggle_info_assessment": false, + "embeddables": [{ + "embeddable": { + "content": "\u003Cp\u003EAs weather scientists, your job is not only to collect and organize data, but also to make sense of the data you collected. One way to make sense of the data is to develop a rule, generalized statements of patterns you see again and again.\u003C/p\u003E\n\u003Cp\u003EExample: This rule has two parts that must happen to have a certain result. If it was a [ \u003Cstrong\u003Every nice summer\u003C/strong\u003E ] and if it is [ \u003Cstrong\u003EAugust\u003C/strong\u003E ], then there will be [ \u003Cstrong\u003Elots of berries to pick\u003C/strong\u003E ].\u0026nbsp;\u003C/p\u003E\n\u003Cp style=\"text-align: justify;\"\u003E\u003Cimg class=\"\" src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/RuleStatement.jpg\" alt=\"\" width=\"472\" height=\"221\" /\u003E\u003C/p\u003E\n\u003Cp\u003EThink about developing a similar statement that could be used to determine where it will rain.\u003C/p\u003E", + "is_callout": false, + "is_full_width": true, + "is_hidden": false, + "name": "", + "type": "Embeddable::Xhtml", + "ref_id": "147899-Embeddable::Xhtml" + }, + "section": "header_block" + }, { + "embeddable": { + "plugin": { + "description": "", + "author_data": "{\"tipType\":\"windowShade\",\"questionWrapper\":{\"correctExplanation\":\"correct\",\"distractorsExplanation\":\"distractor\",\"exemplar\":\"exemplar\",\"teacherTip\":\"teacherTip\",\"teacherTipImageOverlay\":\"\"},\"windowShade\":{\"windowShadeType\":\"theoryAndBackground\",\"layout\":\"mediaLeft\",\"initialOpenState\":false,\"content\":\"### LESSON 4: BUILDING RULES\\n**WHERE DOES IT RAIN?**\\n\\nIn this lesson, students develop a rule for where it will rain and test their rule using a Virtual Model. 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a/src/public/offline-activities/precipitating-change-v3/lesson-5-post.json b/src/public/offline-activities/precipitating-change-v3/lesson-5-post.json new file mode 100644 index 00000000..6f90a926 --- /dev/null +++ b/src/public/offline-activities/precipitating-change-v3/lesson-5-post.json @@ -0,0 +1,285 @@ +{ + "description": "", + "editor_mode": 0, + "layout": 0, + "name": "Alaska 2021 - Lesson 5: Post-thoughts - How should we represent wind direction?", + "notes": "", + "project_id": 25, + "related": "", + "runtime": "Activity Player", + "show_submit_button": true, + "student_report_enabled": true, + "thumbnail_url": "https://learn-resources.concord.org/images/stem-resources/icons/pc-lesson2.png", + "time_to_complete": null, + "version": 1, + "theme_name": "Precipitating Change", + "pages": [{ + "additional_sections": {}, + "embeddable_display_mode": "stacked", + "id": 143619, + "is_completion": false, + "is_hidden": false, + "layout": "l-full-width", + "name": "Page 1", + "position": 1, + "show_header": true, + "show_info_assessment": false, + "show_interactive": false, + "show_sidebar": false, + "sidebar": null, + "sidebar_title": "Did you know?", + "toggle_info_assessment": false, + "embeddables": [{ + "embeddable": { + "content": "\u003Cp\u003E\u003Cstrong\u003EHow Should We Represent Wind Direction?\u003C/strong\u003E\u003C/p\u003E\r\n\u003Cp\u003EThe word represent means to let one thing stand for another. For example, some people use the symbol of a\u003C/p\u003E\r\n\u003Cp\u003Eheart [\u003Cimg src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/Captioned_Videos/new_picts/heart2.png\" width=\"27\" height=\"23\" /\u003E] to represent (or stand for) love. \u0026nbsp;\u003C/p\u003E\r\n\u003Cp\u003EFour students in Ms. Tevuk\u0026rsquo;s class are figuring out how to represent wind direction both (1) in their computer model that does calculations to predict the weather and (2) on a map the computer model produces to show the weather prediction. The students have different ideas about how to represent wind direction for these two purposes.\u003C/p\u003E\r\n\u003Cp\u003EHere are some different options Ms. Tevuk\u0026rsquo;s students are considering for representing wind direction.\u003C/p\u003E\r\n\u003Cp\u003E\u0026bull;\u0026nbsp;\u003Cstrong\u003EWind direction represented with degree number (between 0 and 360) based on the compass\u0026nbsp;\u003C/strong\u003E\u003C/p\u003E\r\n\u003Cp\u003E\u003Cimg src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/Captioned_Videos/new_picts/Lesson_5_new_Embedded_assessment/Version2_wind_direction_with_degrees.png\" width=\"503\" height=\"230\" /\u003E\u003C/p\u003E\r\n\u003Cp\u003E\u003Cstrong\u003E\u0026bull;\u0026nbsp;Wind direction represented with letters based on the compass\u0026nbsp;\u003C/strong\u003E\u003C/p\u003E\r\n\u003Cp\u003E\u003Cstrong\u003E\u003Cimg src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/Captioned_Videos/new_picts/Lesson_5_new_Embedded_assessment/Version2_wind_direction_with_letters.png\" width=\"509\" height=\"234\" /\u003E\u003C/strong\u003E\u003C/p\u003E\r\n\u003Cp\u003E\u003Cstrong\u003E\u0026bull;\u0026nbsp;Wind direction represented with arrows\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u003C/strong\u003E\u003C/p\u003E\r\n\u003Cp\u003E\u003Cstrong\u003E\u003Cimg class=\"\" src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/Captioned_Videos/new_picts/Lesson_5_new_Embedded_assessment/Wind_direction_based_arrows.png\" alt=\"\" width=\"177\" height=\"181\" /\u003E\u003C/strong\u003E\u003C/p\u003E\r\n\u003Cp\u003E\u003Cstrong\u003E\u0026bull;\u0026nbsp;Wind direction represented with different colors\u003C/strong\u003E\u003C/p\u003E\r\n\u003Cp\u003E\u003Cstrong\u003E\u003Cimg class=\"\" src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/Captioned_Videos/new_picts/Lesson_5_new_Embedded_assessment/Wind_direction_different_colors.png\" alt=\"\" width=\"173\" height=\"177\" /\u003E\u003C/strong\u003E\u003C/p\u003E\r\n\u003Cp\u003EHere are the students\u0026rsquo; ideas:\u003C/p\u003E\r\n\u003Ctable style=\"border: solid 1px #000;\" cellpadding=\"30\"\u003E\r\n\u003Ctbody\u003E\r\n\u003Ctr\u003E\r\n\u003Cth style=\"border-right: solid 1px #000;\" colspan=\"2\"\u003E\u003Cstrong\u003EAlex\u003C/strong\u003E\u003C/th\u003E\r\n\u003Cth colspan=\"2\"\u003E\u003Cstrong\u003EDelana\u003C/strong\u003E\u003C/th\u003E\r\n\u003C/tr\u003E\r\n\u003Ctr\u003E\r\n\u003Ctd style=\"border-bottom: solid 1px #000;\" width=\"88\"\u003E\u003Cimg src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/Alex1.png\" width=\"60\" height=\"88\" align=\"center\" hspace=\"10\" vspace=\"10\" /\u003E\u003C/td\u003E\r\n\u003Ctd style=\"border-right: solid 1px #000; border-bottom: solid 1px #000; padding: 10px;\" width=\"350\"\u003E\r\n\u003Cp\u003EI think we should use the \u003Cstrong\u003Eletters for the computer model\u003C/strong\u003E because there are only 8 options, so the computer will have simple information to calculate with and it won\u0026rsquo;t get stuck computing. We can use the \u003Cstrong\u003Earrows on the map\u003C/strong\u003E because that way you can see which way the wind is going.\u003C/p\u003E\r\n\u003Cp\u003E\u003Cimg src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/Captioned_Videos/new_picts/Lesson_5_new_Embedded_assessment/Version2_letters_for_computer_model_Alex.png\" width=\"267\" height=\"183\" /\u003E\u003C/p\u003E\r\n\u003Cp\u003E\u003Cimg class=\"\" src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/Captioned_Videos/new_picts/Lesson_5_new_Embedded_assessment/Parts/Alex_Part2.png\" alt=\"\" width=\"270\" height=\"185\" /\u003E\u003C/p\u003E\r\n\u003C/td\u003E\r\n\u003Ctd style=\"border-bottom: solid 1px #000;\" width=\"88\"\u003E\u003Cimg src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/Delana1.png\" width=\"65\" height=\"92\" align=\"center\" hspace=\"10\" vspace=\"10\" /\u003E\u003C/td\u003E\r\n\u003Ctd style=\"border-bottom: solid 1px #000; padding: 10px;\" width=\"350\"\u003E\r\n\u003Cp\u003ELet\u0026rsquo;s use \u003Cstrong\u003Enumber of degrees on the computer model\u003C/strong\u003E because computers do calculations with numbers. I think we should use \u003Cstrong\u003Earrows on the map\u003C/strong\u003E because they make the pattern of wind direction easy to see.\u003C/p\u003E\r\n\u003Cp\u003E\u003Cimg src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/Captioned_Videos/new_picts/Lesson_5_new_Embedded_assessment/Version2_compass_degrees_for_computer_model_Delana.png\" width=\"269\" height=\"181\" /\u003E\u003C/p\u003E\r\n\u003Cp\u003E\u003Cimg class=\"\" src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/Captioned_Videos/new_picts/Lesson_5_new_Embedded_assessment/Parts/Delana_Part2.png\" alt=\"\" width=\"271\" height=\"180\" /\u003E\u003C/p\u003E\r\n\u003C/td\u003E\r\n\u003C/tr\u003E\r\n\u003Ctr\u003E\r\n\u003Cth style=\"border-right: solid 1px #000;\" colspan=\"2\"\u003E\u003Cstrong\u003EKalin\u003C/strong\u003E\u003C/th\u003E\r\n\u003Cth colspan=\"2\"\u003E\u003Cstrong\u003ESage\u003C/strong\u003E\u003C/th\u003E\r\n\u003C/tr\u003E\r\n\u003Ctr\u003E\r\n\u003Ctd width=\"88\"\u003E\r\n\u003Cp\u003E\u003Cimg src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/Kalin.png\" width=\"65\" height=\"88\" align=\"center\" hspace=\"10\" vspace=\"10\" /\u003E\u003C/p\u003E\r\n\u003C/td\u003E\r\n\u003Ctd style=\"border-right: solid 1px #000; padding: 10px;\" width=\"350\"\u003E\r\n\u003Cp\u003EI think we should use \u003Cstrong\u003Enumber of degrees for both the computer model and the map\u003C/strong\u003E because computers do calculations with numbers and our map should show what the computer calculated.\u003C/p\u003E\r\n\u003Cp\u003E\u003Cimg src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/Captioned_Videos/new_picts/Lesson_5_new_Embedded_assessment/Version2_compass_degrees_for_computer_model_Kalin.png\" width=\"257\" height=\"185\" /\u003E\u003C/p\u003E\r\n\u003Cp\u003E\u003Cimg src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/Captioned_Videos/new_picts/Lesson_5_new_Embedded_assessment/Version2_compass_degree_numbers_for_map_Kalin.png\" width=\"253\" height=\"181\" /\u003E\u003C/p\u003E\r\n\u003C/td\u003E\r\n\u003Ctd width=\"88\"\u003E\r\n\u003Cp\u003E\u003Cimg src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/Sage1.png\" width=\"65\" height=\"92\" align=\"center\" hspace=\"8\" vspace=\"8\" /\u003E\u003C/p\u003E\r\n\u003C/td\u003E\r\n\u003Ctd style=\"padding: 10px;\" width=\"350\"\u003E\r\n\u003Cp\u003EI think we should use \u003Cstrong\u003Ecolors for both the computer model and the map.\u003C/strong\u003E Colors are good for the map because it\u0026rsquo;s easy to see patterns in different colors. 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Pre-Assessment*\\nDuring the pre-assessment, each student will view the probe and make an individual choice. The request for explanation will only be on the post-assessment. After students make an individual commitment for the pre-assessment, you can lead a discussion including, for example, a pair/share opportunity and/or full class discussion. \\n\\nAt this time, encourage students to share and discuss their ideas and reasons without indicating that any one answer is better or worse. Let the students know that they should keep thinking about this question and that the class will return to it at the end of the lesson.\\n\",\"content2\":\"\",\"mediaType\":\"none\",\"mediaCaption\":\"Last, First. \\\"Title of Work.\\\" Year created. Site Title [OR] Publisher. 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Review the information and consider ways to scaffold students toward developing knowledge and practice as appropriate for their classes. We also recommend during the first implementation of the probe, you scaffold students to focus on student ideas about this problem, rather than on vocabulary terms such as **interpolation**. By discussing the different options, students can engage in productive talk related to data sense making and computational thinking without using technical terminology. 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For example, some people use the symbol of a\u003C/p\u003E\r\n\u003Cp\u003Eheart [\u003Cimg src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/Captioned_Videos/new_picts/heart2.png\" width=\"27\" height=\"23\" /\u003E] to represent (or stand for) love. \u0026nbsp;\u003C/p\u003E\r\n\u003Cp\u003EFour students in Ms. Tevuk\u0026rsquo;s class are figuring out how to represent wind direction both (1) in their computer model that does calculations to predict the weather and (2) on a map the computer model produces to show the weather prediction. The students have different ideas about how to represent wind direction for these two purposes.\u003C/p\u003E\r\n\u003Cp\u003EHere are some different options Ms. Tevuk\u0026rsquo;s students are considering for representing wind direction.\u003C/p\u003E\r\n\u003Cp\u003E\u0026bull;\u0026nbsp;\u003Cstrong\u003EWind direction represented with degree number (between 0 and 360) based on the compass\u0026nbsp;\u003C/strong\u003E\u003C/p\u003E\r\n\u003Cp\u003E\u003Cimg src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/Captioned_Videos/new_picts/Lesson_5_new_Embedded_assessment/Version2_wind_direction_with_degrees.png\" width=\"503\" height=\"230\" /\u003E\u003C/p\u003E\r\n\u003Cp\u003E\u003Cstrong\u003E\u0026bull;\u0026nbsp;Wind direction represented with letters based on the compass\u0026nbsp;\u003C/strong\u003E\u003C/p\u003E\r\n\u003Cp\u003E\u003Cstrong\u003E\u003Cimg src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/Captioned_Videos/new_picts/Lesson_5_new_Embedded_assessment/Version2_wind_direction_with_letters.png\" width=\"509\" height=\"234\" /\u003E\u003C/strong\u003E\u003C/p\u003E\r\n\u003Cp\u003E\u003Cstrong\u003E\u0026bull;\u0026nbsp;Wind direction represented with arrows\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u003C/strong\u003E\u003C/p\u003E\r\n\u003Cp\u003E\u003Cstrong\u003E\u003Cimg class=\"\" src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/Captioned_Videos/new_picts/Lesson_5_new_Embedded_assessment/Wind_direction_based_arrows.png\" alt=\"\" width=\"177\" height=\"181\" /\u003E\u003C/strong\u003E\u003C/p\u003E\r\n\u003Cp\u003E\u003Cstrong\u003E\u0026bull;\u0026nbsp;Wind direction represented with different colors\u003C/strong\u003E\u003C/p\u003E\r\n\u003Cp\u003E\u003Cstrong\u003E\u003Cimg class=\"\" src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/Captioned_Videos/new_picts/Lesson_5_new_Embedded_assessment/Wind_direction_different_colors.png\" alt=\"\" width=\"173\" height=\"177\" /\u003E\u003C/strong\u003E\u003C/p\u003E\r\n\u003Cp\u003EHere are the students\u0026rsquo; ideas:\u003C/p\u003E\r\n\u003Ctable style=\"border: solid 1px #000;\" cellpadding=\"30\"\u003E\r\n\u003Ctbody\u003E\r\n\u003Ctr\u003E\r\n\u003Cth style=\"border-right: solid 1px #000;\" colspan=\"2\"\u003E\u003Cstrong\u003EAlex\u003C/strong\u003E\u003C/th\u003E\r\n\u003Cth colspan=\"2\"\u003E\u003Cstrong\u003EDelana\u003C/strong\u003E\u003C/th\u003E\r\n\u003C/tr\u003E\r\n\u003Ctr\u003E\r\n\u003Ctd style=\"border-bottom: solid 1px #000;\" width=\"88\"\u003E\u003Cimg src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/Alex1.png\" width=\"60\" height=\"88\" align=\"center\" hspace=\"10\" vspace=\"10\" /\u003E\u003C/td\u003E\r\n\u003Ctd style=\"border-right: solid 1px #000; border-bottom: solid 1px #000; padding: 10px;\" width=\"350\"\u003E\r\n\u003Cp\u003EI think we should use the \u003Cstrong\u003Eletters for the computer model\u003C/strong\u003E because there are only 8 options, so the computer will have simple information to calculate with and it won\u0026rsquo;t get stuck computing. We can use the \u003Cstrong\u003Earrows on the map\u003C/strong\u003E because that way you can see which way the wind is going.\u003C/p\u003E\r\n\u003Cp\u003E\u003Cimg src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/Captioned_Videos/new_picts/Lesson_5_new_Embedded_assessment/Version2_letters_for_computer_model_Alex.png\" width=\"267\" height=\"183\" /\u003E\u003C/p\u003E\r\n\u003Cp\u003E\u003Cimg class=\"\" src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/Captioned_Videos/new_picts/Lesson_5_new_Embedded_assessment/Parts/Alex_Part2.png\" alt=\"\" width=\"270\" height=\"185\" /\u003E\u003C/p\u003E\r\n\u003C/td\u003E\r\n\u003Ctd style=\"border-bottom: solid 1px #000;\" width=\"88\"\u003E\u003Cimg src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/Delana1.png\" width=\"65\" height=\"92\" align=\"center\" hspace=\"10\" vspace=\"10\" /\u003E\u003C/td\u003E\r\n\u003Ctd style=\"border-bottom: solid 1px #000; padding: 10px;\" width=\"350\"\u003E\r\n\u003Cp\u003ELet\u0026rsquo;s use \u003Cstrong\u003Enumber of degrees on the computer model\u003C/strong\u003E because computers do calculations with numbers. I think we should use \u003Cstrong\u003Earrows on the map\u003C/strong\u003E because they make the pattern of wind direction easy to see.\u003C/p\u003E\r\n\u003Cp\u003E\u003Cimg src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/Captioned_Videos/new_picts/Lesson_5_new_Embedded_assessment/Version2_compass_degrees_for_computer_model_Delana.png\" width=\"269\" height=\"181\" /\u003E\u003C/p\u003E\r\n\u003Cp\u003E\u003Cimg class=\"\" src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/Captioned_Videos/new_picts/Lesson_5_new_Embedded_assessment/Parts/Delana_Part2.png\" alt=\"\" width=\"271\" height=\"180\" /\u003E\u003C/p\u003E\r\n\u003C/td\u003E\r\n\u003C/tr\u003E\r\n\u003Ctr\u003E\r\n\u003Cth style=\"border-right: solid 1px #000;\" colspan=\"2\"\u003E\u003Cstrong\u003EKalin\u003C/strong\u003E\u003C/th\u003E\r\n\u003Cth colspan=\"2\"\u003E\u003Cstrong\u003ESage\u003C/strong\u003E\u003C/th\u003E\r\n\u003C/tr\u003E\r\n\u003Ctr\u003E\r\n\u003Ctd style=\"border-bottom: solid 1px #000;\" width=\"88\"\u003E\r\n\u003Cp\u003E\u003Cimg src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/Kalin.png\" width=\"65\" height=\"88\" align=\"center\" hspace=\"10\" vspace=\"10\" /\u003E\u003C/p\u003E\r\n\u003C/td\u003E\r\n\u003Ctd style=\"border-right: solid 1px #000; border-bottom: solid 1px #000; padding: 10px;\" width=\"350\"\u003E\r\n\u003Cp\u003EI think we should use \u003Cstrong\u003Enumber of degrees for both the computer model and the map\u003C/strong\u003E because computers do calculations with numbers and our map should show what the computer calculated.\u003C/p\u003E\r\n\u003Cp\u003E\u003Cimg src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/Captioned_Videos/new_picts/Lesson_5_new_Embedded_assessment/Version2_compass_degrees_for_computer_model_Kalin.png\" width=\"257\" height=\"185\" /\u003E\u003C/p\u003E\r\n\u003Cp\u003E\u003Cimg src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/Captioned_Videos/new_picts/Lesson_5_new_Embedded_assessment/Version2_compass_degree_numbers_for_map_Kalin.png\" width=\"253\" height=\"181\" /\u003E\u003C/p\u003E\r\n\u003C/td\u003E\r\n\u003Ctd style=\"border-bottom: solid 1px #000;\" width=\"88\"\u003E\r\n\u003Cp\u003E\u003Cimg src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/Sage1.png\" width=\"65\" height=\"92\" align=\"center\" hspace=\"8\" vspace=\"8\" /\u003E\u003C/p\u003E\r\n\u003C/td\u003E\r\n\u003Ctd style=\"border-bottom: solid 1px #000; padding: 10px;\" width=\"350\"\u003E\r\n\u003Cp\u003EI think we should use \u003Cstrong\u003Ecolors for both the computer model and the map.\u003C/strong\u003E Colors are good for the map because it\u0026rsquo;s easy to see patterns in different colors. Then it helps to have your computer model and map match, so it makes sense to use colors for the computer model too.\u003C/p\u003E\r\n\u003Cp\u003E\u003Cimg class=\"\" src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/Captioned_Videos/new_picts/Lesson_5_new_Embedded_assessment/Parts/Sage_Part1.png\" alt=\"\" width=\"275\" height=\"193\" /\u003E\u003C/p\u003E\r\n\u003Cp\u003E\u003Cimg class=\"\" src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/Captioned_Videos/new_picts/Lesson_5_new_Embedded_assessment/Parts/Sage_Part2.png\" alt=\"\" width=\"275\" height=\"190\" /\u003E\u003C/p\u003E\r\n\u003C/td\u003E\r\n\u003C/tr\u003E\r\n\u003C/tbody\u003E\r\n\u003C/table\u003E", + "is_callout": false, + "is_full_width": true, + "is_hidden": false, + "name": "", + "type": "Embeddable::Xhtml", + "ref_id": "147929-Embeddable::Xhtml" + }, + "section": "header_block" + }, { + "embeddable": { + "name": "", + "url_fragment": null, + "authored_state": "{\"version\":1,\"questionType\":\"multiple_choice\",\"multipleAnswers\":false,\"layout\":\"vertical\",\"choices\":[{\"id\":\"1\",\"content\":\"Alex\",\"correct\":false},{\"id\":\"2\",\"content\":\"Delana\",\"correct\":false},{\"id\":\"3\",\"content\":\"Kalin\",\"correct\":false},{\"content\":\"Sage\",\"correct\":false,\"id\":\"48ed2c41-2f41-4d5e-b70c-89cc42e2eb72\"}],\"prompt\":\"\u003Cp\u003EWhich student\u2019s idea do you agree with the most?\u003C/p\u003E\"}", + "is_hidden": false, + "is_full_width": true, + "show_in_featured_question_report": true, + "inherit_aspect_ratio_method": true, + "custom_aspect_ratio_method": "DEFAULT", + "inherit_native_width": true, + "custom_native_width": 576, + "inherit_native_height": true, + "custom_native_height": 435, + "inherit_click_to_play": true, + "custom_click_to_play": false, + "inherit_full_window": true, + "custom_full_window": false, + "inherit_click_to_play_prompt": true, + "custom_click_to_play_prompt": null, + "inherit_image_url": true, + "custom_image_url": null, + "library_interactive": { + "hash": "98f3d10aa7f2fce6bdeb0ecda339fa56dc80b37c", + "data": { + "aspect_ratio_method": "DEFAULT", + "authoring_guidance": "", + "base_url": "https://models-resources.concord.org/question-interactives/version/v1.1.0/multiple-choice/", + "click_to_play": false, + "click_to_play_prompt": null, + "description": "", + "enable_learner_state": true, + "full_window": false, + "has_report_url": false, + "image_url": null, + "name": "Multiple Choice", + "native_height": 435, + "native_width": 576, + "no_snapshots": false, + "show_delete_data_button": false, + "thumbnail_url": "", + "customizable": true, + "authorable": true + } + }, + "type": "ManagedInteractive", + "ref_id": "1698-ManagedInteractive", + "linked_interactives": [] + }, + "section": "header_block" + }, { + "embeddable": { + "name": "", + "url_fragment": null, + "authored_state": "{\"version\":1,\"questionType\":\"open_response\",\"prompt\":\"\u003Cp\u003EWhy do you think the choice you picked is the best for representing wind direction in the computer model and on the map? Please explain your reasoning. \u003C/p\u003E\"}", + "is_hidden": false, + "is_full_width": true, + "show_in_featured_question_report": true, + "inherit_aspect_ratio_method": true, + "custom_aspect_ratio_method": "DEFAULT", + "inherit_native_width": true, + "custom_native_width": 576, + "inherit_native_height": true, + "custom_native_height": 435, + "inherit_click_to_play": true, + "custom_click_to_play": false, + "inherit_full_window": true, + "custom_full_window": false, + "inherit_click_to_play_prompt": true, + "custom_click_to_play_prompt": null, + "inherit_image_url": true, + "custom_image_url": null, + "library_interactive": { + "hash": "512e0a0a74a0e1cd6247a8ec98fa94dabb8a6132", + "data": { + "aspect_ratio_method": "DEFAULT", + "authoring_guidance": "", + "base_url": "https://models-resources.concord.org/question-interactives/version/v1.1.0/open-response/", + "click_to_play": false, + "click_to_play_prompt": null, + "description": "", + "enable_learner_state": true, + "full_window": false, + "has_report_url": false, + "image_url": null, + "name": "Open Response", + "native_height": 435, + "native_width": 576, + "no_snapshots": false, + "show_delete_data_button": false, + "thumbnail_url": "", + "customizable": true, + "authorable": true + } + }, + "type": "ManagedInteractive", + "ref_id": "1699-ManagedInteractive", + "linked_interactives": [] + }, + "section": "header_block" + }, { + "embeddable": { + "custom": false, + "enable_check_answer": false, + "give_prediction_feedback": false, + "hint": "", + "is_full_width": true, + "is_hidden": false, + "is_prediction": false, + "layout": "vertical", + "multi_answer": false, + "name": "Multiple Choice Question element", + "prediction_feedback": "", + "prompt": "\u003Cp\u003EWhich student\u0026rsquo;s idea do you agree with the most?\u003C/p\u003E", + "show_as_menu": false, + "show_in_featured_question_report": true, + "choices": [{ + "choice": "Alex", + "is_correct": false, + "prompt": "" + }, { + "choice": "Delana", + "is_correct": false, + "prompt": "" + }, { + "choice": "Kalin", + "is_correct": false, + "prompt": "" + }, { + "choice": "Sage", + "is_correct": false, + "prompt": "" + }], + "type": "Embeddable::MultipleChoice", + "ref_id": "17146-Embeddable::MultipleChoice" + }, + "section": null + }, { + "embeddable": { + "plugin": { + "description": null, + "author_data": "{\"tipType\":\"windowShade\",\"windowShade\":{\"windowShadeType\":\"teacherTip\",\"layout\":\"mediaLeft\",\"initialOpenState\":true,\"content\":\"###Pre-Assessment Implementation\\n*Lesson 2, Opening: How Should We Estimate the Temperature? Pre-Assessment*\\nDuring the pre-assessment, each student will view the probe and make an individual choice. The request for explanation will only be on the post-assessment. After students make an individual commitment for the pre-assessment, you can lead a discussion including, for example, a pair/share opportunity and/or full class discussion. \\n\\nAt this time, encourage students to share and discuss their ideas and reasons without indicating that any one answer is better or worse. Let the students know that they should keep thinking about this question and that the class will return to it at the end of the lesson.\\n\",\"content2\":\"\",\"mediaType\":\"none\",\"mediaCaption\":\"Last, First. \\\"Title of Work.\\\" Year created. Site Title [OR] Publisher. Gallery [OR] Location. http://www.url.com.\",\"mediaURL\":\"\"}}", + "approved_script_label": "teacherEditionTips", + "component_label": "windowShade", + "approved_script": { + "name": "Teacher Edition", + "url": "https://teacher-edition-tips-plugin.concord.org/version/v3.6.0/plugin.js", + "label": "teacherEditionTips", + "description": "This plugin provides Teacher Edition components", + "version": 3, + "json_url": "https://teacher-edition-tips-plugin.concord.org/version/v3.6.0/manifest.json", + "authoring_metadata": "{\"components\":[{\"label\":\"windowShade\",\"name\":\"Window Shades\",\"scope\":\"embeddable\",\"guiAuthoring\":true},{\"label\":\"sideTip\",\"name\":\"Side Tips\",\"scope\":\"embeddable\",\"guiAuthoring\":true},{\"label\":\"questionWrapper\",\"name\":\"Question Wrapper\",\"scope\":\"embeddable-decoration\",\"decorates\":[\"Embeddable::MultipleChoice\",\"Embeddable::OpenResponse\",\"Embeddable::ImageQuestion\",\"ManagedInteractive\",\"MwInteractive\",\"ImageInteractive\",\"VideoInteractive\"],\"guiAuthoring\":true,\"guiPreview\":true}]}" + } + }, + "is_hidden": false, + "is_full_width": true, + "type": "Embeddable::EmbeddablePlugin", + "ref_id": "10295-Embeddable::EmbeddablePlugin" + }, + "section": null + }, { + "embeddable": { + "plugin": { + "description": null, + "author_data": "{\"tipType\":\"windowShade\",\"windowShade\":{\"windowShadeType\":\"theoryAndBackground\",\"layout\":\"mediaLeft\",\"initialOpenState\":true,\"content\":\"###Computational Thinking Concept and Practice:\\n* Interpolation\\n\\n###What is the Purpose of this Assessment Probe?\\nThe following information provides background for **teachers** and is not necessarily representative of the learning goals for everything students should understand. Review the information and consider ways to scaffold students toward developing knowledge and practice as appropriate for their classes. We also recommend during the first implementation of the probe, you scaffold students to focus on student ideas about this problem, rather than on vocabulary terms such as **interpolation**. By discussing the different options, students can engage in productive talk related to data sense making and computational thinking without using technical terminology. During the ensuing lesson and the second implementation of the probe, the term interpolation can be used, as appropriate.\\n\\nThis assessment probe is designed to assess and scaffold students in thinking and talking about **interpolation**. **Interpolation** means estimating a value between ones that are known or tabulated using surrounding points or values (that is, estimating an unknown value based on surrounding information). \\n\\nThe assessment is situated within the unit context to provide an opportunity for students to make sense about interpolation of a specific, tangible weather question (i.e., temperatures along a map transect). There is always uncertainty involved when interpolating across data. Also, depending on circumstances, different methods may be appropriate. For example, if the students were trying to figure out how to dress for the day at location X, then simply choosing a number somewhere between the two might be sufficient. 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Gallery [OR] Location. http://www.url.com.\",\"mediaURL\":\"\"}}", + "approved_script_label": "teacherEditionTips", + "component_label": "windowShade", + "approved_script": { + "name": "Teacher Edition", + "url": "https://teacher-edition-tips-plugin.concord.org/version/v3.6.0/plugin.js", + "label": "teacherEditionTips", + "description": "This plugin provides Teacher Edition components", + "version": 3, + "json_url": "https://teacher-edition-tips-plugin.concord.org/version/v3.6.0/manifest.json", + "authoring_metadata": "{\"components\":[{\"label\":\"windowShade\",\"name\":\"Window Shades\",\"scope\":\"embeddable\",\"guiAuthoring\":true},{\"label\":\"sideTip\",\"name\":\"Side Tips\",\"scope\":\"embeddable\",\"guiAuthoring\":true},{\"label\":\"questionWrapper\",\"name\":\"Question Wrapper\",\"scope\":\"embeddable-decoration\",\"decorates\":[\"Embeddable::MultipleChoice\",\"Embeddable::OpenResponse\",\"Embeddable::ImageQuestion\",\"ManagedInteractive\",\"MwInteractive\",\"ImageInteractive\",\"VideoInteractive\"],\"guiAuthoring\":true,\"guiPreview\":true}]}" + } + }, + "is_hidden": false, + "is_full_width": true, + "type": "Embeddable::EmbeddablePlugin", + "ref_id": "10296-Embeddable::EmbeddablePlugin" + }, + "section": null + }, { + "embeddable": { + "plugin": { + "description": null, + "author_data": "{\"tipType\":\"windowShade\",\"windowShade\":{\"windowShadeType\":\"discussionPoints\",\"layout\":\"mediaLeft\",\"initialOpenState\":true,\"content\":\"###What Are Common Student Ideas and What Supports Could Help Students?\\nBelow are some issues to consider in assessing students\u2019 ideas, and some suggestions of ways to support students in developing more formal reasoning.\\n\\n###Less Formal Ideas\\n\u2022\\t**Kalin\u2019s response (It doesn\u2019t make sense to estimate; you need to go there and measure.)** suggests a very concrete thinking approach consistent with the idea that \u201cyou\u2019ve got to see it to believe it.\u201d \\n\\nStudents who choose Kalin\u2019s response could benefit from discussions about how while estimates and interpolations may not be perfect, they can still give us a sense of what\u2019s going on in a system when we have limited data. It might be helpful to discuss that we can never collect all the data in the world; there\u2019s too much! Because of this, we need a way to fill in missing values using the data that we do have available. \\n\\n###Middle Level \\n\u2022\\t**Both Alex\u2019s response (choose the value half way between)** and **Sage\u2019s response (choose a number closer to 59)** might be reasonable estimates in certain circumstances (e.g., for picking out what clothes to wear if you were at location X at that time). These approaches are both better than just choosing a random value as an estimate for X. However, for contexts in which more precision is called for (e.g., making a weather model), then there are ways that we can be more precise in our approaches to interpolation. \\n\\nStudents who choose Alex\u2019s and/or Sage\u2019s response could benefit from discussions of when and why we sometimes might need to be more precise in our estimation approaches. \\n\\n\\n###More Formal Idea\\n\u2022\\t**Delana\u2019s response (mark a number line with the estimate in each square going up the same amount between the two measured values)** suggests that she understands which mathematical interpolation approach will give the most precise value. Again, this level of precision will take more time and effort, and may not even be necessary in some circumstances, as discussed above. 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She will discuss how wind direction\u0026nbsp;impacts different air masses.\u003C/p\u003E", + "is_callout": true, + "is_full_width": true, + "is_hidden": false, + "name": "", + "type": "Embeddable::Xhtml", + "ref_id": "148015-Embeddable::Xhtml" + }, + "section": "header_block" + }, { + "embeddable": { + "name": "", + "url_fragment": null, + "authored_state": "{\"version\":1,\"questionType\":\"iframe_interactive\",\"videoUrl\":\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/Captioned_Videos/JackieLesson5_88_Captioned.mp4\",\"poster\":\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/Captioned_Videos/Posters/Poster_L5_Video.png\"}", + "is_hidden": false, + "is_full_width": true, + "show_in_featured_question_report": true, + "inherit_aspect_ratio_method": true, + "custom_aspect_ratio_method": null, + "inherit_native_width": true, + "custom_native_width": 576, + "inherit_native_height": true, + "custom_native_height": 435, + "inherit_click_to_play": true, + "custom_click_to_play": false, + "inherit_full_window": true, + "custom_full_window": false, + "inherit_click_to_play_prompt": true, + "custom_click_to_play_prompt": null, + "inherit_image_url": true, + "custom_image_url": null, + "library_interactive": { + "hash": "34e1a2a39c058da8ff4ffe5a09ad14af337c4a01", + "data": { + "aspect_ratio_method": "DEFAULT", + "authoring_guidance": "", + "base_url": "https://models-resources.concord.org/question-interactives/version/v1.1.0/video-player/", + "click_to_play": false, + "click_to_play_prompt": null, + "description": "This video player will not have the blue header bar above the interactive.\r\nIt does not save the students position in the video. \r\nIt will not show up in the teacher report.", + "enable_learner_state": false, + "full_window": false, + "has_report_url": false, + "image_url": null, + "name": "Video Player", + "native_height": 435, + "native_width": 576, + "no_snapshots": false, + "show_delete_data_button": false, + "thumbnail_url": "", + "customizable": false, + "authorable": true + } + }, + "type": "ManagedInteractive", + "ref_id": "1767-ManagedInteractive", + "linked_interactives": [] + }, + "section": "header_block" + }] + }, { + "additional_sections": {}, + "embeddable_display_mode": "stacked", + "id": 143599, + "is_completion": false, + "is_hidden": false, + "layout": "l-full-width", + "name": "Opening", + "position": 2, + "show_header": true, + "show_info_assessment": true, + "show_interactive": false, + "show_sidebar": false, + "sidebar": null, + "sidebar_title": "Did you know?", + "toggle_info_assessment": false, + "embeddables": [{ + "embeddable": { + "content": "\u003Cp\u003EHave you ever noticed that the wind can come from one direction and then a few hours later a different direction? As weather scientists, you will explore a new component of the\u0026nbsp;weather\u0026nbsp;- wind! The direction of the wind can give you clues about what\u0026nbsp;weather\u0026nbsp;to expect. And when the wind changes its direction drastically, interesting\u0026nbsp;weather\u0026nbsp;events can happen.\u003C/p\u003E\n\u003Cp\u003E\u003Cbr /\u003EIn this lesson you will explore how air masses interact by\u0026nbsp;setting up a wind table. You will also revisit weather station data and radar maps you used in Lesson 1 with some additions: wind data and five more\u0026nbsp;weather\u0026nbsp;stations. In your Science Notebook, go to Lesson 5 to locate the following information:\u0026nbsp;\u003Cbr /\u003E\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; 0 Map with Additional Weather Stations and Data Tables\u0026nbsp;\u003Cbr /\u003E\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; 0 Alaskan Stations 7 pm Readings \u003Cbr /\u003E\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; 0 Alaskan Stations 7 pm Interpolated Map\u003Cbr /\u003E\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;0 Alaskan Stations 7 am Interpolated Map\u003Cbr /\u003E\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u003C/p\u003E", + "is_callout": false, + "is_full_width": true, + "is_hidden": false, + "name": "", + "type": "Embeddable::Xhtml", + "ref_id": "147905-Embeddable::Xhtml" + }, + "section": "header_block" + }, { + "embeddable": { + "plugin": { + "description": "", + "author_data": "{\"tipType\":\"windowShade\",\"questionWrapper\":{\"correctExplanation\":\"correct\",\"distractorsExplanation\":\"distractor\",\"exemplar\":\"exemplar\",\"teacherTip\":\"teacherTip\",\"teacherTipImageOverlay\":\"\"},\"windowShade\":{\"windowShadeType\":\"theoryAndBackground\",\"layout\":\"mediaLeft\",\"initialOpenState\":false,\"content\":\"###LESSON 5: IDENTIFYING AIR MASSES\\n\\n**WHERE DOES THE AIR COME FROM?**\\n\\nIn this lesson, students investigate the role that wind plays in determining the weather and are introduced to ways to identify and define an air mass. Air masses have a similar range of weather variables (temperature and moisture), have indistinct boundaries, and are categorized by the range of weather variables within them. The air within an air mass is constantly moving and precipitation can occur where air from different air masses mixes/interacts. Scientists use models to predict where precipitation will occur based on where different air masses interact, the type of air in each, and the movement of that air.\\n\\nTo begin to identify air masses, students will do a hands-on wind table activity, and get new temperature, air moisture content, and wind direction data for five additional weather stations. As in Lesson 4, the students once again construct a set of rules through a series of activities that allow them to uncover patterns in the data, investigate the mechanisms for these patterns, and abstract a rule that describes the relationship between wind direction, its associated air mass, and the resulting precipitation. \\n\\n###LEARNING GOALS\\nStudents will be able to:\\n\\n* Identify and define an air mass\\n\\n* Explain that air masses are defined by where they come from\\n\\n* Explain the role of wind in weather events\\n\\n* Identify where on a map two different masses are interacting/mixing\\n\\n* Develop a rule for how wind moves and test the rule with multiple kinds of air masses\\n\\n* Develop a rule to express the relationship between weather components (temperature and moisture) and air masses\\n\\nComputational Thinking (CT) skills introduced in this lessons can be found in the table below:\\n\\n| CT Skill | Definition |\\n|---------------------|---------------------------------------------------------------------------------------------------|------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|\\n| Pattern Recognition | Recognizing that data or information is repeating in a logical (expected) way |\\n| Rule Abstraction | Developing a statement of how things work based on the patterns you observed |\\n| Rule Testing | Investigating whether a rule will still be true in different situations |\\n| Rule Refinement | Modifying a rule to be more precise (exact, careful about details) to work in the model |\",\"content2\":\"\",\"mediaType\":\"none\",\"mediaCaption\":\"Last, First. \\\"Title of Work.\\\" Year created. 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(25 mins)\\n\\n* Post-Assessment - What Are the Rules for Fronts and Precipitation? (10 mins)\\n\\n###MATERIALS AND SET-UP\\n\\nActivity 1 - What is an Air Mass?\\n\\nPer Research Team:\\n\\n* Direct students to Lesson 5 in their Science Notebooks to find the following information:\\n * Lesson 5, Activity 1: Wind Table Instructions and Questions\\n * Lesson 5, Activity 2: Additional Weather Station Data\\n * Lesson 5, Activity 2: Weather Stations 7 pm Readings\\n * Lesson 5, Activity 2: Weather Stations 7 pm Interpolated\\n * Lesson 5, Activity 2: 7 pm Weather Station Data and 7 pm Radar Map\\n * Lesson 5, Activity 2: 7 am Weather Station Data \\n\\nPer Class:\\n\\n* Set up on one demonstration table that students can gather around: a wind fan, a piece of paper with a wind rose taped to the table, and a single weather vane. See below for a top-down view. \\n\\n\u003Cimg src=\\\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/Lesson5WIndTablesTopDownView1.jpg\\\" width=\\\"400\\\" height=\\\"350\\\"\u003E\\n\\n* To print the wind rose, click [here](https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/WindCompass.jpg) to download. \",\"content2\":\"\",\"mediaType\":\"none\",\"mediaCaption\":\"Last, First. \\\"Title of Work.\\\" Year created. Site Title [OR] Publisher. Gallery [OR] Location. http://www.url.com.\",\"mediaURL\":\"\"}}", + "approved_script_label": "teacherEditionTips", + "component_label": "windowShade", + "approved_script": { + "name": "Teacher Edition", + "url": "https://teacher-edition-tips-plugin.concord.org/version/v3.6.0/plugin.js", + "label": "teacherEditionTips", + "description": "This plugin provides Teacher Edition components", + "version": 3, + "json_url": "https://teacher-edition-tips-plugin.concord.org/version/v3.6.0/manifest.json", + "authoring_metadata": "{\"components\":[{\"label\":\"windowShade\",\"name\":\"Window Shades\",\"scope\":\"embeddable\",\"guiAuthoring\":true},{\"label\":\"sideTip\",\"name\":\"Side Tips\",\"scope\":\"embeddable\",\"guiAuthoring\":true},{\"label\":\"questionWrapper\",\"name\":\"Question Wrapper\",\"scope\":\"embeddable-decoration\",\"decorates\":[\"Embeddable::MultipleChoice\",\"Embeddable::OpenResponse\",\"Embeddable::ImageQuestion\",\"ManagedInteractive\",\"MwInteractive\",\"ImageInteractive\",\"VideoInteractive\"],\"guiAuthoring\":true,\"guiPreview\":true}]}" + } + }, + "is_hidden": false, + "is_full_width": true, + "type": "Embeddable::EmbeddablePlugin", + "ref_id": "10260-Embeddable::EmbeddablePlugin" + }, + "section": null + }, { + "embeddable": { + "plugin": { + "description": null, + "author_data": "{\"tipType\":\"windowShade\",\"windowShade\":{\"windowShadeType\":\"framing\",\"layout\":\"mediaLeft\",\"initialOpenState\":true,\"content\":\"Watch this video with your class to give students a perspective on the importance of weather and to build weather science career awareness.\",\"content2\":\"\",\"mediaType\":\"video\",\"mediaCaption\":\"Purcell, Jackie. \\\"Lesson 5.\\\" 2019. Good Life Productions. Anchorage, AK.\",\"mediaURL\":\"https://precipitatingchange-resources.concord.org/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/JackieLesson5_88.mp4\"}}", + "approved_script_label": "teacherEditionTips", + "component_label": "windowShade", + "approved_script": { + "name": "Teacher Edition", + "url": "https://teacher-edition-tips-plugin.concord.org/version/v3.6.0/plugin.js", + "label": "teacherEditionTips", + "description": "This plugin provides Teacher Edition components", + "version": 3, + "json_url": "https://teacher-edition-tips-plugin.concord.org/version/v3.6.0/manifest.json", + "authoring_metadata": "{\"components\":[{\"label\":\"windowShade\",\"name\":\"Window Shades\",\"scope\":\"embeddable\",\"guiAuthoring\":true},{\"label\":\"sideTip\",\"name\":\"Side Tips\",\"scope\":\"embeddable\",\"guiAuthoring\":true},{\"label\":\"questionWrapper\",\"name\":\"Question Wrapper\",\"scope\":\"embeddable-decoration\",\"decorates\":[\"Embeddable::MultipleChoice\",\"Embeddable::OpenResponse\",\"Embeddable::ImageQuestion\",\"ManagedInteractive\",\"MwInteractive\",\"ImageInteractive\",\"VideoInteractive\"],\"guiAuthoring\":true,\"guiPreview\":true}]}" + } + }, + "is_hidden": false, + "is_full_width": true, + "type": "Embeddable::EmbeddablePlugin", + "ref_id": "10261-Embeddable::EmbeddablePlugin" + }, + "section": null + }] + }, { + "additional_sections": {}, + "embeddable_display_mode": "stacked", + "id": 143600, + "is_completion": false, + "is_hidden": false, + "layout": "l-full-width", + "name": "What is an air mass?", + "position": 3, + "show_header": true, + "show_info_assessment": true, + "show_interactive": false, + "show_sidebar": false, + "sidebar": null, + "sidebar_title": "Did you know?", + "toggle_info_assessment": false, + "embeddables": [{ + "embeddable": { + "content": "\u003Cp\u003E\u003Cstrong\u003EMeasuring Wind with the Compass\u0026nbsp;\u003C/strong\u003E\u003C/p\u003E\n\u003Cp\u003EOne way wind direction\u0026nbsp;can be measured is with\u0026nbsp;a weather\u0026nbsp;vane or air socks. When the wind blows, the\u0026nbsp;weather\u0026nbsp;vane rotates and lines up with the path the air is flowing. So,\u0026nbsp;wind direction\u0026nbsp;is determined by what direction the wind is blowing and measured in degrees (\u0026deg;).\u003C/p\u003E\n\u003Cp\u003E\u003Cimg class=\"\" style=\"display: block; margin-left: auto; margin-right: auto;\" src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/WindCompass.jpg\" alt=\"\" width=\"323\" height=\"328\" /\u003E\u003C/p\u003E\n\u003Cp\u003EIn this activity, you will use a Wind Table to map the movement of air on a grid representing a region in Alaska. Go to your Science Notebooks, Lesson 5, page 21, for further instructions and to record your observations.\u003C/p\u003E\n\u003Cp\u003E\u003Cstrong\u003EWind Table\u003C/strong\u003E\u003C/p\u003E\n\u003Cp\u003E\u003Cimg style=\"display: block; margin-left: auto; margin-right: auto;\" src=\"https://precipitatingchange-resources.concord.org/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/WindTunnels.png\" width=\"576\" height=\"510\" /\u003E\u003C/p\u003E\n\u003Cp\u003E\u0026nbsp;\u003C/p\u003E", + "is_callout": false, + "is_full_width": true, + "is_hidden": false, + "name": "", + "type": "Embeddable::Xhtml", + "ref_id": "147906-Embeddable::Xhtml" + }, + "section": "header_block" + }, { + "embeddable": { + "plugin": { + "description": "", + "author_data": "{\"tipType\":\"windowShade\",\"questionWrapper\":{\"correctExplanation\":\"correct\",\"distractorsExplanation\":\"distractor\",\"exemplar\":\"exemplar\",\"teacherTip\":\"teacherTip\",\"teacherTipImageOverlay\":\"\"},\"windowShade\":{\"windowShadeType\":\"theoryAndBackground\",\"layout\":\"mediaLeft\",\"initialOpenState\":false,\"content\":\"\\n###Activity 1 - **What is an Air Mass?**\\nIn this activity students explore the patterns of air movement within and between air masses. Using a hands-on \u201cwind table,\u201d they engage in a tangible interaction with wind. By leveraging patterns from the previous activity dataset and the wind table, they will discover that when two air masses meet, the air converges. Weather scientists refer to these regions as fronts. \\n\\n###Wind Table Directions\\n * **1.Introduce the Wind Table.** Wind is one of the first things that atmospheric scientists look at when investigating the weather, but it can be difficult to understand by just looking at data and maps. A hands-on model is helpful to investigate a phenomenon like the wind.\\n\\n\\n * **2.Assign teams:** Assign research teams a Wind Table position number, either #1 or #2. \\n * **3.Wind tunnel position:** Have students place wind tunnel #1 and wind tunnel #2 according to the diagram in their Science Notebook for their assigned Team #.\\n * **4.Reminders:** Read over the things to keep in mind on page 21 in the Science Notebook, together as a class:\\n * **BE CAREFUL NOT TO PUT YOUR FINGERS NEAR THE FAN**\\n * Graph paper represents a region.\\n * A wind vane can be placed anywhere on the graph paper to determine what direction the wind is coming from.\\n * Record the wind direction by drawing an arrow in the direction the wind vane is pointing. (Recall that wind is always recorded showing the direction the wind is coming from.) If there is not a clear determination where the wind is coming from, then leave the square blank.\\n * Place a Styrofoam ball on the wind table to see the interaction between the two air masses.\\n * **5.Analyze air mass interactions** \\n\\n * Once all of the groups have finished mapping the wind direction, ask the students to determine the boundary of the two air masses by drawing a circle around the different air masses. \\n\\n * Ask the students if there was anywhere on the grid that they either had trouble deciding what direction to draw their arrow. Some students might remark that the wind vane wobbles or spins in the region between the two distinct air masses. Instruct the students to identify the diagonal region between the two air masses and circle this area with a green marker. \\n\\n* **6.Connecting the Wind Table to the interpolated map.** Ask students to compare Alaska Weather Stations: 7 pm Interpolated data with the wind map they created on their Wind Table. Lead a class conversation. See possible Discussion Points below. \\n\",\"content2\":\"\",\"mediaType\":\"none\",\"mediaCaption\":\"Last, First. \\\"Title of Work.\\\" Year created. Site Title [OR] Publisher. 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(Note that scientists also include pressure, but pressure is not covered in this unit.)\\n\\n###Wind Table Demonstration \\nThe compass rose describes the direction the wind is blowing in degrees. Wind coming directly from the South has a direction of 180\u00b0, from the East 90\u00b0, from the North 360\u00b0, etc. Place the fan to the \u201cNorth\u201d of the weather vane and turn it on. Move the weather vane so that it's at the center of the rose and have students read the wind direction from the rose. Then, move the fan to other locations. Ask students where you should move the fan to get a wind direction of, for example, 180\u00b0, 90\u00b0, 45\u00b0, etc. Move the fan to check their predictions. \\n\\n**Teacher Note:** Wind direction is determined by what direction the wind is coming from. This is a consequence of how it is measured. 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(cont.)", + "position": 4, + "show_header": true, + "show_info_assessment": true, + "show_interactive": true, + "show_sidebar": false, + "sidebar": null, + "sidebar_title": "Did you know?", + "toggle_info_assessment": false, + "embeddables": [{ + "embeddable": { + "content": "\u003Cp\u003EIDENTIFYING AIR MASSES\u003C/p\u003E\r\n\u003Cp\u003EIn Lesson 5 of your Science Notebook on pages 21-23, you have additional data weather station data and maps that show you the direction of the wind. On page 22, you will find a map that shows you the 7 pm reading from the additional weather stations. The arrows on the map represent the\u0026nbsp;wind direction. The data on page 23 of your Science Notebook, \"Weather Stations 7 pm Interpolated\" comes from an\u0026nbsp;interpolation\u0026nbsp;of wind direction\u0026nbsp;across the mainland of Alaska at 7 pm. See map below. Using the map on page 23, draw a line that splits the map into two parts: one section with the wind coming from the same direction and the other section with the wind coming from a different direction. It is your job to determine where you see that change in the\u0026nbsp;wind direction.\u003C/p\u003E\r\n\u003Cp\u003EStrategy for Identifying Two Air Masses:\u003C/p\u003E\r\n\u003Cp\u003E1. Make Sense of the Map:\u0026nbsp;\u003Cbr /\u003E\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026bull; Look at each row and see if the arrows change direction as you move across the row.\u0026nbsp;\u003Cbr /\u003E\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026bull; Look at each column and see if the arrows change direction as you move down the column.\u0026nbsp;\u003Cbr /\u003E2. Identify where you are going to place your line.\u0026nbsp;\u003Cbr /\u003E3. Draw your line on your paper map.\u003C/p\u003E", + "is_callout": false, + "is_full_width": true, + "is_hidden": false, + "name": "", + "type": "Embeddable::Xhtml", + "ref_id": "147907-Embeddable::Xhtml" + }, + "section": "header_block" + }, { + "embeddable": { + "default_text": "", + "give_prediction_feedback": false, + "hint": "", + "is_full_width": true, + "is_hidden": false, + "is_prediction": false, + "name": "", + "prediction_feedback": "", + "prompt": "\u003Cp\u003EWhy did you draw the line there?\u003C/p\u003E", + "show_in_featured_question_report": true, + "type": "Embeddable::OpenResponse", + "ref_id": "208885-Embeddable::OpenResponse" + }, + "section": null + }, { + "embeddable": { + "aspect_ratio_method": "DEFAULT", + "authored_state": "", + "click_to_play": false, + "click_to_play_prompt": null, + "enable_learner_state": false, + "full_window": false, + "has_report_url": false, + "image_url": null, + "is_full_width": true, + "is_hidden": false, + "model_library_url": null, + "name": "Identifying Air Masses and Fronts", + "native_height": 435, + "native_width": 576, + "no_snapshots": false, + "show_delete_data_button": true, + "show_in_featured_question_report": true, + "url": "https://s3.amazonaws.com/cc-project-resources/precipitatingchange/Models-2021/Lesson5-air-masses.v4.html", + "type": "MwInteractive", + "ref_id": "97692-MwInteractive", + "linked_interactives": [] + }, + "section": "interactive_box" + }] + }, { + "additional_sections": {}, + "embeddable_display_mode": "stacked", + "id": 143602, + "is_completion": false, + "is_hidden": false, + "layout": "l-full-width", + "name": "What is an air mass? (cont.)", + "position": 5, + "show_header": true, + "show_info_assessment": true, + "show_interactive": false, + "show_sidebar": false, + "sidebar": null, + "sidebar_title": "Did you know?", + "toggle_info_assessment": false, + "embeddables": [{ + "embeddable": { + "content": "\u003Cp\u003EThe line that you drew across your map represents a boundary between two\u0026nbsp;air masses. An air mass is a body of air with similar temperature and\u0026nbsp;air moisture\u0026nbsp;content. Identifying air masses and their properties is an important part of the work of atmospheric scientists. On the map you may have noticed a temperature number at the top of the square and an\u0026nbsp;air moisture\u0026nbsp;content number at the bottom of the square.\u003C/p\u003E\n\u003Cp\u003E\u003Cimg style=\"display: block; margin-left: auto; margin-right: auto;\" src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/TempMoisture.jpg\" width=\"212\" height=\"292\" /\u003E\u003C/p\u003E", + "is_callout": false, + "is_full_width": true, + "is_hidden": false, + "name": "", + "type": "Embeddable::Xhtml", + "ref_id": "147908-Embeddable::Xhtml" + }, + "section": "header_block" + }, { + "embeddable": { + "content": "\u003Cp\u003EDevelop a way to define the two air masses using the temperature and\u0026nbsp;air moisture\u0026nbsp;content values provided on the Alaskan Stations: Interpolated at 7 pm Map.\u003C/p\u003E\r\n\u003Cp\u003E\u003Cimg 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#2.\u003C/p\u003E\r\n\u003Cp\u003EAir Mass #1 is:\u003C/p\u003E", + "show_as_menu": false, + "show_in_featured_question_report": true, + "choices": [{ + "choice": "more moist", + "is_correct": false, + "prompt": "" + }, { + "choice": "more dry", + "is_correct": false, + "prompt": "" + }], + "type": "Embeddable::MultipleChoice", + "ref_id": "17141-Embeddable::MultipleChoice" + }, + "section": null + }, { + "embeddable": { + "custom": false, + "enable_check_answer": false, + "give_prediction_feedback": false, + "hint": "", + "is_full_width": true, + "is_hidden": false, + "is_prediction": false, + "layout": "vertical", + "multi_answer": false, + "name": "Multiple Choice Question element", + "prediction_feedback": "", + "prompt": "\u003Cp\u003E\u003Cstrong\u003EAir Mass #2 Properties\u003C/strong\u003E\u003C/p\u003E\r\n\u003Cp\u003ETemperature: Compare Air Mass #2 to Air Mass #1.\u003C/p\u003E\r\n\u003Cp\u003EAir Mass #2 over land is:\u003C/p\u003E", + "show_as_menu": false, + 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are very interested in fronts because they are where the\u0026nbsp;weather\u0026nbsp;can change. Sometimes this change is very sudden.\u003C/p\u003E", + "is_callout": false, + "is_full_width": true, + "is_hidden": false, + "name": "", + "type": "Embeddable::Xhtml", + "ref_id": "147910-Embeddable::Xhtml" + }, + "section": "header_block" + }, { + "embeddable": { + "content": "\u003Cp\u003EGo to page 24 in your Science Notebook and compare the 7 pm interpolated map and the 7 pm radar map.\u003C/p\u003E\r\n\u003Cp\u003E\u003Cimg class=\"\" src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/Lesson5_7pmInterpolatedRADARMAPcomparison.jpg\" alt=\"\" width=\"860\" height=\"300\" /\u003E\u003C/p\u003E\r\n\u003Cp\u003EDiscuss with your research team and write a general statement that answers the question, \u0026ldquo;How do air masses affect where it rains?\"\u0026nbsp;\u0026nbsp;\u003C/p\u003E\r\n\u003Cp\u003E\u0026nbsp;\u003C/p\u003E", + "is_callout": true, + "is_full_width": true, + "is_hidden": false, + "name": "TASK", + "type": "Embeddable::Xhtml", + "ref_id": "147911-Embeddable::Xhtml" + }, + "section": null + }, { + "embeddable": { + "default_text": "", + "give_prediction_feedback": false, + "hint": "\u003Cp\u003E\u0026bull; Where is the front? Where is it raining? How do they compare?\u003Cbr /\u003E\u0026bull; How does the location of the precipitation on the radar map compare to the warm air mass, the cold air mass, and the front?\u003Cbr /\u003E\u0026bull; What is the air like where it is raining?\u003C/p\u003E", + "is_full_width": true, + "is_hidden": false, + "is_prediction": false, + "name": "", + "prediction_feedback": "", + "prompt": "\u003Cp\u003EHow do air masses affect where it rains?\u003C/p\u003E", + "show_in_featured_question_report": true, + "type": "Embeddable::OpenResponse", + "ref_id": "208886-Embeddable::OpenResponse" + }, + "section": null + }, { + "embeddable": { + "content": "\u003Cp\u003EGo to page 25 in your Science Notebook and work with you research team to make a prediction for where you think it could rain at 7 am by drawing on the 7 am weather station map in your notebook.\u003C/p\u003E\r\n\u003Cp\u003E\u003Cimg src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/L4_ACT1_Alaska%20Weather%20Stations_7am%20Interpolated.png\" width=\"437\" height=\"263\" /\u003E\u003C/p\u003E\r\n\u003Cp\u003EAlaska Stations: Interpolated at 7 am\u003C/p\u003E", + "is_callout": true, + "is_full_width": true, + "is_hidden": false, + "name": "TASK", + "type": "Embeddable::Xhtml", + "ref_id": "147912-Embeddable::Xhtml" + }, + "section": null + }, { + "embeddable": { + "default_text": "", + "give_prediction_feedback": false, + "hint": "", + "is_full_width": true, + "is_hidden": false, + "is_prediction": false, + "name": "", + "prediction_feedback": "", + "prompt": "\u003Cp\u003EExplain why you think it could rain in the area you selected.\u003C/p\u003E", + "show_in_featured_question_report": true, + "type": "Embeddable::OpenResponse", + "ref_id": "208887-Embeddable::OpenResponse" + }, + "section": null + }, { + "embeddable": { + "plugin": { + "description": "", + "author_data": "{\"tipType\":\"windowShade\",\"questionWrapper\":{\"correctExplanation\":\"correct\",\"distractorsExplanation\":\"distractor\",\"exemplar\":\"exemplar\",\"teacherTip\":\"teacherTip\",\"teacherTipImageOverlay\":\"\",\"location\":\"bottom\"},\"windowShade\":{\"windowShadeType\":\"discussionPoints\",\"layout\":\"mediaLeft\",\"initialOpenState\":false,\"content\":\"###Identifying Air Masses\\n\\nPossible discussion questions:\\n\\n* How do we identify air masses? 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Sometimes it feels cold; sometimes it feels warm. The wind is what moves air. Weather scientists use\u0026nbsp;wind direction\u0026nbsp;to distinguish multiple air masses. What happens at the boundary of those two air masses? You will explore that question using a new Virtual Model. \u0026nbsp;\u003C/p\u003E", + "is_callout": false, + "is_full_width": true, + "is_hidden": false, + "name": "", + "type": "Embeddable::Xhtml", + "ref_id": "147914-Embeddable::Xhtml" + }, + "section": "header_block" + }, { + "embeddable": { + "content": "\u003Cp\u003EThis model shows wind as moving arrowheads and precipitation as green circles. There are two air masses. Identify where the front is.\u0026nbsp;\u003C/p\u003E\r\n\u003Cp\u003EThen, by trying different settings of the temperature and moisture, see if you can make up a rule for what conditions produce precipitation along the front, and on which side of the front the precipitation will occur.\u0026nbsp;\u003C/p\u003E\r\n\u003Cp\u003EStart by pressing \u003Cstrong\u003ESetup\u003C/strong\u003E and \u003Cstrong\u003ERun\u003C/strong\u003E. As you change temperatures and moisture settings you may want to press \u003Cstrong\u003ESetup\u003C/strong\u003E occasionally to start fresh. Be sure to discuss what you find with your research team.\u003C/p\u003E", + "is_callout": true, + "is_full_width": true, + "is_hidden": false, + "name": "TASK ", + "type": "Embeddable::Xhtml", + "ref_id": "147915-Embeddable::Xhtml" + }, + "section": null + }, { + "embeddable": { + "default_text": "", + "give_prediction_feedback": false, + "hint": "", + "is_full_width": true, + "is_hidden": false, + "is_prediction": false, + "name": "", + "prediction_feedback": "", + "prompt": "\u003Cp\u003EDescribe the position of the front, and explain how you know this.\u003C/p\u003E\r\n\u003Cp\u003EYou may use city names as landmarks.\u003C/p\u003E", + "show_in_featured_question_report": true, + "type": "Embeddable::OpenResponse", + "ref_id": "208890-Embeddable::OpenResponse" + }, + "section": null + }, { + "embeddable": { + "default_text": "", + "give_prediction_feedback": false, + "hint": "\u003Cp\u003E\u0026bull; Look at the temperature values for Air Mass 1 and Air Mass 2\u003Cbr /\u003E\u0026bull; Look at the moisture values for Air Mass 1 and Air Mass 2\u003C/p\u003E", + "is_full_width": true, + "is_hidden": false, + "is_prediction": false, + "name": "", + "prediction_feedback": "", + "prompt": "\u003Cp\u003EWhat are the conditions in the model that result in precipitation happening along a front?\u003C/p\u003E", + "show_in_featured_question_report": true, + "type": "Embeddable::OpenResponse", + "ref_id": "208891-Embeddable::OpenResponse" + }, + "section": null + }, { + "embeddable": { + "default_text": "", + "give_prediction_feedback": false, + "hint": "\u003Cp\u003E\u0026bull; Is the precipitation happening more on the colder side of the front?\u003Cbr /\u003E\u0026bull; Is the precipitation happening more on the warmer side of the front?\u003C/p\u003E", + "is_full_width": true, + "is_hidden": false, + "is_prediction": false, + "name": "", + "prediction_feedback": "", + "prompt": "\u003Cp\u003EDescribe specifically where the precipitation happens within the front.\u003C/p\u003E", + "show_in_featured_question_report": true, + "type": "Embeddable::OpenResponse", + "ref_id": "208892-Embeddable::OpenResponse" + }, + "section": null + }, { + "embeddable": { + "default_text": "", + "give_prediction_feedback": false, + "hint": "\u003Cp\u003EMake sure to use precise language and include both temperature and moisture values.\u003C/p\u003E", + "is_full_width": true, + "is_hidden": false, + "is_prediction": false, + "name": "", + "prediction_feedback": "", + "prompt": "\u003Cp\u003EFinalize your rule statement for \u0026ldquo;How do air masses affect where it rains?\u0026rdquo;\u003C/p\u003E", + "show_in_featured_question_report": true, + "type": "Embeddable::OpenResponse", + "ref_id": "208893-Embeddable::OpenResponse" + }, + "section": null + }, { + "embeddable": { + "plugin": { + "description": null, + "author_data": "{\"tipType\":\"windowShade\",\"windowShade\":{\"windowShadeType\":\"theoryAndBackground\",\"layout\":\"mediaLeft\",\"initialOpenState\":true,\"content\":\"###Activity 3 - How Do Air Masses Affect Precipitation? Virtual Model\\n\\n**Objective:** To build students\u2019 rule refinement skills by experimenting with a model to figure out its built-in weather rules. In this model, precipitation falls under a variety of conditions that can be set by changing temperatures and moisture for two air masses. \\n\\nStudents can vary the temperature and moisture of two air masses in order to better understand how interacting air masses create patterns of rain at a front. Through this process, students will come up with an even more robust rule for predicting rain that involves interacting air masses. The specific computational thinking practice highlighted and practiced in this activity is **Rule Refinement**.\\n\\n**1. Class discussion about air mass properties.**Use the Alaska Weather Stations: 7am Interpolated map! [](https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/Lesson5AirMasses1and2.jpg) to remind students of the properties of the air masses in their regional weather system. See Discussion Points below for possible prompts. \\n\\n**2. Set up the model challenge.** \\n\\n* Have students recall the rule they developed to answer the question \u201cHow do air masses affect where it rains?\u201d \\n\\n* Students will use the Lesson 5 virtual model to help refine their rule.\\n\\n**3. Exploring the Virtual Model.** \\n\\nIntroduce the task, and give students time to explore the model. Then let them tell you what they discovered. They may notice:\\n\\n * The properties of the incoming air can be changed using the sliders on the left and bottom.\\n\\n * The direction of the wind can be seen with arrows and trails that can be turned on or off.\\n\\n * Precipitation appears as green circles with bigger circles meaning heavier rain.\\n\\n * Color of arrows correspond to temperature (Red = Warm, Blue = Cold, Purple = In Between)\\n\\n * Size of arrows correspond to air moisture (Small = dry, Large = moist or humid)\\n\\nYou may want to point out that\\n\\n * Even though the air in the model moves, the model shows airflow for a certain time. Time does not change.\\n\\n**4. Experiment with the Model to find the Rule**\\n\\nTell students that this model has a built-in rule for precipitation made by the model\u2019s programmer. 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Ask students to discuss what they noticed about the model and what they learned from experimenting with it. The model is complex so there can be many viewpoints. The objective of this is to have students feel that they can learn from the model themselves. All observations are valid and up for discussion.\\n\\nPossible topics for discussion:\\n* It may be most valuable to discuss the questions student's answered on this page. An extended discussion could come from the question below.\\n\\n* What do the sizes and colors of the wind arrowheads mean? (The redder the warmer; the bluer the cooler; the larger the more moist; and the smaller the drier.)\\n\\n* Does precipitation fall only near the front? (No, it can fall where the arrowheads converge or come closer together.)\\n\\n* If the south settings and the west setting are the same, is there a front? (No, but the air may still converge.)\\n\\n* Do you see precipitation even where there is no front? What is a rule for it forming? 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students wrote rules for their computer model to predict weather in Alaska. Then they tested their model to see how well it worked. They found their predictions were only right about half the time. The students had different ideas for improving the model.\u003C/p\u003E\r\n\u003Cp\u003EHere are the students\u0026rsquo; ideas:\u003C/p\u003E\r\n\u003Ctable cellpadding=\"30\"\u003E\r\n\u003Ctbody\u003E\r\n\u003Ctr\u003E\r\n\u003Cth colspan=\"2\"\u003E\u003Cstrong\u003EAlex\u003C/strong\u003E\u003C/th\u003E\r\n\u003Cth colspan=\"2\"\u003E\u003Cstrong\u003EDelana\u003C/strong\u003E\u003C/th\u003E\r\n\u003C/tr\u003E\r\n\u003Ctr\u003E\r\n\u003Ctd width=\"88\"\u003E\u003Cimg src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/Alex%206.png\" width=\"72\" height=\"90\" align=\"center\" hspace=\"10\" vspace=\"10\" /\u003E\u003C/td\u003E\r\n\u003Ctd style=\"padding: 10px;\" width=\"350\"\u003EWe need to run the model longer. The longer you run a computer model the better the prediction will be.\u003C/td\u003E\r\n\u003Ctd width=\"88\"\u003E\u003Cimg src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/Delana6.png\" width=\"70\" height=\"90\" align=\"center\" hspace=\"10\" vspace=\"10\" /\u003E\u003C/td\u003E\r\n\u003Ctd style=\"padding: 10px;\" width=\"350\"\u003EThere\u0026rsquo;s no way to make a computer model that can predict the weather. 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We sometimes see this type of reasoning when students and even adults talk about climate change models. Some people say things like, \u201cthey are just models, so they don\u2019t really tell us what\u2019s going to happen in the real world.\u201d \\n\\nStudents who choose Delana\u2019s response could use support in developing understanding that computer models don\u2019t need to be perfect in order to be useful. No model is perfectly accurate. Models just need to be good enough for a given purpose. Computer modelers set calibration targets that define how close to the actual event they want their prediction to be (e.g., maybe they want their model to predict the correct outcome of rain or no rain for the next day 95% of the time). Uncertainty is also built into weather models for precipitation in other ways (e.g., a forecast of 70% chance of rain for a given day). Knowing that there is a 70% chance of rain tomorrow is better than not having any information about tomorrow\u2019s weather at all. Students who choose Delana\u2019s response (as well as all the other students) could benefit from conversations about and examples of what it means for a model to be \u201cgood enough\u201d to serve a purpose.\\n\\n###Middle Level \\n\u2022\\t**Alex\u2019s response (run the model longer)** suggests awareness that models are not perfect and that they can improve over time. This response may also appeal to some students who know about the idea of computer iteration (i.e., a process in which a set of instructions is repeated in a sequence multiple times or until a condition is met). Sometimes computer models need to run over time through multiple iterations to reach a certain set of criteria for the output. However, in this case, if the computer model is only making a correct prediction about half the time, then the computer needing more time to process the data probably isn\u2019t the problem. \\n\\nStudents who choose Alex\u2019s response could benefit from a discussion about whether or not they think running the model longer would help in this case.\\n\\n\u2022\\t**Kalin\u2019s response (keep working on rules using science)** has some merit. We do want to work on model rules based on scientific principles. However, when modeling a real-world system, it\u2019s not enough to just use the rules of science to make our models. We need to know that our model is actually going to work (i.e., be sufficiently accurate in outputs such as predictions) when it is applied in the real world. Real-world systems are complex. 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Then they tested their model to see how well it worked. They found their predictions were only right about half the time. The students had different ideas for improving the model.\u003C/p\u003E\r\n\u003Cp\u003EHere are the students\u0026rsquo; ideas:\u003C/p\u003E\r\n\u003Ctable cellpadding=\"30\"\u003E\r\n\u003Ctbody\u003E\r\n\u003Ctr\u003E\r\n\u003Cth colspan=\"2\"\u003E\u003Cstrong\u003EAlex\u003C/strong\u003E\u003C/th\u003E\r\n\u003Cth colspan=\"2\"\u003E\u003Cstrong\u003EDelana\u003C/strong\u003E\u003C/th\u003E\r\n\u003C/tr\u003E\r\n\u003Ctr\u003E\r\n\u003Ctd width=\"88\"\u003E\u003Cimg src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/Alex%206.png\" width=\"72\" height=\"90\" align=\"center\" hspace=\"10\" vspace=\"10\" /\u003E\u003C/td\u003E\r\n\u003Ctd style=\"padding: 10px;\" width=\"350\"\u003EWe need to run the model longer. The longer you run a computer model the better the prediction will be.\u003C/td\u003E\r\n\u003Ctd width=\"88\"\u003E\u003Cimg src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/Delana6.png\" width=\"70\" height=\"90\" align=\"center\" hspace=\"10\" vspace=\"10\" /\u003E\u003C/td\u003E\r\n\u003Ctd style=\"padding: 10px;\" width=\"350\"\u003EThere\u0026rsquo;s no way to make a computer model that can predict the weather. Computer models aren\u0026rsquo;t the real world, so they can\u0026rsquo;t predict what will happen in the real world.\u003C/td\u003E\r\n\u003C/tr\u003E\r\n\u003C/tbody\u003E\r\n\u003Ctbody\u003E\r\n\u003Ctr\u003E\r\n\u003Cth colspan=\"2\"\u003E\u003Cstrong\u003EKalin\u003C/strong\u003E\u003C/th\u003E\r\n\u003Cth colspan=\"2\"\u003E\u003Cstrong\u003ESage\u003C/strong\u003E\u003C/th\u003E\r\n\u003C/tr\u003E\r\n\u003Ctr\u003E\r\n\u003Ctd width=\"88\"\u003E\r\n\u003Cp\u003E\u003Cimg src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/Kalin1.png\" width=\"72\" height=\"90\" align=\"center\" hspace=\"10\" vspace=\"10\" /\u003E\u003C/p\u003E\r\n\u003C/td\u003E\r\n\u003Ctd style=\"padding: 10px;\" width=\"350\"\u003EWe should keep working on the rules based on the science of weather prediction. 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After students make an individual choice for the pre-assessment, lead a discussion including, for example, a pair/share opportunity and/or full class discussion. \\n\\nAt this time, encourage students to share and discuss their ideas and reasons without indicating that any one answer is better or worse. Let the students know that they should keep thinking about this question and that the class will return to it at the end of the lesson.\",\"content2\":\"\",\"mediaType\":\"none\",\"mediaCaption\":\"Last, First. \\\"Title of Work.\\\" Year created. Site Title [OR] Publisher. 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We suggest teachers review the information and think about ways to scaffold students toward developing knowledge and practice as appropriate for their classes. We also recommend emphasizing the underlying ideas and practices, rather than on vocabulary terms. By discussing the different options, students can engage in productive talk related to these computational thinking concepts without using technical terminology. \\n\\nThis assessment probe is designed to assess and scaffold students in thinking and talking about **Rule Refinement** and, especially, **Rule Testing**. **Rule Refinement** involves refining a rule for use in a modeling environment using scientific principles and incorporating additional data, making the rule more precise, computational, and/or detecting and correcting errors. **Rule Testing** is a process of \\\"calibration\\\" between the modeling environment and the observable world. It involves systematically testing a rule to detect errors and limitations, and analyzing the efficiency of various solutions.\\n\\nThe assessment is situated in the unit context to provide an opportunity for students to make sense about rule refinement and rule testing in a specific, tangible weather problem. While one of the responses makes the most sense from a practical standpoint for this problem, other responses have implicit connections to facets of computational thinking (e.g., using understanding of systems to determine model rules and iteration in modeling). Using an indefinite problem provides space for students to think and talk about different approaches to refining and testing rules for a computer model. 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We sometimes see this type of reasoning when students and even adults talk about climate change models. Some people say things like, \u201cthey are just models, so they don\u2019t really tell us what\u2019s going to happen in the real world.\u201d \\n\\nStudents who choose Delana\u2019s response could use support in developing understanding that computer models don\u2019t need to be perfect in order to be useful. No model is perfectly accurate. Models just need to be good enough for a given purpose. Computer modelers set calibration targets that define how close to the actual event they want their prediction to be (e.g., maybe they want their model to predict the correct outcome of rain or no rain for the next day 95% of the time). Uncertainty is also built into weather models for precipitation in other ways (e.g., a forecast of 70% chance of rain for a given day). Knowing that there is a 70% chance of rain tomorrow is better than not having any information about tomorrow\u2019s weather at all. Students who choose Delana\u2019s response (as well as all the other students) could benefit from conversations about and examples of what it means for a model to be \u201cgood enough\u201d to serve a purpose.\\n\\n###Middle Level \\n\u2022\\t**Alex\u2019s response (run the model longer)** suggests awareness that models are not perfect and that they can improve over time. This response may also appeal to some students who know about the idea of computer iteration (i.e., a process in which a set of instructions is repeated in a sequence multiple times or until a condition is met). Sometimes computer models need to run over time through multiple iterations to reach a certain set of criteria for the output. However, in this case, if the computer model is only making a correct prediction about half the time, then the computer needing more time to process the data probably isn\u2019t the problem. \\n\\nStudents who choose Alex\u2019s response could benefit from a discussion about whether or not they think running the model longer would help in this case.\\n\\n\u2022\\t**Kalin\u2019s response (keep working on rules using science)** has some merit. We do want to work on model rules based on scientific principles. However, when modeling a real-world system, it\u2019s not enough to just use the rules of science to make our models. We need to know that our model is actually going to work (i.e., be sufficiently accurate in outputs such as predictions) when it is applied in the real world. Real-world systems are complex. If we just go by the rules of science, we may be overlooking possible problems with either the rules of the model (e.g., omitting an important variable) or with input data (e.g., perhaps a temperature sensor is faulty or isn\u2019t calibrated correctly). In either case, just working on the rules of the model would not be enough to know that the model really works unless we check our weather model predictions against the weather that actually occurs.\\n\\n###More Formal Ideas\\n\u2022\\t**Sage\u2019s answer (refine and test model predictions using Alaska weather data)** is the only option that acknowledges the importance of using calibration to test model rules, which is essential for establishing confidence in a computer model that is designed to represent or simulate an event or phenomenon in the real world. Weather modelers need to compare their model outputs to real-world data to ascertain how well they are working. 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You are now ready to begin to apply all of that knowledge to the unit challenge:\u0026nbsp;What will the\u0026nbsp;weather\u0026nbsp;be in Anchorage 24 hours from now?\u003C/p\u003E\n\u003Cp\u003EUse the resources from your past lessons to help inform your prediction. Go to page 28 in your Science Notebooks to review the Lesson 1, Weather Radar Maps for the Alaskan Region, to help you.\u003C/p\u003E\n\u003Cp\u003E\u003Cimg src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/L1AKRADARMAPAPRIL21_7am.png\" width=\"303\" height=\"231\" /\u003E\u003Cimg src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/L1AKRADARMAPAPRIL21_1pm.png\" width=\"303\" height=\"231\" /\u003E\u003Cimg src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/L1AKRADARMAPAPRIL21_7pm.png\" width=\"303\" height=\"231\" /\u003E\u003Cimg src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/L1AKRADARMAPAPRIL22_1am.png\" width=\"297\" height=\"230\" /\u003E\u003Cimg src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/L1AKRADARMAPAPRIL22_7am.png\" width=\"303\" height=\"231\" /\u003E\u003C/p\u003E\n\u003Cp\u003E\u0026nbsp;\u003C/p\u003E", + "is_callout": false, + "is_full_width": true, + "is_hidden": false, + "name": "", + "type": "Embeddable::Xhtml", + "ref_id": "147917-Embeddable::Xhtml" + }, + "section": "header_block" + }, { + "embeddable": { + "plugin": { + "description": "", + "author_data": "{\"tipType\":\"windowShade\",\"questionWrapper\":{\"correctExplanation\":\"correct\",\"distractorsExplanation\":\"distractor\",\"exemplar\":\"exemplar\",\"teacherTip\":\"teacherTip\",\"teacherTipImageOverlay\":\"\"},\"windowShade\":{\"windowShadeType\":\"theoryAndBackground\",\"layout\":\"mediaLeft\",\"initialOpenState\":false,\"content\":\"###LESSON 6: MODELING FRONTS\\n**HOW DO FRONTS MOVE?**\\n\\nIn this lesson, students identify the location, direction, and rate of movement of the front. 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The understandings developed in this lesson support students in developing their predictions for the unit challenge in Lesson 7. \\n\\n**LEARNING GOALS**\\n\\nStudents will be able to:\\n\\n* Understand that air masses are constantly moving and their characteristics (temperature and moisture) change\\n\\n* Identify evidence of a front moving through a given location \\n\\n* Analyze the speed and direction of a front moving over a region from given data\",\"content2\":\"\",\"mediaType\":\"none\",\"mediaCaption\":\"Last, First. \\\"Title of Work.\\\" Year created. Site Title [OR] Publisher. 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In this activity, students use front visualizations from 11 am, 9 pm, and 7 am to see where the air masses are colliding (i.e., the front) at different times and to track the direction of the front. The specific computational thinking skills highlighted and practiced in this activity are **Decomposition**, **Pattern Recognition**, and **Model Evaluation**.\\n\\n###Activity Breakdown\\n\\n1.Play the Lesson 6 Virtual Model tutorial.\\n\\n2.Research teams use the Front Visualizations in their Science Notebooks and the Alaska Map Transparency to describe the direction the front is moving.\\n\\n3.In the student online activity, teams summarize their findings for the direction the front is moving within the region.\",\"content2\":\"\",\"mediaType\":\"none\",\"mediaCaption\":\"Last, First. \\\"Title of Work.\\\" Year created. Site Title [OR] Publisher. 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Strategy Tips \\nThe intention of this task is to provide students with a more open-ended task than seen in Lessons 1 - 4 and to give them an opportunity to apply their CT skills before solving the unit challenge. It is important that students work independently. The goal is to see if students can decompose the mini front challenge on their own. Additionally, this shift in perspective gives the students agency in their own learning to identify which CT skills are key to addressing this question. Students should realize that they know how to identify a front from Lesson 4, and have data at their disposal that can help them figure out the location of the front is at different points in time. Ideally, they will decompose \u201chow the front moves\u201d into two components: direction (which way it is heading) and speed (distance/time). Please see a list of possible discussion prompts to guide students through this process:\\n\\n\\n* Remind students that they learned how to identify a front in the last lesson, and that fronts can be an indicator of complex weather. \\n\\n* Point out that the unit challenge is to make a decision on if they are to continue, cancel, or postpone the Native Youth Olympics (NYO Games) and explain to them that figuring out where this front will be in 24 hours can help improve their prediction.\\n\\n* Raise the question: What do we need to know about the front to predict where it will be in the future? \\n\\n* Ask the research teams to:\\n\\n * Think about the question and brainstorm their ideas as a group.\\n * Identify the computational thinking skills they think will help them address this challenge. \\n\\n * Identify what features in the Virtual Model would help them answer this question. \\n * Identify what data they have from Lessons 1 - 5 that would help them answer this question.\\n* Have research teams answer the online activity questions.\",\"content2\":\"\",\"mediaType\":\"none\",\"mediaCaption\":\"Last, First. \\\"Title of Work.\\\" Year created. 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So you may be wondering when it\u0026rsquo;s going to pass through there. Where the\u0026nbsp;front\u0026nbsp;is at the time of the Alaskan Native Youth Olympics (NYO Games) will greatly affect the\u0026nbsp;weather.\u003C/p\u003E\n\u003Cp\u003ETo best predict where the\u0026nbsp;front\u0026nbsp;will be in 24 hours, you will need to figure out how fast it is moving. This is a calculation of speed (distance over time). Once you know both speed and direction (from Activity 1) of the\u0026nbsp;front, your\u0026nbsp;weather\u0026nbsp;analysis will help you answer the question \u0026ldquo;How fast is the\u0026nbsp;front\u0026nbsp;moving?\u0026rdquo;\u003C/p\u003E\n\u003Cp\u003EYou will have the following tools to help you:\u003C/p\u003E\n\u003Cp\u003E\u0026bull; Your\u0026nbsp;front images from the Virtual Model\u003Cbr /\u003E\u0026bull; A regional map transparency\u003Cbr /\u003E\u0026bull; Rulers and pens\u003C/p\u003E", + "is_callout": false, + "is_full_width": true, + "is_hidden": false, + "name": "", + "type": "Embeddable::Xhtml", + "ref_id": "147919-Embeddable::Xhtml" + }, + "section": "header_block" + }, { + "embeddable": { + "content": "\u003Cp\u003EUsing the available materials, develop a strategy for calculating the rate of the\u0026nbsp;front. Remember that speed equals distance an object moves divided by the time it takes the object to move to its new location.\u003C/p\u003E\r\n\u003Cp style=\"padding-left: 30px;\"\u003E\u003Cstrong\u003E\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Speed = Distance/Time\u003C/strong\u003E\u003C/p\u003E", + "is_callout": true, + "is_full_width": true, + "is_hidden": false, + "name": "TASK ", + "type": "Embeddable::Xhtml", + "ref_id": "147920-Embeddable::Xhtml" + }, + "section": null + }, { + "embeddable": { + "default_text": "", + "give_prediction_feedback": false, + "hint": "\u003Cp\u003E\u0026bull; Your answer should be a rate or speed.\u003C/p\u003E\r\n\u003Cp\u003E\u0026bull; Speed is a measurement of distance over time.\u003C/p\u003E\r\n\u003Cp\u003E\u0026bull; Distance can be measured in units of kilometers, miles, etc.\u003C/p\u003E\r\n\u003Cp\u003E\u0026bull; Time can be measured in hours, days, etc.\u003C/p\u003E", + "is_full_width": true, + "is_hidden": false, + "is_prediction": false, + "name": "", + "prediction_feedback": "", + "prompt": "\u003Cp\u003EHow fast is the\u0026nbsp;front\u0026nbsp;moving? Be as specific as you can.\u003C/p\u003E", + "show_in_featured_question_report": true, + "type": "Embeddable::OpenResponse", + "ref_id": "208896-Embeddable::OpenResponse" + }, + "section": null + }, { + "embeddable": { + "default_text": "", + "give_prediction_feedback": false, + "hint": "\u003Cp\u003E\u0026bull; Explain your strategy.\u003C/p\u003E\r\n\u003Cp\u003E\u0026bull; Talk about what you did to come up with your answer.\u003C/p\u003E", + "is_full_width": true, + "is_hidden": false, + "is_prediction": false, + "name": "", + "prediction_feedback": "", + "prompt": "\u003Cp\u003EDescribe how your team figured out how fast the\u0026nbsp;front\u0026nbsp;is moving.\u003C/p\u003E", + "show_in_featured_question_report": true, + "type": "Embeddable::OpenResponse", + "ref_id": "208897-Embeddable::OpenResponse" + }, + "section": null + }, { + "embeddable": { + "plugin": { + "description": "", + "author_data": "{\"tipType\":\"windowShade\",\"questionWrapper\":{\"correctExplanation\":\"correct\",\"distractorsExplanation\":\"distractor\",\"exemplar\":\"exemplar\",\"teacherTip\":\"teacherTip\",\"teacherTipImageOverlay\":\"\"},\"windowShade\":{\"windowShadeType\":\"theoryAndBackground\",\"layout\":\"mediaLeft\",\"initialOpenState\":false,\"content\":\"###Activity 2 - How Fast is the Front Moving?\\n\\nThe focus of this activity is for students to analyze the visualization data they generated in Activity 1 and to develop a statement defining the speed of the front moving across the region. The activity ends with research teams developing a description of how fast the front is moving and recording it in the student online activity. The specific computational thinking practice highlighted and practiced in this activity is **Pattern Recognition**.\\n\\n\u003Cbr\u003E**1. Calculate the speed the front is moving.**\\n\\n* Pass out to the research teams their Science Notebooks with the front visualizations, Regional Map Transparency, wet erase markers, paper towels, and rulers. \\n\\n* Students may also want to use the [L1A2: Alaska Weather Station Data Sheet](https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/L1A2_WeatherStationDataAK.png) and the [L4A1: Alaska Additional Weather Stations handouts](https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/L4A1_AdditionalWeatherStationsDataSheet_AK.png). \\n\\n* The primary challenge for students will be deciding where on the front to use as a reference point when measuring the distance that it moves from timestamp to timestamp. 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This event has been planned for months and the committee is expecting over 500 people to attend. One of your jobs on this committee is to watch the\u0026nbsp;weather\u0026nbsp;and determine if the event is safe to proceed as\u0026nbsp;planned, or if it should be\u0026nbsp;postponed\u0026nbsp;or\u0026nbsp;even canceled.\u003C/p\u003E\n\u003Cp\u003EIt\u0026rsquo;s time to put your computational thinking skills to work!\u003C/p\u003E", + "is_callout": false, + "is_full_width": true, + "is_hidden": false, + "name": "", + "type": "Embeddable::Xhtml", + "ref_id": "147923-Embeddable::Xhtml" + }, + "section": "header_block" + }, { + "embeddable": { + "plugin": { + "description": "", + "author_data": "{\"tipType\":\"windowShade\",\"questionWrapper\":{\"correctExplanation\":\"correct\",\"distractorsExplanation\":\"distractor\",\"exemplar\":\"exemplar\",\"teacherTip\":\"teacherTip\",\"teacherTipImageOverlay\":\"\"},\"windowShade\":{\"windowShadeType\":\"theoryAndBackground\",\"layout\":\"mediaLeft\",\"initialOpenState\":false,\"content\":\"###LESSON 7: ANALYZING DATA AND MAKING A PREDICTION\\n\\n**What will the local weather be 24 hours from now?**\\n\\nIn this lesson, students revisit the unit challenge and the original question posted to them in Lesson 1, \\\"Should the NYO Games proceed as planned, be postponed or canceled?\\\" Students assume the role of weather forecasters and make a weather prediction for Anchorage on April 23 at 7 am using regional data and models they have been exploring throughout this unit. 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Although we have not named the skill until now, notice in the table below the skills you have used to help decide if the NYO Games should proceed.\u003C/p\u003E\r\n\u003Ctable cellpadding=\"30\"\u003E\r\n\u003Ctbody\u003E\r\n\u003Ctr bgcolor=\"#D3D3D3\"\u003E\r\n\u003Cth style=\"border: 1px solid black;\" colspan=\"1\"\u003E\u003Cstrong\u003EDefinition\u003C/strong\u003E\u003C/th\u003E\r\n\u003Cth style=\"border: 1px solid black;\" colspan=\"1\"\u003E\u0026nbsp;\u003C/th\u003E\r\n\u003Cth style=\"border: 1px solid black;\" colspan=\"1\"\u003E\u003Cstrong\u003EComputational Thinking Skill\u003C/strong\u003E\u003C/th\u003E\r\n\u003C/tr\u003E\r\n\u003Ctr\u003E\r\n\u003Ctd style=\"border: 1px solid black; padding: 20px;\" width=\"300\"\u003E\r\n\u003Cp style=\"text-align: left;\"\u003EOrganizing a large amount of information (data) into smaller more manageable parts.\u003C/p\u003E\r\n\u003C/td\u003E\r\n\u003Ctd style=\"border: 1px solid black; text-align: center;\" width=\"250\"\u003E\u003Cimg src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/Glossary/ct-decomposition.jpg\" width=\"235\" height=\"132\" /\u003E\u003C/td\u003E\r\n\u003Ctd style=\"border: 1px solid black; text-align: center; padding: 20px;\" width=\"300\"\u003E\r\n\u003Cp\u003E\u003Cstrong\u003EDecomposition\u003C/strong\u003E\u003C/p\u003E\r\n\u003Cp\u003EIn \u003Cstrong\u003ELesson 1, \u003C/strong\u003Eyou organized weather station data over a two-day period and radar maps of Alaska every 6 hours to make a prediction.\u003C/p\u003E\r\n\u003C/td\u003E\r\n\u003C/tr\u003E\r\n\u003Ctr style=\"border: 1px solid black; text-align: center;\"\u003E\r\n\u003Ctd style=\"border: 1px solid black; padding: 20px;\" width=\"300\"\u003E\r\n\u003Cp style=\"text-align: left;\"\u003ERecognizing that data or information is repeating in a logical (expected) way.\u003C/p\u003E\r\n\u003C/td\u003E\r\n\u003Ctd style=\"border: 1px solid black;\" width=\"250\"\u003E\u003Cimg src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/Captioned_Videos/new_picts/Lesson_5_new_Embedded_assessment/Netlogo_temp_model.png\" width=\"159\" height=\"181\" /\u003E\u003C/td\u003E\r\n\u003Ctd style=\"border: 1px solid black; padding: 20px;\" width=\"300\"\u003E\r\n\u003Cp style=\"text-align: center;\"\u003E\u003Cstrong\u003EPattern Recognition\u003C/strong\u003E\u003C/p\u003E\r\n\u003Cp\u003EIn \u003Cstrong\u003ELesson 2\u003C/strong\u003E, you ran the model to see temperature data and patterns of data moving across the map. Before and after each run of the model, you interpolated data. You discovered that warm and cold spots on the map are at times on certain sides, and also you saw these spots change location over time.\u003C/p\u003E\r\n\u003Cp\u003EIn\u003Cstrong\u003E Lesson 3 and 4\u003C/strong\u003E, you ran the models to develop a general statement to answer the question \"Where does it rain?\".\u003C/p\u003E\r\n\u003C/td\u003E\r\n\u003C/tr\u003E\r\n\u003Ctr style=\"border: 1px solid black; text-align: center;\"\u003E\r\n\u003Ctd style=\"border: 1px solid black; padding: 20px;\" width=\"300\"\u003E\r\n\u003Cp style=\"text-align: left;\"\u003EEstimating an unknown value based on surrounding information.\u003C/p\u003E\r\n\u003C/td\u003E\r\n\u003Ctd style=\"border: 1px solid black;\" width=\"250\"\u003E\u003Cimg class=\"\" src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/Glossary/interpolation.jpg\" alt=\"\" width=\"206\" height=\"117\" /\u003E\u003C/td\u003E\r\n\u003Ctd style=\"border: 1px solid black; padding: 20px;\" width=\"300\"\u003E\r\n\u003Cp style=\"text-align: center;\"\u003E\u003Cstrong\u003EInterpolation\u003C/strong\u003E\u003C/p\u003E\r\n\u003Cp style=\"text-align: center;\"\u003EIn \u003Cstrong\u003ELesson 2\u003C/strong\u003E, you made best guess estimates of the temperatures that were missing on the map.\u003C/p\u003E\r\n\u003C/td\u003E\r\n\u003C/tr\u003E\r\n\u003Ctr style=\"border: 1px solid black; text-align: center;\"\u003E\r\n\u003Ctd style=\"border: 1px solid black; padding: 20px;\" width=\"300\"\u003E\r\n\u003Cp style=\"text-align: left;\"\u003EFollowing a pattern beyond the known data points.\u003C/p\u003E\r\n\u003C/td\u003E\r\n\u003Ctd style=\"border: 1px solid black;\" width=\"250\"\u003E\u003Cimg src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/Glossary/exptrapolation.jpg\" width=\"205\" height=\"116\" /\u003E\u003C/td\u003E\r\n\u003Ctd style=\"border: 1px solid black; padding: 20px;\" width=\"300\"\u003E\r\n\u003Cp style=\"text-align: center;\"\u003E\u003Cstrong\u003EExtrapolation\u003C/strong\u003E\u003C/p\u003E\r\n\u003Cp style=\"text-align: center;\"\u003EIn \u003Cstrong\u003ELesson 2\u003C/strong\u003E, you predicted future weather based on patterns you observed in the changing temperatures you collected and visualized.\u003C/p\u003E\r\n\u003C/td\u003E\r\n\u003C/tr\u003E\r\n\u003Ctr style=\"border: 1px solid black; text-align: center;\"\u003E\r\n\u003Ctd style=\"border: 1px solid black; 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Watch Mr. Neyhard tell you more about the unit challenge.
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\r\n\"What am I going to wear today?\" is a question everyone asks each morning. How do you determine what you are going to wear? What information do you collect to inform your decision?
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\r\nThe data from the weather stations are organized to show information for a 24-hour time period.
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\r\nMs. Tevuk’s class is studying weather. The students will make a computer model to predict weather in Alaska.
\r\nFour students in Ms. Tevuk’s class are figuring out how to estimate the temperature of a location. The students are looking at the map below and have different ideas for estimating the temperature at the location marked X using the recorded temperatures of 31˚ and 59˚.
\r\n![\"\"](\"https://project-resources.concord.org/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/L2AssessmentQ.png\")
Here are the students’ ideas:
\r\n| Alex | \r\nDelana | \r\n||
|---|---|---|---|
![](\"https://project-resources.concord.org/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/Alex1.png\") | \r\nWe should use the number that is exactly halfway in between 31˚and 59˚. That’s the most exact way to estimate. | \r\n![](\"https://project-resources.concord.org/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/Delana1.png\") | \r\nWe should mark a number line along the map with the estimate in each square going up the same amount between 31˚ and 59˚. That’d be the best estimate. | \r\n
| Kalin | \r\nSage | \r\n||
| \r\n
| \r\nIt doesn’t make sense to estimate the temperature at the X. We’d need to go there and measure the temperature. You can’t be confident unless you measure it. | \r\n\r\n
| \r\nThe X is closer to the 59˚ than to the 31˚, so let’s choose a number closer to 59˚. That’s the best we can do because we don’t know what’s happening with the weather in those places. | \r\n
![](\"https://project-resources.concord.org/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/Kalin.png\")
![](\"https://project-resources.concord.org/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/Sage1.png\")
Which student’s idea do you agree with the most?
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\r\nMs. Tevuk’s class is studying weather. The students will make a computer model to predict weather in Alaska.
\r\nFour students in Ms. Tevuk’s class are figuring out how to estimate the temperature of a location. The students are looking at the map below and have different ideas for estimating the temperature at the location marked X using the recorded temperatures of 31˚ and 59˚.
\r\n
Here are the students’ ideas:
\r\n| Alex | \r\nDelana | \r\n||
|---|---|---|---|
| \r\nWe should use the number that is exactly halfway in between 31˚and 59˚. That’s the most exact way to estimate. | \r\n | \r\nWe should mark a number line along the map with the estimate in each square going up the same amount between 31˚ and 59˚. That’d be the best estimate. | \r\n
| Kalin | \r\nSage | \r\n||
| \r\n
| \r\nIt doesn’t make sense to estimate the temperature at the X. We’d need to go there and measure the temperature. You can’t be confident unless you measure it. | \r\n\r\n
| \r\nThe X is closer to the 59˚ than to the 31˚, so let’s choose a number closer to 59˚. That’s the best we can do because we don’t know what’s happening with the weather in those places. | \r\n
Which student’s idea do you agree with the most?
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\r\nThere are many different methods to interpolate data. Let’s look at the three interpolation methods used to make these maps.
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For Square A, you may have guessed 54°F degrees or something very close to that. This is the simplest interpolation method. It is called Nearest Neighbor. With this method, you find the nearest weather station to the unknown point and assume it has a similar temperature.
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If two weather scientists were using the same data but different interpolation methods, could they get different results?
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For Square B, you may have guessed between 38°F and 50°F, but closer to 50°F. Since this square is between two known temperatures, the unknown temperature is probably between 38°F and 50°F. To be even closer, you can think of it like a number line with temperature in each square increasing by four degrees.
\r\n![\"Number](\"https://project-resources.concord.org/precipitatingchange/images/linearinterpolation.jpg\")
This method is called Linear Interpolation.
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\r\n![\"\"](\"https://project-resources.concord.org/precipitatingchange/images/AKweightedneigborinterpolation.jpg\")
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If two weather scientists were using the same data but different interpolation methods, could they get different results??
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\r\n![](\"https://project-resources.concord.org/precipitatingchange/images/AK-3-maps-interpolation.png\")
Which interpolation method does Map 1 use?
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\r\nBelow you will see three maps of temperature data each one at a different time during one day. Study the changes of temperature over time looking for patterns in the data.
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\r\n- \r\n
- Use the slider to see temperatures from 7am to 3pm. \r\n
- Look for patterns of temperature changes over time. \r\n
- To see patterns, it may help to turn on and off the temperature data or the color key. \r\n
Remember: always start by clicking Setup and then Run.
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\r\nMs. Tevuk’s class is looking at a temperature map with five data points taken from weather station observations. All five weather station observations were made at the same time on the same day. The map also shows some temperatures that were estimated using the weather station observation data (estimated temperatures are in parentheses).
\r\n![](\"https://project-resources.concord.org/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/L3AssessmentProbeMap.png\")
Ms. Tevuk asks the students which of the estimated temperatures they are LEAST CERTAIN (MOST UNSURE) about.
\r\nHere are the students’ ideas. (Each student’s estimated temperature choice is in bold to make it easier to find.)
\r\n| Alex | \r\nDelana | \r\n||
|---|---|---|---|
![](\"https://project-resources.concord.org/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/Alex1-1.png\") | \r\n\r\n I’m least certain about the estimate of 53˚ because it’s furthest outside of the temperatures that were actually measured at a weather station. \r\n
| \r\n![](\"https://project-resources.concord.org/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/Delana2.png\") | \r\n\r\n I’m least certain about the estimate of 43˚ because it’s far away from any temperatures measured at a weather station. \r\n
| \r\n
| Kalin | \r\nSage | \r\n||
| \r\n
| \r\n\r\n I’m least certain about the estimate of 39˚ because there aren’t any other estimated temperatures near the 39˚ estimate. \r\n
| \r\n\r\n
| \r\n\r\n I’m least certain about the estimate of 37˚ because weather usually moves from west to east, so I’m unsure about estimates on the west side of the map. \r\n
| \r\n
![](\"https://project-resources.concord.org/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/Lesson3AlexsChoice.png\")
![](\"https://project-resources.concord.org/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/Lesson3DelanasChoice.png\")
![](\"https://project-resources.concord.org/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/Kalin3.png\")
![](\"https://project-resources.concord.org/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/Lesson3KalinsChoice.png\")
![](\"https://project-resources.concord.org/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/Lesson3SageAvatar.png\"){kind=avatar}
![\"\"](\"https://project-resources.concord.org/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/Lesson3SagesChoice.png\")
Why do you think the estimated temperature you picked is the one we should be least certain (most unsure) about? Please explain your reasoning.
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\r\nMs. Tevuk’s class is looking at a temperature map with five data points taken from weather station observations. All five weather station observations were made at the same time on the same day. The map also shows some temperatures that were estimated using the weather station observation data (estimated temperatures are in parentheses).
\r\n
Ms. Tevuk asks the students which of the estimated temperatures they are LEAST CERTAIN (MOST UNSURE) about.
\r\nHere are the students’ ideas. (Each student’s estimated temperature choice is in bold to make it easier to find.)
\r\n| Alex | \r\nDelana | \r\n||
|---|---|---|---|
| \r\n\r\n I’m least certain about the estimate of 53˚ because it’s furthest outside of the temperatures that were actually measured at a weather station. \r\n
| \r\n | \r\n\r\n I’m least certain about the estimate of 43˚ because it’s far away from any temperatures measured at a weather station. \r\n
| \r\n
| Kalin | \r\nSage | \r\n||
| \r\n
| \r\n\r\n I’m least certain about the estimate of 39˚ because there aren’t any other estimated temperatures near the 39˚ estimate. \r\n
| \r\n\r\n
| \r\n\r\n I’m least certain about the estimate of 37˚ because weather usually moves from west to east, so I’m unsure about estimates on the west side of the map. \r\n
| \r\n
Why do you think the estimated temperature you picked is the one we should be least certain (most unsure) about? Please explain your reasoning.
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\r\n\r\n
Precipitation symbol = raindrops ![\"\"](\"https://project-resources.concord.org/precipitatingchange/images/3-drop-black-staggered.png\")
\r\n
![\"\"](\"https://project-resources.concord.org/precipitatingchange/2019_20_Curriculum_%20Documents/Air%20Moisture.jpg\")
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Would you change what you selected to wear? Yes or No
\nIf yes, what would you change and why?
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\r\nPrecipitation is shown with three raindrops:
The air moisture and temperature data are shown this way:![\"\"](\"https://project-resources.concord.org/precipitatingchange/images-2021/Temp-Moisture-Key.png\")
Set the map to show the data at 3 pm. Check all cells listed below that have precipitation.
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• What was your strategy that helped you develop your prediction?
The weather map of the virtual storm below shows temperature and air moisture data at 7pm. Use the relationships you just figured out between air moisture, temperature, and precipitation to try and predict where it will rain at 7pm.
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", + "editor_mode": 0, + "layout": 0, + "name": "Alaska 2021 - Lesson 4: Post-thoughts - What Do You Think?", + "notes": "", + "project_id": 25, + "related": "", + "runtime": "Activity Player", + "show_submit_button": true, + "student_report_enabled": true, + "thumbnail_url": "https://learn-resources.concord.org/images/stem-resources/icons/pc-lesson3.png", + "time_to_complete": null, + "version": 1, + "theme_name": "Precipitating Change", + "pages": [ + { + "additional_sections": {}, + "embeddable_display_mode": "stacked", + "id": 143598, + "is_completion": false, + "is_hidden": false, + "layout": "l-full-width", + "name": "Page 1", + "position": 1, + "show_header": true, + "show_info_assessment": true, + "show_interactive": false, + "show_sidebar": false, + "sidebar": null, + "sidebar_title": "Did you know?", + "toggle_info_assessment": false, + "embeddables": [ + { + "embeddable": { + "content": "What Are the Rules for Fronts and Precipitation?
\r\nMs. Tevuk’s students need to write a rule for their computer model to predict areas of precipitation on a map showing weather fronts. They have different ideas for what the rule should be.
\r\nHere are the students’ ideas: The rule should be that precipitation happens…
\r\n| Alex | \r\nDelana | \r\n||
|---|---|---|---|
![](\"https://project-resources.concord.org/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/Alex4.png\") | \r\nwith a warm front coming in because warm air moves in and mixes with cold air, which leads to precipitation. You don’t get precipitation with a cold front because cold air is dry. | \r\n![](\"https://project-resources.concord.org/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/Delana4.png\") | \r\nwith both cold fronts and warm fronts coming in because in both cases warm air and cold air meet, leading to condensation and precipitation. | \r\n
| Kalin | \r\nSage | \r\n||
| \r\n
| \r\nwith a cold front coming in because it’s usually rainy or snowy when it’s cold out. You don’t get precipitation with a warm front because it’s warm when the sun is shining. | \r\n\r\n
| \r\nafter a cold front has passed by because the cold air the front leaves behind is humid, which leads to precipitation. | \r\n
![](\"https://project-resources.concord.org/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/Kalin6.png\")
![](\"https://project-resources.concord.org/precipitatingchange/Sage2.png\")
Why do you think the rule you picked is the best one for predicting precipitation? Please explain your reasoning.
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", + "editor_mode": 0, + "layout": 0, + "name": "Alaska 2021 - Lesson 4: Pre-thoughts - What Do You Think?", + "notes": "", + "project_id": 25, + "related": "", + "runtime": "Activity Player", + "show_submit_button": true, + "student_report_enabled": true, + "thumbnail_url": "https://learn-resources.concord.org/images/stem-resources/icons/pc-lesson3.png", + "time_to_complete": null, + "version": 1, + "theme_name": "Precipitating Change", + "pages": [ + { + "additional_sections": {}, + "embeddable_display_mode": "stacked", + "id": 143597, + "is_completion": false, + "is_hidden": false, + "layout": "l-full-width", + "name": "Page 1", + "position": 1, + "show_header": true, + "show_info_assessment": true, + "show_interactive": false, + "show_sidebar": false, + "sidebar": null, + "sidebar_title": "Did you know?", + "toggle_info_assessment": false, + "embeddables": [ + { + "embeddable": { + "content": "What Are the Rules for Fronts and Precipitation?
\r\nMs. Tevuk’s students need to write a rule for their computer model to predict areas of precipitation on a map showing weather fronts. They have different ideas for what the rule should be.
\r\nHere are the students’ ideas: The rule should be that precipitation happens…
\r\n| Alex | \r\nDelana | \r\n||
|---|---|---|---|
| \r\nwith a warm front coming in because warm air moves in and mixes with cold air, which leads to precipitation. You don’t get precipitation with a cold front because cold air is dry. | \r\n | \r\nwith both cold fronts and warm fronts coming in because in both cases warm air and cold air meet, leading to condensation and precipitation. | \r\n
| Kalin | \r\nSage | \r\n||
| \r\n
| \r\nwith a cold front coming in because it’s usually rainy or snowy when it’s cold out. You don’t get precipitation with a warm front because it’s warm when the sun is shining. | \r\n\r\n
| \r\nafter a cold front has passed by because the cold air the front leaves behind is humid, which leads to precipitation. | \r\n
Why do you think the rule you picked is the best one for predicting precipitation? Please explain your reasoning.
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\nExample: This rule has two parts that must happen to have a certain result. If it was a [ very nice summer ] and if it is [ August ], then there will be [ lots of berries to pick ].
\n![\"\"](\"https://project-resources.concord.org/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/RuleStatement.jpg\")
Think about developing a similar statement that could be used to determine where it will rain.
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\nTo make computational models, we need to create rules that are very specific for a computer to run. In this activity, you are going to refine the rule statement you made by testing it within a Virtual Model.
\nYou can practice making more specific rule statements by answering the questions below and testing them using the model.
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\r\n![\"\"](\"https://project-resources.concord.org/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/Lesson4NWImage.png\")
IF the upper square (the northwest square) is colder than the lower square by [ 5 or more degrees ] AND IF the moisture of the lower square is [ 7 or more ] THEN it rains in the lower square.
\r\n
Which square will have rain according to this rule?
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\r\nTry your rule with all of the data sets.
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\r\nThe word represent means to let one thing stand for another. For example, some people use the symbol of a
\r\nheart [![](\"https://project-resources.concord.org/precipitatingchange/Captioned_Videos/new_picts/heart2.png\")
] to represent (or stand for) love.
Four students in Ms. Tevuk’s class are figuring out how to represent wind direction both (1) in their computer model that does calculations to predict the weather and (2) on a map the computer model produces to show the weather prediction. The students have different ideas about how to represent wind direction for these two purposes.
\r\nHere are some different options Ms. Tevuk’s students are considering for representing wind direction.
\r\n• Wind direction represented with degree number (between 0 and 360) based on the compass
\r\n![](\"https://project-resources.concord.org/precipitatingchange/Captioned_Videos/new_picts/Lesson_5_new_Embedded_assessment/Version2_wind_direction_with_degrees.png\")
• Wind direction represented with letters based on the compass
\r\n![](\"https://project-resources.concord.org/precipitatingchange/Captioned_Videos/new_picts/Lesson_5_new_Embedded_assessment/Version2_wind_direction_with_letters.png\")
• Wind direction represented with arrows
\r\n![\"\"](\"https://project-resources.concord.org/precipitatingchange/Captioned_Videos/new_picts/Lesson_5_new_Embedded_assessment/Wind_direction_based_arrows.png\")
• Wind direction represented with different colors
\r\n![\"\"](\"https://project-resources.concord.org/precipitatingchange/Captioned_Videos/new_picts/Lesson_5_new_Embedded_assessment/Wind_direction_different_colors.png\")
Here are the students’ ideas:
\r\n| Alex | \r\nDelana | \r\n||
|---|---|---|---|
| \r\n\r\n I think we should use the letters for the computer model because there are only 8 options, so the computer will have simple information to calculate with and it won’t get stuck computing. We can use the arrows on the map because that way you can see which way the wind is going. \r\n
| \r\n | \r\n\r\n Let’s use number of degrees on the computer model because computers do calculations with numbers. I think we should use arrows on the map because they make the pattern of wind direction easy to see. \r\n
| \r\n
| Kalin | \r\nSage | \r\n||
| \r\n
| \r\n\r\n I think we should use number of degrees for both the computer model and the map because computers do calculations with numbers and our map should show what the computer calculated. \r\n
| \r\n\r\n
| \r\n\r\n I think we should use colors for both the computer model and the map. Colors are good for the map because it’s easy to see patterns in different colors. Then it helps to have your computer model and map match, so it makes sense to use colors for the computer model too. \r\n
| \r\n
![](\"https://project-resources.concord.org/precipitatingchange/Captioned_Videos/new_picts/Lesson_5_new_Embedded_assessment/Version2_letters_for_computer_model_Alex.png\")
![\"\"](\"https://project-resources.concord.org/precipitatingchange/Captioned_Videos/new_picts/Lesson_5_new_Embedded_assessment/Parts/Alex_Part2.png\")
![](\"https://project-resources.concord.org/precipitatingchange/Captioned_Videos/new_picts/Lesson_5_new_Embedded_assessment/Version2_compass_degrees_for_computer_model_Delana.png\")
![\"\"](\"https://project-resources.concord.org/precipitatingchange/Captioned_Videos/new_picts/Lesson_5_new_Embedded_assessment/Parts/Delana_Part2.png\")
![](\"https://project-resources.concord.org/precipitatingchange/Captioned_Videos/new_picts/Lesson_5_new_Embedded_assessment/Version2_compass_degrees_for_computer_model_Kalin.png\")
![](\"https://project-resources.concord.org/precipitatingchange/Captioned_Videos/new_picts/Lesson_5_new_Embedded_assessment/Version2_compass_degree_numbers_for_map_Kalin.png\")
![\"\"](\"https://project-resources.concord.org/precipitatingchange/Captioned_Videos/new_picts/Lesson_5_new_Embedded_assessment/Parts/Sage_Part1.png\")
![\"\"](\"https://project-resources.concord.org/precipitatingchange/Captioned_Videos/new_picts/Lesson_5_new_Embedded_assessment/Parts/Sage_Part2.png\")
Which student’s idea do you agree with the most?
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\r\nThe word represent means to let one thing stand for another. For example, some people use the symbol of a
\r\nheart [] to represent (or stand for) love.
Four students in Ms. Tevuk’s class are figuring out how to represent wind direction both (1) in their computer model that does calculations to predict the weather and (2) on a map the computer model produces to show the weather prediction. The students have different ideas about how to represent wind direction for these two purposes.
\r\nHere are some different options Ms. Tevuk’s students are considering for representing wind direction.
\r\n• Wind direction represented with degree number (between 0 and 360) based on the compass
\r\n
• Wind direction represented with letters based on the compass
\r\n
• Wind direction represented with arrows
\r\n
• Wind direction represented with different colors
\r\n
Here are the students’ ideas:
\r\n| Alex | \r\nDelana | \r\n||
|---|---|---|---|
| \r\n\r\n I think we should use the letters for the computer model because there are only 8 options, so the computer will have simple information to calculate with and it won’t get stuck computing. We can use the arrows on the map because that way you can see which way the wind is going. \r\n
| \r\n | \r\n\r\n Let’s use number of degrees on the computer model because computers do calculations with numbers. I think we should use arrows on the map because they make the pattern of wind direction easy to see. \r\n
| \r\n
| Kalin | \r\nSage | \r\n||
| \r\n
| \r\n\r\n I think we should use number of degrees for both the computer model and the map because computers do calculations with numbers and our map should show what the computer calculated. \r\n
| \r\n\r\n
| \r\n\r\n I think we should use colors for both the computer model and the map. Colors are good for the map because it’s easy to see patterns in different colors. Then it helps to have your computer model and map match, so it makes sense to use colors for the computer model too. \r\n
| \r\n
Which student’s idea do you agree with the most?
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\r\n
In this lesson you will explore how air masses interact by watching a wind table. You will also revisit weather station data and radar maps you used in Lesson 1 with some additions: wind data and five more weather stations.
In this activity, you will see how wind blowing from two directions interacts on a Wind Table. Please watch the video below for a demonstration on how a Wind Table maps the movement of air on a gird representing a region of Alaska.
\r\nWind Table
\r\n![](\"https://project-resources.concord.org/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/WindTunnels.png\")
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Wind direction is often measured with a weather vane or an air sock. When the wind blows, the weather vane rotates and lines up with the path that the air is flowing. So, wind direction is determined by what direction the wind is coming from. It is measured in degrees (°).
\r\n![\"\"](\"https://project-resources.concord.org/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/WindCompass.jpg\")
The arrows on the model below represent the wind direction at each location. Your challenge using this model is to identify the two air masses and mark a line of cells that splits the map into two parts: one section with the wind coming from the same direction and the other section with the wind coming from a different direction.
\r\nRemember to click Startup and Run. Then,
\r\n- \r\n
- Use gray color to mark where the front is located \r\n
- Use blue to mark air mass 1 \r\n
- Use red color to mark air mass 2 \r\n
You can check your work at any time.
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\r\nAn air mass is a body of air with similar temperature and air moisture content.
\r\nIdentifying air masses and their properties is an important part of the work of atmospheric scientists. On the map you may have noticed a temperature number at the top of the square and an air moisture content number at the bottom of the square.
\r\n![](\"https://project-resources.concord.org/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/TempMoisture.jpg\")
Develop a way to identify the two air masses using temperature and air moisture content values provided on the map you just colored.
\r\n![\"Air](\"https://project-resources.concord.org/precipitatingchange/images-2021/AirMassMap-Colored.png\")
Temperature: Compare Air Mass #1 to Air Mass #2.
\\nAir Mass 1 is:
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\\n\\rAir Mass #2 over land is:
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Air Mass #1 is:
Air moisture: Compare Air Mass #2 to Air Mass #1.
\\nAir Mass #2 is:
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", + "is_callout": true, + "is_full_width": true, + "is_hidden": false, + "name": "Activity at the Fronts", + "type": "Embeddable::Xhtml", + "ref_id": "147910-Embeddable::Xhtml" + }, + "section": "header_block" + }, + { + "embeddable": { + "content": "Compare the 7 pm interpolated map and the 7 pm radar map.
\r\n![\"\"](\"https://project-resources.concord.org/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/Lesson5_7pmInterpolatedRADARMAPcomparison.jpg\")
Comparing these maps think about how air masses affect where it rains.
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How does a front affect where it rains?
\",\"enableCheckAnswer\":true}", + "is_hidden": false, + "is_full_width": true, + "show_in_featured_question_report": true, + "inherit_aspect_ratio_method": true, + "custom_aspect_ratio_method": "DEFAULT", + "inherit_native_width": true, + "custom_native_width": 576, + "inherit_native_height": true, + "custom_native_height": 435, + "inherit_click_to_play": true, + "custom_click_to_play": false, + "inherit_full_window": true, + "custom_full_window": false, + "inherit_click_to_play_prompt": true, + "custom_click_to_play_prompt": null, + "inherit_image_url": true, + "custom_image_url": null, + "library_interactive": { + "hash": "98f3d10aa7f2fce6bdeb0ecda339fa56dc80b37c", + "data": { + "aspect_ratio_method": "DEFAULT", + "authoring_guidance": "", + "base_url": "https://models-resources.concord.org/question-interactives/version/v1.2.0-pre.1/multiple-choice/", + "click_to_play": false, + "click_to_play_prompt": null, + "description": "", + "enable_learner_state": true, + "full_window": false, + "has_report_url": false, + "image_url": null, + "name": "Multiple Choice", + "native_height": 435, + "native_width": 576, + "no_snapshots": false, + "show_delete_data_button": false, + "thumbnail_url": "", + "customizable": true, + "authorable": true + } + }, + "type": "ManagedInteractive", + "ref_id": "2257-ManagedInteractive", + "linked_interactives": [] + }, + "section": null + }, + { + "embeddable": { + "content": "The weather map below shows wind direction, temperature, and air moisture, but not precipitation. Look at this data and think about where raining would most likely occur.
\r\n![](\"https://project-resources.concord.org/precipitatingchange/images-2021/Alaska%20Weather%20Stations_7am%20Interpolated-w-coordinates.png\")
Alaska Stations: Interpolated at 7 am
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\r\n![](\"https://project-resources.concord.org/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/L1AKRADARMAPAPRIL22_7am.png\")
Radar Image for 7 am
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", + "is_callout": false, + "is_full_width": true, + "is_hidden": false, + "name": "", + "type": "Embeddable::Xhtml", + "ref_id": "147914-Embeddable::Xhtml" + }, + "section": "header_block" + }, + { + "embeddable": { + "content": "This model shows wind as moving arrowheads and precipitation as green circles. There are two air masses. Identify where the front is.
\r\nThen, by trying different settings of the temperature and moisture, see if you can make up a rule for what conditions produce precipitation along the front, and on which side of the front the precipitation will occur.
\r\nStart by pressing Setup and Run. As you change temperatures and moisture settings you may want to press Setup occasionally to start fresh. Be sure to discuss what you find with your research team.
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\r\nMs. Tevuk’s students wrote rules for their computer model to predict weather in Alaska. Then they tested their model to see how well it worked. They found their predictions were only right about half the time. The students had different ideas for improving the model.
\r\nHere are the students’ ideas:
\r\n| Alex | \r\nDelana | \r\n||
|---|---|---|---|
![](\"https://project-resources.concord.org/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/Alex%206.png\") | \r\nWe need to run the model longer. The longer you run a computer model the better the prediction will be. | \r\n![](\"https://project-resources.concord.org/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/Delana6.png\") | \r\nThere’s no way to make a computer model that can predict the weather. Computer models aren’t the real world, so they can’t predict what will happen in the real world. | \r\n
| Kalin | \r\nSage | \r\n||
| \r\n
| \r\nWe should keep working on the rules based on the science of weather prediction. If we get the science right, the model will be accurate. | \r\n\r\n
| \r\nWe should keep working on the rules and testing the model predictions using Alaska weather data. That way we’ll know the model works. | \r\n
![](\"https://project-resources.concord.org/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/Kalin1.png\")
![](\"https://project-resources.concord.org/precipitatingchange/Sage4.png\")
Why do you think the choice you picked is the best idea for improving the model? Please explain your reasoning.
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", + "editor_mode": 0, + "layout": 0, + "name": "Alaska 2021 - Lesson 6: Pre-thoughts - What Do You Think?", + "notes": "", + "project_id": null, + "related": "", + "runtime": "Activity Player", + "show_submit_button": true, + "student_report_enabled": true, + "thumbnail_url": "https://learn-resources.concord.org/images/stem-resources/icons/pc-lesson5.jpg?v2", + "time_to_complete": null, + "version": 1, + "theme_name": "Precipitating Change", + "pages": [ + { + "additional_sections": {}, + "embeddable_display_mode": "stacked", + "id": 143610, + "is_completion": false, + "is_hidden": false, + "layout": "l-full-width", + "name": "Page 1", + "position": 1, + "show_header": true, + "show_info_assessment": true, + "show_interactive": false, + "show_sidebar": false, + "sidebar": null, + "sidebar_title": "Did you know?", + "toggle_info_assessment": false, + "embeddables": [ + { + "embeddable": { + "content": "How Do We Make An Accurate Model to Predict Weather?
\r\nMs. Tevuk’s students wrote rules for their computer model to predict weather in Alaska. Then they tested their model to see how well it worked. They found their predictions were only right about half the time. The students had different ideas for improving the model.
\r\nHere are the students’ ideas:
\r\n| Alex | \r\nDelana | \r\n||
|---|---|---|---|
| \r\nWe need to run the model longer. The longer you run a computer model the better the prediction will be. | \r\n | \r\nThere’s no way to make a computer model that can predict the weather. Computer models aren’t the real world, so they can’t predict what will happen in the real world. | \r\n
| Kalin | \r\nSage | \r\n||
| \r\n
| \r\nWe should keep working on the rules based on the science of weather prediction. If we get the science right, the model will be accurate. | \r\n\r\n
| \r\nWe should keep working on the rules and testing the model predictions using Alaska weather data. That way we’ll know the model works. | \r\n
Why do you think the choice you picked is the best idea for improving the model? Please explain your reasoning.
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\r\nThroughout this unit you have been exploring different aspects of regional weather data. There is one more piece of information we need to figure out before you can make your final prediction for the unit challenge:
\r\nWhat will the weather be in Anchorage 24 hours from now?
\r\n![](\"https://project-resources.concord.org/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/L1AKRADARMAPAPRIL21_7am.png\")
![](\"https://project-resources.concord.org/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/L1AKRADARMAPAPRIL21_1pm.png\")
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Press Setup and Run on the model below. Watch as the arrows trace their path for 11am. Then do the same for 9pm and 7am. Take note of any differences you see between the times.
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\r\nTo best predict where the front will be in 24 hours, you will need to figure out how fast it is moving. This is a calculation of speed (distance divided by time). Once you know both speed and direction of the front, your weather analysis will help you answer the question, “Will it be raining in Anchorage?”
\r\nThe model below allows you to mark the fronts at three times and measure the distance between them. With the time and distance data you can calculate the approximate speed of the front and then calculate where it will be 24 hours after the last measurement. To do this you can use the tools built into this model.
\r\nFirst, mark the fronts.
\r\n• Click Setup and Run and see where the front forms. (Once the front has formed click Run again to turn it off.) See Mr. Neyhard's video for help.
• Click Draw Line and use the mouse to mark the front. (Be sure the mouse stays inside the map while dragging.)
• You can always start over by clicking Clear Last Line or Clear All Lines.
• Repeat this for 9pm and 7am. You can turn Run off or click Setup again if the map gets too dark.
Second, measure the distance between fronts.
\r\n• Turn off Run and click show-distance?. Now, lines that you draw will show their length in kilometers. (You can click Setup to see the map more clearly.)
• Draw a line from one front to the other to measure the distance between them. Start near Fairbanks because the front there will be close to where it will cross Anchorage. Do this for the distance between the first and second front and the second and third front.
Third, calculate the speed of the front. See Mr. Neyhard's video for help.
\r\n• Each set of data is separated by 10 hours.
• Divide the distance between the top and middle front by 10 to get the speed in kilometers per hour.
• Divide the distance between the middle and bottom front by 10 to get the speed in kilometers per hour.
• Average the two speeds by adding them together and then divide by 2.
Finally, calculate the location of the front 24 hours later.
\r\n• Mutliply the average speed by 24 hours to predict where it will be on April 23 at 7am.
• Will the front be on top of Anchorage? Should the NYO Games go on as planned?
You have marked three fronts. Please answer the following three questions:
\\n(1) What distance did you measure between the fronts at April 21, 11am, and April 21, 9pm?
\\n(2) What distance did you measure between the fronts at April 21, 9pm and April 22, 7am?
\\n(3) What is the average distance between the fronts?
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\nIt’s time to put your computational thinking skills to work!
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\r\n| Definition | \r\n\r\n | Computational Thinking Skill | \r\n
|---|---|---|
| \r\n Organizing a large amount of information (data) into smaller more manageable parts. \r\n | \r\n![](\"https://project-resources.concord.org/precipitatingchange/Glossary/ct-decomposition.jpg\") | \r\n\r\n Decomposition \r\nIn Lesson 1, you organized weather station data over a two-day period and radar maps of Alaska every 6 hours to make a prediction. \r\n | \r\n
| \r\n Recognizing that data or information is repeating in a logical (expected) way. \r\n | \r\n![](\"https://project-resources.concord.org/precipitatingchange/Captioned_Videos/new_picts/Lesson_5_new_Embedded_assessment/Netlogo_temp_model.png\") | \r\n\r\n Pattern Recognition \r\nIn Lesson 2, you ran the model to see temperature data and patterns of data moving across the map. Before and after each run of the model, you interpolated data. You discovered that warm and cold spots on the map are at times on certain sides, and also you saw these spots change location over time. \r\nIn Lesson 3 and 4, you ran the models to develop a general statement to answer the question \"Where does it rain?\". \r\n | \r\n
| \r\n Estimating an unknown value based on surrounding information. \r\n | \r\n![\"\"](\"https://project-resources.concord.org/precipitatingchange/Glossary/interpolation.jpg\") | \r\n\r\n Interpolation \r\nIn Lesson 2, you made best guess estimates of the temperatures that were missing on the map. \r\n | \r\n
| \r\n Following a pattern beyond the known data points. \r\n | \r\n![](\"https://project-resources.concord.org/precipitatingchange/Glossary/exptrapolation.jpg\") | \r\n\r\n Extrapolation \r\nIn Lesson 2, you predicted future weather based on patterns you observed in the changing temperatures you collected and visualized. \r\n | \r\n
| \r\n Collecting and organizing data to better understand the topic. \r\n | \r\n![](\"https://project-resources.concord.org/precipitatingchange/Glossary/aggregation.jpg\") | \r\n\r\n Data Aggregation \r\nIn Lesson 2, you observed temperature data from a model and organized the data to see the “big picture”. \r\n | \r\n
| \r\n Simplifying data to make it easier to interpret and find patterns. \r\n | \r\n![](\"https://project-resources.concord.org/precipitatingchange/Glossary/abstraction.jpg\") | \r\n\r\n Data Abstraction \r\nIn Lesson 2, you came up with a color scheme for temperature and changed how the data was represented from numbers to temperature categories, and then to colors. \r\n | \r\n
| \r\n Developing a statement of how things work based on the patterns you observed. \r\n | \r\n![](\"https://project-resources.concord.org/precipitatingchange/Glossary/RuleAbstraction.png\") | \r\n\r\n Rule Abstraction \r\nIn Lesson 3, you made a generic statement to answer the question, \"Where does it rain?\". \r\n | \r\n
| \r\n Looking at the big picture by putting all the components together in the model to see if it works. \r\n | \r\n![](\"https://project-resources.concord.org/precipitatingchange/Glossary/ModelEvaluation.png\") | \r\n\r\n Model Evaluation \r\nIn Lesson 4 and 5, you ran a model to determine whether a rule was still true in different situations. \r\n | \r\n
| \r\n Modifying a rule to be more precise (exact, careful about details) to work in the model. \r\n | \r\n![](\"https://project-resources.concord.org/precipitatingchange/Glossary/RuleRefinement.png\") | \r\n\r\n Rule Refinement \r\nIn Lesson 4 and 5, as you ran the model, you were able to test your rule statements and make changes based on the model. \r\n | \r\n
| \r\n Forecast based on evidence about a future event. \r\n | \r\n![](\"https://project-resources.concord.org/precipitatingchange/Glossary/DatabasedPrediction.png\") | \r\n\r\n Data-based Prediction \r\nIn Lesson 6, you selected data including temperature, air moisture and wind direction to help form a forecast about a future event. \r\n | \r\n
Which skill was the easiest to use? Please explain why.
\\na) Decomposition
\\nb) Pattern Recognition
\\nc) Interpolation
\\nd) Extrapolation
\\ne) Data Aggregation
\\nf) Data Abstraction
\\ng) Rule Abstraction
\\nh) Model Evaluation
\\ni) Rule Refinement
\\nj) Data-based Prediction
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\r\n\"What am I going to wear today?\" is a question everyone asks each morning. How do you determine what you are going to wear? What information do you collect to inform your decision?
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\r\nMs. Tevuk’s class is studying weather. The students will make a computer model to predict weather in Alaska.
\r\nFour students in Ms. Tevuk’s class are figuring out how to estimate the temperature of a location. The students are looking at the map below and have different ideas for estimating the temperature at the location marked X using the recorded temperatures of 31˚ and 59˚.
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Here are the students’ ideas:
\r\n| Alex | \r\nDelana | \r\n||
|---|---|---|---|
| \r\nWe should use the number that is exactly halfway in between 31˚and 59˚. That’s the most exact way to estimate. | \r\n | \r\nWe should mark a number line along the map with the estimate in each square going up the same amount between 31˚ and 59˚. That’d be the best estimate. | \r\n
| Kalin | \r\nSage | \r\n||
| \r\n
| \r\nIt doesn’t make sense to estimate the temperature at the X. We’d need to go there and measure the temperature. You can’t be confident unless you measure it. | \r\n\r\n
| \r\nThe X is closer to the 59˚ than to the 31˚, so let’s choose a number closer to 59˚. That’s the best we can do because we don’t know what’s happening with the weather in those places. | \r\n
Which student’s idea do you agree with the most?
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\r\nMs. Tevuk’s class is studying weather. The students will make a computer model to predict weather in Alaska.
\r\nFour students in Ms. Tevuk’s class are figuring out how to estimate the temperature of a location. The students are looking at the map below and have different ideas for estimating the temperature at the location marked X using the recorded temperatures of 31˚ and 59˚.
\r\n
Here are the students’ ideas:
\r\n| Alex | \r\nDelana | \r\n||
|---|---|---|---|
| \r\nWe should use the number that is exactly halfway in between 31˚and 59˚. That’s the most exact way to estimate. | \r\n | \r\nWe should mark a number line along the map with the estimate in each square going up the same amount between 31˚ and 59˚. That’d be the best estimate. | \r\n
| Kalin | \r\nSage | \r\n||
| \r\n
| \r\nIt doesn’t make sense to estimate the temperature at the X. We’d need to go there and measure the temperature. You can’t be confident unless you measure it. | \r\n\r\n
| \r\nThe X is closer to the 59˚ than to the 31˚, so let’s choose a number closer to 59˚. That’s the best we can do because we don’t know what’s happening with the weather in those places. | \r\n
Which student’s idea do you agree with the most?
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\r\nThere are many different methods to interpolate data. Let’s look at the three interpolation methods used to make these maps.
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For Square A, you may have guessed 54°F degrees or something very close to that. This is the simplest interpolation method. It is called Nearest Neighbor. With this method, you find the nearest weather station to the unknown point and assume it has a similar temperature.
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For Square B, you may have guessed between 38°F and 50°F, but closer to 50°F. Since this square is between two known temperatures, the unknown temperature is probably between 38°F and 50°F. To be even closer, you can think of it like a number line with temperature in each square increasing by four degrees.
\r\n
This method is called Linear Interpolation.
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\r\n
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If two weather scientists were using the same data but different interpolation methods, could they get different results??
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\r\n
Which interpolation method does Map 1 use?
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\r\nHint: To make coloring easier, a colored cell can be used to \"paint\" other cells by dragging over them.
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- To see patterns, it may help to turn on and off the temperature data or the color key. \r\n
Remember: always start by clicking Setup and then Run.
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\r\nMs. Tevuk’s class is looking at a temperature map with five data points taken from weather station observations. All five weather station observations were made at the same time on the same day. The map also shows some temperatures that were estimated using the weather station observation data (estimated temperatures are in parentheses).
\r\n
Ms. Tevuk asks the students which of the estimated temperatures they are LEAST CERTAIN (MOST UNSURE) about.
\r\nHere are the students’ ideas. (Each student’s estimated temperature choice is in bold to make it easier to find.)
\r\n| Alex | \r\nDelana | \r\n||
|---|---|---|---|
| \r\n\r\n I’m least certain about the estimate of 53˚ because it’s furthest outside of the temperatures that were actually measured at a weather station. \r\n
| \r\n | \r\n\r\n I’m least certain about the estimate of 43˚ because it’s far away from any temperatures measured at a weather station. \r\n
| \r\n
| Kalin | \r\nSage | \r\n||
| \r\n
| \r\n\r\n I’m least certain about the estimate of 39˚ because there aren’t any other estimated temperatures near the 39˚ estimate. \r\n
| \r\n\r\n
| \r\n\r\n I’m least certain about the estimate of 37˚ because weather usually moves from west to east, so I’m unsure about estimates on the west side of the map. \r\n
| \r\n
Why do you think the estimated temperature you picked is the one we should be least certain (most unsure) about? Please explain your reasoning.
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\r\nMs. Tevuk’s class is looking at a temperature map with five data points taken from weather station observations. All five weather station observations were made at the same time on the same day. The map also shows some temperatures that were estimated using the weather station observation data (estimated temperatures are in parentheses).
\r\n
Ms. Tevuk asks the students which of the estimated temperatures they are LEAST CERTAIN (MOST UNSURE) about.
\r\nHere are the students’ ideas. (Each student’s estimated temperature choice is in bold to make it easier to find.)
\r\n| Alex | \r\nDelana | \r\n||
|---|---|---|---|
| \r\n\r\n I’m least certain about the estimate of 53˚ because it’s furthest outside of the temperatures that were actually measured at a weather station. \r\n
| \r\n | \r\n\r\n I’m least certain about the estimate of 43˚ because it’s far away from any temperatures measured at a weather station. \r\n
| \r\n
| Kalin | \r\nSage | \r\n||
| \r\n
| \r\n\r\n I’m least certain about the estimate of 39˚ because there aren’t any other estimated temperatures near the 39˚ estimate. \r\n
| \r\n\r\n
| \r\n\r\n I’m least certain about the estimate of 37˚ because weather usually moves from west to east, so I’m unsure about estimates on the west side of the map. \r\n
| \r\n
Why do you think the estimated temperature you picked is the one we should be least certain (most unsure) about? Please explain your reasoning.
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\r\n\r\n
Precipitation symbol = raindrops
\r\n
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Would you change what you selected to wear? Yes or No
\nIf yes, what would you change and why?
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\r\nPrecipitation is shown with three raindrops:
The air moisture and temperature data are shown this way:
Set the map to show the data at 3 pm. Check all cells listed below that have precipitation.
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\nPossible discussion questions:
\n• What was your prediction for the weather in Boston on November 7th at 7am?
• What was your strategy that helped you develop your prediction?
The weather map of the virtual storm below shows temperature and air moisture data at 7pm. Use the relationships you just figured out between air moisture, temperature, and precipitation to try and predict where it will rain at 7pm.
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\r\nHere are the students’ ideas: The rule should be that precipitation happens…
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|---|---|---|---|
| \r\nwith a warm front coming in because warm air moves in and mixes with cold air, which leads to precipitation. You don’t get precipitation with a cold front because cold air is dry. | \r\n | \r\nwith both cold fronts and warm fronts coming in because in both cases warm air and cold air meet, leading to condensation and precipitation. | \r\n
| Kalin | \r\nSage | \r\n||
| \r\n
| \r\nwith a cold front coming in because it’s usually rainy or snowy when it’s cold out. You don’t get precipitation with a warm front because it’s warm when the sun is shining. | \r\n\r\n
| \r\nafter a cold front has passed by because the cold air the front leaves behind is humid, which leads to precipitation. | \r\n
Why do you think the rule you picked is the best one for predicting precipitation? Please explain your reasoning.
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\r\nHere are the students’ ideas: The rule should be that precipitation happens…
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| \r\nwith a warm front coming in because warm air moves in and mixes with cold air, which leads to precipitation. You don’t get precipitation with a cold front because cold air is dry. | \r\n | \r\nwith both cold fronts and warm fronts coming in because in both cases warm air and cold air meet, leading to condensation and precipitation. | \r\n
| Kalin | \r\nSage | \r\n||
| \r\n
| \r\nwith a cold front coming in because it’s usually rainy or snowy when it’s cold out. You don’t get precipitation with a warm front because it’s warm when the sun is shining. | \r\n\r\n
| \r\nafter a cold front has passed by because the cold air the front leaves behind is humid, which leads to precipitation. | \r\n
Why do you think the rule you picked is the best one for predicting precipitation? Please explain your reasoning.
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Think about developing a similar statement that could be used to determine where it will rain.
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\r\nTry your rule with all of the data sets.
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\r\nThe word represent means to let one thing stand for another. For example, some people use the symbol of a
\r\nheart [] to represent (or stand for) love.
Four students in Ms. Tevuk’s class are figuring out how to represent wind direction both (1) in their computer model that does calculations to predict the weather and (2) on a map the computer model produces to show the weather prediction. The students have different ideas about how to represent wind direction for these two purposes.
\r\nHere are some different options Ms. Tevuk’s students are considering for representing wind direction.
\r\n• Wind direction represented with degree number (between 0 and 360) based on the compass
\r\n
• Wind direction represented with letters based on the compass
\r\n
• Wind direction represented with arrows
\r\n
• Wind direction represented with different colors
\r\n
Here are the students’ ideas:
\r\n| Alex | \r\nDelana | \r\n||
|---|---|---|---|
| \r\n\r\n I think we should use the letters for the computer model because there are only 8 options, so the computer will have simple information to calculate with and it won’t get stuck computing. We can use the arrows on the map because that way you can see which way the wind is going. \r\n
| \r\n | \r\n\r\n Let’s use number of degrees on the computer model because computers do calculations with numbers. I think we should use arrows on the map because they make the pattern of wind direction easy to see. \r\n
| \r\n
| Kalin | \r\nSage | \r\n||
| \r\n
| \r\n\r\n I think we should use number of degrees for both the computer model and the map because computers do calculations with numbers and our map should show what the computer calculated. \r\n
| \r\n\r\n
| \r\n\r\n I think we should use colors for both the computer model and the map. Colors are good for the map because it’s easy to see patterns in different colors. Then it helps to have your computer model and map match, so it makes sense to use colors for the computer model too. \r\n
| \r\n
Which student’s idea do you agree with the most?
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\r\nThe word represent means to let one thing stand for another. For example, some people use the symbol of a
\r\nheart [] to represent (or stand for) love.
Four students in Ms. Tevuk’s class are figuring out how to represent wind direction both (1) in their computer model that does calculations to predict the weather and (2) on a map the computer model produces to show the weather prediction. The students have different ideas about how to represent wind direction for these two purposes.
\r\nHere are some different options Ms. Tevuk’s students are considering for representing wind direction.
\r\n• Wind direction represented with degree number (between 0 and 360) based on the compass
\r\n
• Wind direction represented with letters based on the compass
\r\n
• Wind direction represented with arrows
\r\n
• Wind direction represented with different colors
\r\n
Here are the students’ ideas:
\r\n| Alex | \r\nDelana | \r\n||
|---|---|---|---|
| \r\n\r\n I think we should use the letters for the computer model because there are only 8 options, so the computer will have simple information to calculate with and it won’t get stuck computing. We can use the arrows on the map because that way you can see which way the wind is going. \r\n
| \r\n | \r\n\r\n Let’s use number of degrees on the computer model because computers do calculations with numbers. I think we should use arrows on the map because they make the pattern of wind direction easy to see. \r\n
| \r\n
| Kalin | \r\nSage | \r\n||
| \r\n
| \r\n\r\n I think we should use number of degrees for both the computer model and the map because computers do calculations with numbers and our map should show what the computer calculated. \r\n
| \r\n\r\n
| \r\n\r\n I think we should use colors for both the computer model and the map. Colors are good for the map because it’s easy to see patterns in different colors. Then it helps to have your computer model and map match, so it makes sense to use colors for the computer model too. \r\n
| \r\n
Which student’s idea do you agree with the most?
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\r\n
In this lesson you will explore how air masses interact by watching a wind table. You will also revisit weather station data and radar maps you used in Lesson 1 with some additions: wind data and five more weather stations.
In this activity, you will see how wind blowing from two directions interacts on a Wind Table. Please watch the video below for a demonstration on how a Wind Table maps the movement of air on a gird representing a region of Alaska.
\r\nWind Table
\r\n
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Wind direction is often measured with a weather vane or an air sock. When the wind blows, the weather vane rotates and lines up with the path that the air is flowing. So, wind direction is determined by what direction the wind is coming from. It is measured in degrees (°).
\r\n
The arrows on the model below represent the wind direction at each location. Your challenge using this model is to identify the two air masses and mark a line of cells that splits the map into two parts: one section with the wind coming from the same direction and the other section with the wind coming from a different direction.
\r\nRemember to click Startup and Run. Then,
\r\n- \r\n
- Use gray color to mark where the front is located \r\n
- Use blue to mark air mass 1 \r\n
- Use red color to mark air mass 2 \r\n
You can check your work at any time.
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\r\nAn air mass is a body of air with similar temperature and air moisture content.
\r\nIdentifying air masses and their properties is an important part of the work of atmospheric scientists. On the map you may have noticed a temperature number at the top of the square and an air moisture content number at the bottom of the square.
\r\n
Develop a way to identify the two air masses using temperature and air moisture content values provided on the map you just colored.
\r\n
Temperature: Compare Air Mass #1 to Air Mass #2.
\\nAir Mass 1 is:
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\\n\\rAir Mass #2 over land is:
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Air moisture: Compare Air Mass #2 to Air Mass #1.
\\nAir Mass #2 is:
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\r\n
Comparing these maps think about how air masses affect where it rains.
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How does a front affect where it rains?
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\r\n
Alaska Stations: Interpolated at 7 am
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\r\n
Radar Image for 7 am
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\r\nThen, by trying different settings of the temperature and moisture, see if you can make up a rule for what conditions produce precipitation along the front, and on which side of the front the precipitation will occur.
\r\nStart by pressing Setup and Run. As you change temperatures and moisture settings you may want to press Setup occasionally to start fresh. Be sure to discuss what you find with your research team.
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", + "editor_mode": 0, + "layout": 0, + "name": "Alaska 2021 - Lesson 6: Post-thoughts - What Do You Think?", + "notes": "", + "project_id": null, + "related": "", + "runtime": "Activity Player", + "show_submit_button": true, + "student_report_enabled": true, + "thumbnail_url": "https://learn-resources.concord.org/images/stem-resources/icons/pc-lesson5.jpg?v2", + "time_to_complete": null, + "version": 1, + "theme_name": "Precipitating Change", + "pages": [ + { + "additional_sections": {}, + "embeddable_display_mode": "stacked", + "id": 143611, + "is_completion": false, + "is_hidden": false, + "layout": "l-full-width", + "name": "Page 1", + "position": 1, + "show_header": true, + "show_info_assessment": true, + "show_interactive": false, + "show_sidebar": false, + "sidebar": null, + "sidebar_title": "Did you know?", + "toggle_info_assessment": false, + "embeddables": [ + { + "embeddable": { + "content": "How Do We Make An Accurate Model to Predict Weather?
\r\nMs. Tevuk’s students wrote rules for their computer model to predict weather in Alaska. Then they tested their model to see how well it worked. They found their predictions were only right about half the time. The students had different ideas for improving the model.
\r\nHere are the students’ ideas:
\r\n| Alex | \r\nDelana | \r\n||
|---|---|---|---|
| \r\nWe need to run the model longer. The longer you run a computer model the better the prediction will be. | \r\n | \r\nThere’s no way to make a computer model that can predict the weather. Computer models aren’t the real world, so they can’t predict what will happen in the real world. | \r\n
| Kalin | \r\nSage | \r\n||
| \r\n
| \r\nWe should keep working on the rules based on the science of weather prediction. If we get the science right, the model will be accurate. | \r\n\r\n
| \r\nWe should keep working on the rules and testing the model predictions using Alaska weather data. That way we’ll know the model works. | \r\n
Why do you think the choice you picked is the best idea for improving the model? Please explain your reasoning.
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\r\nMs. Tevuk’s students wrote rules for their computer model to predict weather in Alaska. Then they tested their model to see how well it worked. They found their predictions were only right about half the time. The students had different ideas for improving the model.
\r\nHere are the students’ ideas:
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| \r\nWe need to run the model longer. The longer you run a computer model the better the prediction will be. | \r\n | \r\nThere’s no way to make a computer model that can predict the weather. Computer models aren’t the real world, so they can’t predict what will happen in the real world. | \r\n
| Kalin | \r\nSage | \r\n||
| \r\n
| \r\nWe should keep working on the rules based on the science of weather prediction. If we get the science right, the model will be accurate. | \r\n\r\n
| \r\nWe should keep working on the rules and testing the model predictions using Alaska weather data. That way we’ll know the model works. | \r\n
Why do you think the choice you picked is the best idea for improving the model? Please explain your reasoning.
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", + "editor_mode": 0, + "layout": 0, + "name": "Alaska 2021 - Lesson 6: Modeling Fronts", + "notes": "", + "project_id": null, + "related": "", + "runtime": "Activity Player", + "show_submit_button": true, + "student_report_enabled": true, + "thumbnail_url": "https://learn-resources.concord.org/images/stem-resources/icons/pc-lesson5.jpg?v2", + "time_to_complete": null, + "version": 1, + "theme_name": "Precipitating Change", + "pages": [ + { + "additional_sections": {}, + "embeddable_display_mode": "stacked", + "id": 143691, + "is_completion": false, + "is_hidden": false, + "layout": "l-full-width", + "name": "Real World Application", + "position": 1, + "show_header": true, + "show_info_assessment": false, + "show_interactive": false, + "show_sidebar": false, + "sidebar": null, + "sidebar_title": "Did you know?", + "toggle_info_assessment": false, + "embeddables": [ + { + "embeddable": { + "content": "Watch this video featuring Jackie Purcell, a news station meteorologist at station KTUU in Anchorage, AK. She will discuss how moving fronts impact the weather.
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\r\nThroughout this unit you have been exploring different aspects of regional weather data. There is one more piece of information we need to figure out before you can make your final prediction for the unit challenge:
\r\nWhat will the weather be in Anchorage 24 hours from now?
\r\n
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Press Setup and Run on the model below. Watch as the arrows trace their path for 11am. Then do the same for 9pm and 7am. Take note of any differences you see between the times.
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So you may be wondering when it’s going to pass through there. Where the front is at the time of the Alaskan Native Youth Olympics (NYO Games) will greatly affect the weather.
\r\nTo best predict where the front will be in 24 hours, you will need to figure out how fast it is moving. This is a calculation of speed (distance divided by time). Once you know both speed and direction of the front, your weather analysis will help you answer the question, “Will it be raining in Anchorage?”
\r\nThe model below allows you to mark the fronts at three times and measure the distance between them. With the time and distance data you can calculate the approximate speed of the front and then calculate where it will be 24 hours after the last measurement. To do this you can use the tools built into this model.
\r\nFirst, mark the fronts.
\r\n• Click Setup and Run and see where the front forms. (Once the front has formed click Run again to turn it off.) See Mr. Neyhard's video for help.
• Click Draw Line and use the mouse to mark the front. (Be sure the mouse stays inside the map while dragging.)
• You can always start over by clicking Clear Last Line or Clear All Lines.
• Repeat this for 9pm and 7am. You can turn Run off or click Setup again if the map gets too dark.
Second, measure the distance between fronts.
\r\n• Turn off Run and click show-distance?. Now, lines that you draw will show their length in kilometers. (You can click Setup to see the map more clearly.)
• Draw a line from one front to the other to measure the distance between them. Start near Fairbanks because the front there will be close to where it will cross Anchorage. Do this for the distance between the first and second front and the second and third front.
Third, calculate the speed of the front. See Mr. Neyhard's video for help.
\r\n• Each set of data is separated by 10 hours.
• Divide the distance between the top and middle front by 10 to get the speed in kilometers per hour.
• Divide the distance between the middle and bottom front by 10 to get the speed in kilometers per hour.
• Average the two speeds by adding them together and then divide by 2.
Finally, calculate the location of the front 24 hours later.
\r\n• Mutliply the average speed by 24 hours to predict where it will be on April 23 at 7am.
• Will the front be on top of Anchorage? Should the NYO Games go on as planned?
You have marked three fronts. Please answer the following three questions:
\\n(1) What distance did you measure between the fronts at April 21, 11am, and April 21, 9pm?
\\n(2) What distance did you measure between the fronts at April 21, 9pm and April 22, 7am?
\\n(3) What is the average distance between the fronts?
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\nIt’s time to put your computational thinking skills to work!
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\r\n| Definition | \r\n\r\n | Computational Thinking Skill | \r\n
|---|---|---|
| \r\n Organizing a large amount of information (data) into smaller more manageable parts. \r\n | \r\n | \r\n\r\n Decomposition \r\nIn Lesson 1, you organized weather station data over a two-day period and radar maps of Alaska every 6 hours to make a prediction. \r\n | \r\n
| \r\n Recognizing that data or information is repeating in a logical (expected) way. \r\n | \r\n | \r\n\r\n Pattern Recognition \r\nIn Lesson 2, you ran the model to see temperature data and patterns of data moving across the map. Before and after each run of the model, you interpolated data. You discovered that warm and cold spots on the map are at times on certain sides, and also you saw these spots change location over time. \r\nIn Lesson 3 and 4, you ran the models to develop a general statement to answer the question \"Where does it rain?\". \r\n | \r\n
| \r\n Estimating an unknown value based on surrounding information. \r\n | \r\n | \r\n\r\n Interpolation \r\nIn Lesson 2, you made best guess estimates of the temperatures that were missing on the map. \r\n | \r\n
| \r\n Following a pattern beyond the known data points. \r\n | \r\n | \r\n\r\n Extrapolation \r\nIn Lesson 2, you predicted future weather based on patterns you observed in the changing temperatures you collected and visualized. \r\n | \r\n
| \r\n Collecting and organizing data to better understand the topic. \r\n | \r\n | \r\n\r\n Data Aggregation \r\nIn Lesson 2, you observed temperature data from a model and organized the data to see the “big picture”. \r\n | \r\n
| \r\n Simplifying data to make it easier to interpret and find patterns. \r\n | \r\n | \r\n\r\n Data Abstraction \r\nIn Lesson 2, you came up with a color scheme for temperature and changed how the data was represented from numbers to temperature categories, and then to colors. \r\n | \r\n
| \r\n Developing a statement of how things work based on the patterns you observed. \r\n | \r\n | \r\n\r\n Rule Abstraction \r\nIn Lesson 3, you made a generic statement to answer the question, \"Where does it rain?\". \r\n | \r\n
| \r\n Looking at the big picture by putting all the components together in the model to see if it works. \r\n | \r\n | \r\n\r\n Model Evaluation \r\nIn Lesson 4 and 5, you ran a model to determine whether a rule was still true in different situations. \r\n | \r\n
| \r\n Modifying a rule to be more precise (exact, careful about details) to work in the model. \r\n | \r\n | \r\n\r\n Rule Refinement \r\nIn Lesson 4 and 5, as you ran the model, you were able to test your rule statements and make changes based on the model. \r\n | \r\n
| \r\n Forecast based on evidence about a future event. \r\n | \r\n | \r\n\r\n Data-based Prediction \r\nIn Lesson 6, you selected data including temperature, air moisture and wind direction to help form a forecast about a future event. \r\n | \r\n
Which skill was the easiest to use? Please explain why.
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\\nd) Extrapolation
\\ne) Data Aggregation
\\nf) Data Abstraction
\\ng) Rule Abstraction
\\nh) Model Evaluation
\\ni) Rule Refinement
\\nj) Data-based Prediction
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\r\nWhat if you needed a weather forecast and couldn’t use your usual ways of checking the weather? Imagine you’re planning to go snowmobiling on the tundra, but there’s a big power failure and there’s no TV, Internet, or cell phone available. Even the radio isn’t working! You might try to figure out a weather forecast with help from someone you know.
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\r\nMs. Tevuk’s class is studying weather. The students will make a computer model to predict weather in Alaska.
\r\nFour students in Ms. Tevuk’s class are figuring out how to estimate the temperature of a location. The students are looking at the map below and have different ideas for estimating the temperature at the location marked X using the recorded temperatures of 31˚ and 59˚.
\r\n
Here are the students’ ideas:
\r\n| Alex | \r\nDelana | \r\n||
|---|---|---|---|
| \r\nWe should use the number that is exactly halfway in between 31˚and 59˚. That’s the most exact way to estimate. | \r\n | \r\nWe should mark a number line along the map with the estimate in each square going up the same amount between 31˚ and 59˚. That’d be the best estimate. | \r\n
| Kalin | \r\nSage | \r\n||
| \r\n
| \r\nIt doesn’t make sense to estimate the temperature at the X. We’d need to go there and measure the temperature. You can’t be confident unless you measure it. | \r\n\r\n
| \r\nThe X is closer to the 59˚ than to the 31˚, so let’s choose a number closer to 59˚. That’s the best we can do because we don’t know what’s happening with the weather in those places. | \r\n
Which student’s idea do you agree with the most?
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\r\nMs. Tevuk’s class is studying weather. The students will make a computer model to predict weather in Alaska.
\r\nFour students in Ms. Tevuk’s class are figuring out how to estimate the temperature of a location. The students are looking at the map below and have different ideas for estimating the temperature at the location marked X using the recorded temperatures of 31˚ and 59˚.
\r\n
Here are the students’ ideas:
\r\n| Alex | \r\nDelana | \r\n||
|---|---|---|---|
| \r\nWe should use the number that is exactly halfway in between 31˚and 59˚. That’s the most exact way to estimate. | \r\n | \r\nWe should mark a number line along the map with the estimate in each square going up the same amount between 31˚ and 59˚. That’d be the best estimate. | \r\n
| Kalin | \r\nSage | \r\n||
| \r\n
| \r\nIt doesn’t make sense to estimate the temperature at the X. We’d need to go there and measure the temperature. You can’t be confident unless you measure it. | \r\n\r\n
| \r\nThe X is closer to the 59˚ than to the 31˚, so let’s choose a number closer to 59˚. That’s the best we can do because we don’t know what’s happening with the weather in those places. | \r\n
Which student’s idea do you agree with the most?
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\r\nThere are many different methods to interpolate data. Let’s look at the three interpolation methods used to make these maps.
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For Square A, you may have guessed 54°F degrees or something very close to that. This is the simplest interpolation method. It is called Nearest Neighbor. With this method, you find the nearest weather station to the unknown point and assume it has a similar temperature.
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For Square B, you may have guessed between 38°F and 50°F, but closer to 50°F. Since this square is between two known temperatures, the unknown temperature is probably between 38°F and 50°F. To be even closer, you can think of it like a number line with temperature in each square increasing by four degrees.
\r\n
This method is called Linear Interpolation.
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\r\n
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If two weather scientists were using the same data but different interpolation methods, could they get different results??
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\r\n
Which interpolation method does Map 1 use?
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\r\nBelow you will see three maps of temperature data each one at a different time during one day. Study the changes of temperature over time looking for patterns in the data.
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\r\n- \r\n
- Use the slider to see temperatures from 7am to 3pm. \r\n
- Look for patterns of temperature changes over time. \r\n
- To see patterns, it may help to turn on and off the temperature data or the color key. \r\n
Remember: always start by clicking Setup and then Run.
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What is the definition of the word “Interpolation”?
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\r\nMs. Tevuk’s class is looking at a temperature map with five data points taken from weather station observations. All five weather station observations were made at the same time on the same day. The map also shows some temperatures that were estimated using the weather station observation data (estimated temperatures are in parentheses).
\r\n
Ms. Tevuk asks the students which of the estimated temperatures they are LEAST CERTAIN (MOST UNSURE) about.
\r\nHere are the students’ ideas. (Each student’s estimated temperature choice is in bold to make it easier to find.)
\r\n| Alex | \r\nDelana | \r\n||
|---|---|---|---|
| \r\n\r\n I’m least certain about the estimate of 53˚ because it’s furthest outside of the temperatures that were actually measured at a weather station. \r\n
| \r\n | \r\n\r\n I’m least certain about the estimate of 43˚ because it’s far away from any temperatures measured at a weather station. \r\n
| \r\n
| Kalin | \r\nSage | \r\n||
| \r\n
| \r\n\r\n I’m least certain about the estimate of 39˚ because there aren’t any other estimated temperatures near the 39˚ estimate. \r\n
| \r\n\r\n
| \r\n\r\n I’m least certain about the estimate of 37˚ because weather usually moves from west to east, so I’m unsure about estimates on the west side of the map. \r\n
| \r\n
Why do you think the estimated temperature you picked is the one we should be least certain (most unsure) about? Please explain your reasoning.
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\r\nMs. Tevuk’s class is looking at a temperature map with five data points taken from weather station observations. All five weather station observations were made at the same time on the same day. The map also shows some temperatures that were estimated using the weather station observation data (estimated temperatures are in parentheses).
\r\n
Ms. Tevuk asks the students which of the estimated temperatures they are LEAST CERTAIN (MOST UNSURE) about.
\r\nHere are the students’ ideas. (Each student’s estimated temperature choice is in bold to make it easier to find.)
\r\n| Alex | \r\nDelana | \r\n||
|---|---|---|---|
| \r\n\r\n I’m least certain about the estimate of 53˚ because it’s furthest outside of the temperatures that were actually measured at a weather station. \r\n
| \r\n | \r\n\r\n I’m least certain about the estimate of 43˚ because it’s far away from any temperatures measured at a weather station. \r\n
| \r\n
| Kalin | \r\nSage | \r\n||
| \r\n
| \r\n\r\n I’m least certain about the estimate of 39˚ because there aren’t any other estimated temperatures near the 39˚ estimate. \r\n
| \r\n\r\n
| \r\n\r\n I’m least certain about the estimate of 37˚ because weather usually moves from west to east, so I’m unsure about estimates on the west side of the map. \r\n
| \r\n
Why do you think the estimated temperature you picked is the one we should be least certain (most unsure) about? Please explain your reasoning.
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Precipitation symbol = raindrops
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Would you change what you selected to wear? Yes or No
\nIf yes, what would you change and why?
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\n• What was your prediction for the weather in Boston on November 7th at 7am?
• What was your strategy that helped you develop your prediction?
The weather map of the virtual storm below shows temperature and air moisture data at 7pm. Use the relationships you just figured out between air moisture, temperature, and precipitation to try and predict where it will rain at 7pm.
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", + "editor_mode": 0, + "layout": 0, + "name": "Alaska 2021 - Lesson 4: Post-thoughts - What Do You Think?", + "notes": "", + "project_id": 25, + "related": "", + "runtime": "Activity Player", + "show_submit_button": true, + "student_report_enabled": true, + "thumbnail_url": "https://learn-resources.concord.org/images/stem-resources/icons/pc-lesson3.png", + "time_to_complete": null, + "version": 1, + "theme_name": "Precipitating Change", + "pages": [ + { + "additional_sections": {}, + "embeddable_display_mode": "stacked", + "id": 143598, + "is_completion": false, + "is_hidden": false, + "layout": "l-full-width", + "name": "Page 1", + "position": 1, + "show_header": true, + "show_info_assessment": true, + "show_interactive": false, + "show_sidebar": false, + "sidebar": null, + "sidebar_title": "Did you know?", + "toggle_info_assessment": false, + "embeddables": [ + { + "embeddable": { + "content": "What Are the Rules for Fronts and Precipitation?
\r\nMs. Tevuk’s students need to write a rule for their computer model to predict areas of precipitation on a map showing weather fronts. They have different ideas for what the rule should be.
\r\nHere are the students’ ideas: The rule should be that precipitation happens…
\r\n| Alex | \r\nDelana | \r\n||
|---|---|---|---|
| \r\nwith a warm front coming in because warm air moves in and mixes with cold air, which leads to precipitation. You don’t get precipitation with a cold front because cold air is dry. | \r\n | \r\nwith both cold fronts and warm fronts coming in because in both cases warm air and cold air meet, leading to condensation and precipitation. | \r\n
| Kalin | \r\nSage | \r\n||
| \r\n
| \r\nwith a cold front coming in because it’s usually rainy or snowy when it’s cold out. You don’t get precipitation with a warm front because it’s warm when the sun is shining. | \r\n\r\n
| \r\nafter a cold front has passed by because the cold air the front leaves behind is humid, which leads to precipitation. | \r\n
Why do you think the rule you picked is the best one for predicting precipitation? Please explain your reasoning.
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", + "editor_mode": 0, + "layout": 0, + "name": "Alaska 2021 - Lesson 4: Pre-thoughts - What Do You Think?", + "notes": "", + "project_id": 25, + "related": "", + "runtime": "Activity Player", + "show_submit_button": true, + "student_report_enabled": true, + "thumbnail_url": "https://learn-resources.concord.org/images/stem-resources/icons/pc-lesson3.png", + "time_to_complete": null, + "version": 1, + "theme_name": "Precipitating Change", + "pages": [ + { + "additional_sections": {}, + "embeddable_display_mode": "stacked", + "id": 143597, + "is_completion": false, + "is_hidden": false, + "layout": "l-full-width", + "name": "Page 1", + "position": 1, + "show_header": true, + "show_info_assessment": true, + "show_interactive": false, + "show_sidebar": false, + "sidebar": null, + "sidebar_title": "Did you know?", + "toggle_info_assessment": false, + "embeddables": [ + { + "embeddable": { + "content": "What Are the Rules for Fronts and Precipitation?
\r\nMs. Tevuk’s students need to write a rule for their computer model to predict areas of precipitation on a map showing weather fronts. They have different ideas for what the rule should be.
\r\nHere are the students’ ideas: The rule should be that precipitation happens…
\r\n| Alex | \r\nDelana | \r\n||
|---|---|---|---|
| \r\nwith a warm front coming in because warm air moves in and mixes with cold air, which leads to precipitation. You don’t get precipitation with a cold front because cold air is dry. | \r\n | \r\nwith both cold fronts and warm fronts coming in because in both cases warm air and cold air meet, leading to condensation and precipitation. | \r\n
| Kalin | \r\nSage | \r\n||
| \r\n
| \r\nwith a cold front coming in because it’s usually rainy or snowy when it’s cold out. You don’t get precipitation with a warm front because it’s warm when the sun is shining. | \r\n\r\n
| \r\nafter a cold front has passed by because the cold air the front leaves behind is humid, which leads to precipitation. | \r\n
Why do you think the rule you picked is the best one for predicting precipitation? Please explain your reasoning.
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\nExample: This rule has two parts that must happen to have a certain result. If it was a [ very nice summer ] and if it is [ August ], then there will be [ lots of berries to pick ].
\n
Think about developing a similar statement that could be used to determine where it will rain.
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\r\nTry your rule with all of the data sets.
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\r\nThe word represent means to let one thing stand for another. For example, some people use the symbol of a
\r\nheart [] to represent (or stand for) love.
Four students in Ms. Tevuk’s class are figuring out how to represent wind direction both (1) in their computer model that does calculations to predict the weather and (2) on a map the computer model produces to show the weather prediction. The students have different ideas about how to represent wind direction for these two purposes.
\r\nHere are some different options Ms. Tevuk’s students are considering for representing wind direction.
\r\n• Wind direction represented with degree number (between 0 and 360) based on the compass
\r\n
• Wind direction represented with letters based on the compass
\r\n
• Wind direction represented with arrows
\r\n
• Wind direction represented with different colors
\r\n
Here are the students’ ideas:
\r\n| Alex | \r\nDelana | \r\n||
|---|---|---|---|
| \r\n\r\n I think we should use the letters for the computer model because there are only 8 options, so the computer will have simple information to calculate with and it won’t get stuck computing. We can use the arrows on the map because that way you can see which way the wind is going. \r\n
| \r\n | \r\n\r\n Let’s use number of degrees on the computer model because computers do calculations with numbers. I think we should use arrows on the map because they make the pattern of wind direction easy to see. \r\n
| \r\n
| Kalin | \r\nSage | \r\n||
| \r\n
| \r\n\r\n I think we should use number of degrees for both the computer model and the map because computers do calculations with numbers and our map should show what the computer calculated. \r\n
| \r\n\r\n
| \r\n\r\n I think we should use colors for both the computer model and the map. Colors are good for the map because it’s easy to see patterns in different colors. Then it helps to have your computer model and map match, so it makes sense to use colors for the computer model too. \r\n
| \r\n
Which student’s idea do you agree with the most?
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\r\nThe word represent means to let one thing stand for another. For example, some people use the symbol of a
\r\nheart [] to represent (or stand for) love.
Four students in Ms. Tevuk’s class are figuring out how to represent wind direction both (1) in their computer model that does calculations to predict the weather and (2) on a map the computer model produces to show the weather prediction. The students have different ideas about how to represent wind direction for these two purposes.
\r\nHere are some different options Ms. Tevuk’s students are considering for representing wind direction.
\r\n• Wind direction represented with degree number (between 0 and 360) based on the compass
\r\n
• Wind direction represented with letters based on the compass
\r\n
• Wind direction represented with arrows
\r\n
• Wind direction represented with different colors
\r\n
Here are the students’ ideas:
\r\n| Alex | \r\nDelana | \r\n||
|---|---|---|---|
| \r\n\r\n I think we should use the letters for the computer model because there are only 8 options, so the computer will have simple information to calculate with and it won’t get stuck computing. We can use the arrows on the map because that way you can see which way the wind is going. \r\n
| \r\n | \r\n\r\n Let’s use number of degrees on the computer model because computers do calculations with numbers. I think we should use arrows on the map because they make the pattern of wind direction easy to see. \r\n
| \r\n
| Kalin | \r\nSage | \r\n||
| \r\n
| \r\n\r\n I think we should use number of degrees for both the computer model and the map because computers do calculations with numbers and our map should show what the computer calculated. \r\n
| \r\n\r\n
| \r\n\r\n I think we should use colors for both the computer model and the map. Colors are good for the map because it’s easy to see patterns in different colors. Then it helps to have your computer model and map match, so it makes sense to use colors for the computer model too. \r\n
| \r\n
Which student’s idea do you agree with the most?
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", + "editor_mode": 0, + "layout": 0, + "name": "Alaska 2021 - Lesson 5: Identifying Air Masses", + "notes": "", + "project_id": null, + "related": "", + "runtime": "Activity Player", + "show_submit_button": true, + "student_report_enabled": true, + "thumbnail_url": "https://learn-resources.concord.org/images/stem-resources/icons/pc-lesson4.jpg", + "time_to_complete": null, + "version": 1, + "theme_name": "Precipitating Change", + "pages": [ + { + "additional_sections": {}, + "embeddable_display_mode": "stacked", + "id": 143690, + "is_completion": false, + "is_hidden": false, + "layout": "l-full-width", + "name": "Real World Application", + "position": 1, + "show_header": true, + "show_info_assessment": false, + "show_interactive": false, + "show_sidebar": false, + "sidebar": null, + "sidebar_title": "Did you know?", + "toggle_info_assessment": false, + "embeddables": [ + { + "embeddable": { + "content": "Watch this video featuring Jackie Purcell, a news station meteorologist at station KTUU in Anchorage, AK. She will discuss how wind direction impacts different air masses.
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\r\n
In this lesson you will explore how air masses interact by watching a wind table. You will also revisit weather station data and radar maps you used in Lesson 1 with some additions: wind data and five more weather stations.
In this activity, you will see how wind blowing from two directions interacts on a Wind Table. Please watch the video below for a demonstration on how a Wind Table maps the movement of air on a gird representing a region of Alaska.
\r\nWind Table
\r\n
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Wind direction is often measured with a weather vane or an air sock. When the wind blows, the weather vane rotates and lines up with the path that the air is flowing. So, wind direction is determined by what direction the wind is coming from. It is measured in degrees (°).
\r\n
The arrows on the model below represent the wind direction at each location. Your challenge using this model is to identify the two air masses and mark a line of cells that splits the map into two parts: one section with the wind coming from the same direction and the other section with the wind coming from a different direction.
\r\nRemember to click Startup and Run. Then,
\r\n- \r\n
- Use gray color to mark where the front is located \r\n
- Use blue to mark air mass 1 \r\n
- Use red color to mark air mass 2 \r\n
You can check your work at any time.
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\r\nAn air mass is a body of air with similar temperature and air moisture content.
\r\nIdentifying air masses and their properties is an important part of the work of atmospheric scientists. On the map you may have noticed a temperature number at the top of the square and an air moisture content number at the bottom of the square.
\r\n
Develop a way to identify the two air masses using temperature and air moisture content values provided on the map you just colored.
\r\n
Temperature: Compare Air Mass #1 to Air Mass #2.
\\nAir Mass 1 is:
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\\n\\rAir Mass #2 over land is:
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Air moisture: Compare Air Mass #2 to Air Mass #1.
\\nAir Mass #2 is:
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\r\n
Comparing these maps think about how air masses affect where it rains.
\r\n", + "is_callout": true, + "is_full_width": true, + "is_hidden": false, + "name": "Comparing Weather Data", + "type": "Embeddable::Xhtml", + "ref_id": "147911-Embeddable::Xhtml" + }, + "section": null + }, + { + "embeddable": { + "name": "Thinking about Where Rain Will Occur", + "url_fragment": null, + "authored_state": "{\"version\":1,\"questionType\":\"multiple_choice\",\"multipleAnswers\":false,\"layout\":\"vertical\",\"choices\":[{\"id\":\"1\",\"content\":\"It rains across the front making a cross shape.\",\"correct\":false},{\"id\":\"2\",\"content\":\"It rains away from the front.\",\"correct\":false},{\"id\":\"3\",\"content\":\"It rains on the warm side of the front.\",\"correct\":true},{\"content\":\"It rains on the cold side of the front.\",\"correct\":false,\"id\":\"5a069223-5be8-4ee2-9006-b0e79fcb950a\"}],\"prompt\":\"
How does a front affect where it rains?
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\r\n
Alaska Stations: Interpolated at 7 am
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\r\n
Radar Image for 7 am
", + "is_callout": false, + "is_full_width": true, + "is_hidden": false, + "name": "", + "type": "Embeddable::Xhtml", + "ref_id": "147913-Embeddable::Xhtml" + }, + "section": "header_block" + }, + { + "embeddable": { + "name": "Comparing Your Prediction to the Data", + "url_fragment": null, + "authored_state": "{\"version\":1,\"questionType\":\"open_response\",\"prompt\":\"How accurate was your prediction? Explain.
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\r\nIf the front to the northwest is colder than 5 degrees than the front to the south, and the air moisture of the front to the south is 7 or above then it will rain in the front to the south.
\r\nThe model below allows you to change the temperature and air moisture content of the wind that enteres the model. Explore this model to see if the rule for rain (above) is obeyed. Also, try to discover if there may be other rules that produces rain and what they might be. Remember to click Setup and Run.
\r\n- \r\n
- The arrowheads show the incoming wind. \r\n
- The temperature and moisture content of the wind are set by the sliders on the South and West sides. \r\n
- When precipitation occurs, it is shown as green circles. The larger the circle, the heavier the rain. \r\n
Read the questions below to help focus your exploration of the model. Hint: start by identifying the fronts. Use city names to describe where fronts and rain occur.
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\r\nMs. Tevuk’s students wrote rules for their computer model to predict weather in Alaska. Then they tested their model to see how well it worked. They found their predictions were only right about half the time. The students had different ideas for improving the model.
\r\nHere are the students’ ideas:
\r\n| Alex | \r\nDelana | \r\n||
|---|---|---|---|
| \r\nWe need to run the model longer. The longer you run a computer model the better the prediction will be. | \r\n | \r\nThere’s no way to make a computer model that can predict the weather. Computer models aren’t the real world, so they can’t predict what will happen in the real world. | \r\n
| Kalin | \r\nSage | \r\n||
| \r\n
| \r\nWe should keep working on the rules based on the science of weather prediction. If we get the science right, the model will be accurate. | \r\n\r\n
| \r\nWe should keep working on the rules and testing the model predictions using Alaska weather data. That way we’ll know the model works. | \r\n
Which student's idea do you agree with the most?
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", + "editor_mode": 0, + "layout": 0, + "name": "Alaska 2021 - Lesson 6: Pre-thoughts - What Do You Think?", + "notes": "", + "project_id": null, + "related": "", + "runtime": "Activity Player", + "show_submit_button": true, + "student_report_enabled": true, + "thumbnail_url": "https://learn-resources.concord.org/images/stem-resources/icons/pc-lesson5.jpg?v2", + "time_to_complete": null, + "version": 1, + "theme_name": "Precipitating Change", + "pages": [ + { + "additional_sections": {}, + "embeddable_display_mode": "stacked", + "id": 143610, + "is_completion": false, + "is_hidden": false, + "layout": "l-full-width", + "name": "Page 1", + "position": 1, + "show_header": true, + "show_info_assessment": true, + "show_interactive": false, + "show_sidebar": false, + "sidebar": null, + "sidebar_title": "Did you know?", + "toggle_info_assessment": false, + "embeddables": [ + { + "embeddable": { + "content": "How Do We Make An Accurate Model to Predict Weather?
\r\nMs. Tevuk’s students wrote rules for their computer model to predict weather in Alaska. Then they tested their model to see how well it worked. They found their predictions were only right about half the time. The students had different ideas for improving the model.
\r\nHere are the students’ ideas:
\r\n| Alex | \r\nDelana | \r\n||
|---|---|---|---|
| \r\nWe need to run the model longer. The longer you run a computer model the better the prediction will be. | \r\n | \r\nThere’s no way to make a computer model that can predict the weather. Computer models aren’t the real world, so they can’t predict what will happen in the real world. | \r\n
| Kalin | \r\nSage | \r\n||
| \r\n
| \r\nWe should keep working on the rules based on the science of weather prediction. If we get the science right, the model will be accurate. | \r\n\r\n
| \r\nWe should keep working on the rules and testing the model predictions using Alaska weather data. That way we’ll know the model works. | \r\n
Why do you think the choice you picked is the best idea for improving the model? Please explain your reasoning.
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\r\nThroughout this unit you have been exploring different aspects of regional weather data. There is one more piece of information we need to figure out before you can make your final prediction for the unit challenge:
\r\nWhat will the weather be in Anchorage 24 hours from now?
\r\n
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Press Setup and Run on the model below. Watch as the arrows trace their path for 11am. Then do the same for 9pm and 7am. Take note of any differences you see between the times.
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So you may be wondering when it’s going to pass through there. Where the front is at the time of the Alaskan Native Youth Olympics (NYO Games) will greatly affect the weather.
\r\nTo best predict where the front will be in 24 hours, you will need to figure out how fast it is moving. This is a calculation of speed (distance divided by time). Once you know both speed and direction of the front, your weather analysis will help you answer the question, “Will it be raining in Anchorage?”
\r\nThe model below allows you to mark the fronts at three times and measure the distance between them. With the time and distance data you can calculate the approximate speed of the front and then calculate where it will be 24 hours after the last measurement. To do this you can use the tools built into this model.
\r\nFirst, mark the fronts.
\r\n• Click Setup and Run and see where the front forms. (Once the front has formed click Run again to turn it off.) See Mr. Neyhard's video for help.
• Click Draw Line and use the mouse to mark the front. (Be sure the mouse stays inside the map while dragging.)
• You can always start over by clicking Clear Last Line or Clear All Lines.
• Repeat this for 9pm and 7am. You can turn Run off or click Setup again if the map gets too dark.
Second, measure the distance between fronts.
\r\n• Turn off Run and click show-distance?. Now, lines that you draw will show their length in kilometers. (You can click Setup to see the map more clearly.)
• Draw a line from one front to the other to measure the distance between them. Start near Fairbanks because the front there will be close to where it will cross Anchorage. Do this for the distance between the first and second front and the second and third front.
Third, calculate the speed of the front. See Mr. Neyhard's video for help.
\r\n• Each set of data is separated by 10 hours.
• Divide the distance between the top and middle front by 10 to get the speed in kilometers per hour.
• Divide the distance between the middle and bottom front by 10 to get the speed in kilometers per hour.
• Average the two speeds by adding them together and then divide by 2.
Finally, calculate the location of the front 24 hours later.
\r\n• Mutliply the average speed by 24 hours to predict where it will be on April 23 at 7am.
• Will the front be on top of Anchorage? Should the NYO Games go on as planned?
You have marked three fronts. Please answer the following questions:
\\n(1) What distance did you measure between the fronts at April 21, 11am and April 21, 9pm?
\\n(2) What distance did you measure between the fronts at April 21, 9pm and April 22, 7am?
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\nIt’s time to put your computational thinking skills to work!
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\r\n| Definition | \r\n\r\n | Computational Thinking Skill | \r\n
|---|---|---|
| \r\n Organizing a large amount of information (data) into smaller more manageable parts. \r\n | \r\n | \r\n\r\n Decomposition \r\nIn Lesson 1, you organized weather station data over a two-day period and radar maps of Alaska every 6 hours to make a prediction. \r\n | \r\n
| \r\n Recognizing that data or information is repeating in a logical (expected) way. \r\n | \r\n | \r\n\r\n Pattern Recognition \r\nIn Lesson 2, you ran the model to see temperature data and patterns of data moving across the map. Before and after each run of the model, you interpolated data. You discovered that warm and cold spots on the map are at times on certain sides, and also you saw these spots change location over time. \r\nIn Lesson 3 and 4, you ran the models to develop a general statement to answer the question \"Where does it rain?\". \r\n | \r\n
| \r\n Estimating an unknown value based on surrounding information. \r\n | \r\n | \r\n\r\n Interpolation \r\nIn Lesson 2, you made best guess estimates of the temperatures that were missing on the map. \r\n | \r\n
| \r\n Following a pattern beyond the known data points. \r\n | \r\n | \r\n\r\n Extrapolation \r\nIn Lesson 2, you predicted future weather based on patterns you observed in the changing temperatures you collected and visualized. \r\n | \r\n
| \r\n Collecting and organizing data to better understand the topic. \r\n | \r\n | \r\n\r\n Data Aggregation \r\nIn Lesson 2, you observed temperature data from a model and organized the data to see the “big picture”. \r\n | \r\n
| \r\n Simplifying data to make it easier to interpret and find patterns. \r\n | \r\n | \r\n\r\n Data Abstraction \r\nIn Lesson 2, you came up with a color scheme for temperature and changed how the data was represented from numbers to temperature categories, and then to colors. \r\n | \r\n
| \r\n Developing a statement of how things work based on the patterns you observed. \r\n | \r\n | \r\n\r\n Rule Abstraction \r\nIn Lesson 3, you made a generic statement to answer the question, \"Where does it rain?\". \r\n | \r\n
| \r\n Looking at the big picture by putting all the components together in the model to see if it works. \r\n | \r\n | \r\n\r\n Model Evaluation \r\nIn Lesson 4 and 5, you ran a model to determine whether a rule was still true in different situations. \r\n | \r\n
| \r\n Modifying a rule to be more precise (exact, careful about details) to work in the model. \r\n | \r\n | \r\n\r\n Rule Refinement \r\nIn Lesson 4 and 5, as you ran the model, you were able to test your rule statements and make changes based on the model. \r\n | \r\n
| \r\n Forecast based on evidence about a future event. \r\n | \r\n | \r\n\r\n Data-based Prediction \r\nIn Lesson 6, you selected data including temperature, air moisture and wind direction to help form a forecast about a future event. \r\n | \r\n
Which skill was the easiest to use? Please explain why.
\\na) Decomposition
\\nb) Pattern Recognition
\\nc) Interpolation
\\nd) Extrapolation
\\ne) Data Aggregation
\\nf) Data Abstraction
\\ng) Rule Abstraction
\\nh) Model Evaluation
\\ni) Rule Refinement
\\nj) Data-based Prediction
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\\na) Decomposition
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\\nc) Interpolation
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How confident are you of your final prediction?
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\r\nTalk with an adult family member or family friend who you think might have experience predicting the weather (maybe even someone who is older who learned how to predict the weather when they were around your age).
\r\nWhat if you needed a weather forecast and couldn’t use your usual ways of checking the weather? Imagine you’re planning to go snowmobiling on the tundra, but there’s a big power failure and there’s no TV, Internet, or cell phone available. Even the radio isn’t working! You might try to figure out a weather forecast with help from someone you know.
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Here are the students’ ideas:
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|---|---|---|---|
| \r\nWe should use the number that is exactly halfway in between 31˚and 59˚. That’s the most exact way to estimate. | \r\n | \r\nWe should mark a number line along the map with the estimate in each square going up the same amount between 31˚ and 59˚. That’d be the best estimate. | \r\n
| Kalin | \r\nSage | \r\n||
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\r\nMs. Tevuk’s class is studying weather. The students will make a computer model to predict weather in Alaska.
\r\nFour students in Ms. Tevuk’s class are figuring out how to estimate the temperature of a location. The students are looking at the map below and have different ideas for estimating the temperature at the location marked X using the recorded temperatures of 31˚ and 59˚.
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Here are the students’ ideas:
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|---|---|---|---|
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| Kalin | \r\nSage | \r\n||
| \r\n
| \r\nIt doesn’t make sense to estimate the temperature at the X. We’d need to go there and measure the temperature. You can’t be confident unless you measure it. | \r\n\r\n
| \r\nThe X is closer to the 59˚ than to the 31˚, so let’s choose a number closer to 59˚. That’s the best we can do because we don’t know what’s happening with the weather in those places. | \r\n
Which student’s idea do you agree with the most?
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\r\nThere are many different methods to interpolate data. Let’s look at the three interpolation methods used to make these maps.
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For Square A, you may have guessed 54°F degrees or something very close to that. This is the simplest interpolation method. It is called Nearest Neighbor. With this method, you find the nearest weather station to the unknown point and assume it has a similar temperature.
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For Square B, you may have guessed between 38°F and 50°F, but closer to 50°F. Since this square is between two known temperatures, the unknown temperature is probably between 38°F and 50°F. To be even closer, you can think of it like a number line with temperature in each square increasing by four degrees.
\r\n
This method is called Linear Interpolation.
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\r\n
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Which interpolation method does Map 1 use?
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\r\nHint: To make coloring easier, a colored cell can be used to \"paint\" other cells by dragging over them.
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- To see patterns, it may help to turn on and off the temperature data or the color key. \r\n
Remember: always start by clicking Setup and then Run.
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\r\nMs. Tevuk’s class is looking at a temperature map with five data points taken from weather station observations. All five weather station observations were made at the same time on the same day. The map also shows some temperatures that were estimated using the weather station observation data (estimated temperatures are in parentheses).
\r\n
Ms. Tevuk asks the students which of the estimated temperatures they are LEAST CERTAIN (MOST UNSURE) about.
\r\nHere are the students’ ideas. (Each student’s estimated temperature choice is in bold to make it easier to find.)
\r\n| Alex | \r\nDelana | \r\n||
|---|---|---|---|
| \r\n\r\n I’m least certain about the estimate of 53˚ because it’s furthest outside of the temperatures that were actually measured at a weather station. \r\n
| \r\n | \r\n\r\n I’m least certain about the estimate of 43˚ because it’s far away from any temperatures measured at a weather station. \r\n
| \r\n
| Kalin | \r\nSage | \r\n||
| \r\n
| \r\n\r\n I’m least certain about the estimate of 39˚ because there aren’t any other estimated temperatures near the 39˚ estimate. \r\n
| \r\n\r\n
| \r\n\r\n I’m least certain about the estimate of 37˚ because weather usually moves from west to east, so I’m unsure about estimates on the west side of the map. \r\n
| \r\n
Why do you think the estimated temperature you picked is the one we should be least certain (most unsure) about? Please explain your reasoning.
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\r\nMs. Tevuk’s class is looking at a temperature map with five data points taken from weather station observations. All five weather station observations were made at the same time on the same day. The map also shows some temperatures that were estimated using the weather station observation data (estimated temperatures are in parentheses).
\r\n
Ms. Tevuk asks the students which of the estimated temperatures they are LEAST CERTAIN (MOST UNSURE) about.
\r\nHere are the students’ ideas. (Each student’s estimated temperature choice is in bold to make it easier to find.)
\r\n| Alex | \r\nDelana | \r\n||
|---|---|---|---|
| \r\n\r\n I’m least certain about the estimate of 53˚ because it’s furthest outside of the temperatures that were actually measured at a weather station. \r\n
| \r\n | \r\n\r\n I’m least certain about the estimate of 43˚ because it’s far away from any temperatures measured at a weather station. \r\n
| \r\n
| Kalin | \r\nSage | \r\n||
| \r\n
| \r\n\r\n I’m least certain about the estimate of 39˚ because there aren’t any other estimated temperatures near the 39˚ estimate. \r\n
| \r\n\r\n
| \r\n\r\n I’m least certain about the estimate of 37˚ because weather usually moves from west to east, so I’m unsure about estimates on the west side of the map. \r\n
| \r\n
Why do you think the estimated temperature you picked is the one we should be least certain (most unsure) about? Please explain your reasoning.
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\r\n\r\n
Precipitation symbol = raindrops
\r\n
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Would you change what you selected to wear? Yes or No
\nIf yes, what would you change and why?
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\r\nPrecipitation is shown with three raindrops:
The air moisture and temperature data are shown this way:
Set the map to show the data at 3 pm. Check all cells listed below that have precipitation.
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\nPossible discussion questions:
\n• What was your prediction for the weather in Boston on November 7th at 7am?
• What was your strategy that helped you develop your prediction?
The weather map of the virtual storm below shows temperature and air moisture data at 7pm. Use the relationships you just figured out between air moisture, temperature, and precipitation to try and predict where it will rain at 7pm.
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\r\nHere are the students’ ideas: The rule should be that precipitation happens…
\r\n| Alex | \r\nDelana | \r\n||
|---|---|---|---|
| \r\nwith a warm front coming in because warm air moves in and mixes with cold air, which leads to precipitation. You don’t get precipitation with a cold front because cold air is dry. | \r\n | \r\nwith both cold fronts and warm fronts coming in because in both cases warm air and cold air meet, leading to condensation and precipitation. | \r\n
| Kalin | \r\nSage | \r\n||
| \r\n
| \r\nwith a cold front coming in because it’s usually rainy or snowy when it’s cold out. You don’t get precipitation with a warm front because it’s warm when the sun is shining. | \r\n\r\n
| \r\nafter a cold front has passed by because the cold air the front leaves behind is humid, which leads to precipitation. | \r\n
Why do you think the rule you picked is the best one for predicting precipitation? Please explain your reasoning.
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\r\nHere are the students’ ideas: The rule should be that precipitation happens…
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| \r\nwith a warm front coming in because warm air moves in and mixes with cold air, which leads to precipitation. You don’t get precipitation with a cold front because cold air is dry. | \r\n | \r\nwith both cold fronts and warm fronts coming in because in both cases warm air and cold air meet, leading to condensation and precipitation. | \r\n
| Kalin | \r\nSage | \r\n||
| \r\n
| \r\nwith a cold front coming in because it’s usually rainy or snowy when it’s cold out. You don’t get precipitation with a warm front because it’s warm when the sun is shining. | \r\n\r\n
| \r\nafter a cold front has passed by because the cold air the front leaves behind is humid, which leads to precipitation. | \r\n
Why do you think the rule you picked is the best one for predicting precipitation? Please explain your reasoning.
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Think about developing a similar statement that could be used to determine where it will rain.
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\r\nTry your rule with all of the data sets.
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\r\nThe word represent means to let one thing stand for another. For example, some people use the symbol of a
\r\nheart [] to represent (or stand for) love.
Four students in Ms. Tevuk’s class are figuring out how to represent wind direction both (1) in their computer model that does calculations to predict the weather and (2) on a map the computer model produces to show the weather prediction. The students have different ideas about how to represent wind direction for these two purposes.
\r\nHere are some different options Ms. Tevuk’s students are considering for representing wind direction.
\r\n• Wind direction represented with degree number (between 0 and 360) based on the compass
\r\n
• Wind direction represented with letters based on the compass
\r\n
• Wind direction represented with arrows
\r\n
• Wind direction represented with different colors
\r\n
Here are the students’ ideas:
\r\n| Alex | \r\nDelana | \r\n||
|---|---|---|---|
| \r\n\r\n I think we should use the letters for the computer model because there are only 8 options, so the computer will have simple information to calculate with and it won’t get stuck computing. We can use the arrows on the map because that way you can see which way the wind is going. \r\n
| \r\n | \r\n\r\n Let’s use number of degrees on the computer model because computers do calculations with numbers. I think we should use arrows on the map because they make the pattern of wind direction easy to see. \r\n
| \r\n
| Kalin | \r\nSage | \r\n||
| \r\n
| \r\n\r\n I think we should use number of degrees for both the computer model and the map because computers do calculations with numbers and our map should show what the computer calculated. \r\n
| \r\n\r\n
| \r\n\r\n I think we should use colors for both the computer model and the map. Colors are good for the map because it’s easy to see patterns in different colors. Then it helps to have your computer model and map match, so it makes sense to use colors for the computer model too. \r\n
| \r\n
Which student’s idea do you agree with the most?
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\r\nThe word represent means to let one thing stand for another. For example, some people use the symbol of a
\r\nheart [] to represent (or stand for) love.
Four students in Ms. Tevuk’s class are figuring out how to represent wind direction both (1) in their computer model that does calculations to predict the weather and (2) on a map the computer model produces to show the weather prediction. The students have different ideas about how to represent wind direction for these two purposes.
\r\nHere are some different options Ms. Tevuk’s students are considering for representing wind direction.
\r\n• Wind direction represented with degree number (between 0 and 360) based on the compass
\r\n
• Wind direction represented with letters based on the compass
\r\n
• Wind direction represented with arrows
\r\n
• Wind direction represented with different colors
\r\n
Here are the students’ ideas:
\r\n| Alex | \r\nDelana | \r\n||
|---|---|---|---|
| \r\n\r\n I think we should use the letters for the computer model because there are only 8 options, so the computer will have simple information to calculate with and it won’t get stuck computing. We can use the arrows on the map because that way you can see which way the wind is going. \r\n
| \r\n | \r\n\r\n Let’s use number of degrees on the computer model because computers do calculations with numbers. I think we should use arrows on the map because they make the pattern of wind direction easy to see. \r\n
| \r\n
| Kalin | \r\nSage | \r\n||
| \r\n
| \r\n\r\n I think we should use number of degrees for both the computer model and the map because computers do calculations with numbers and our map should show what the computer calculated. \r\n
| \r\n\r\n
| \r\n\r\n I think we should use colors for both the computer model and the map. Colors are good for the map because it’s easy to see patterns in different colors. Then it helps to have your computer model and map match, so it makes sense to use colors for the computer model too. \r\n
| \r\n
Which student’s idea do you agree with the most?
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\r\n
In this lesson you will explore how air masses interact by watching a wind table. You will also revisit weather station data and radar maps you used in Lesson 1 with some additions: wind data and five more weather stations.
In this activity, you will see how wind blowing from two directions interacts on a Wind Table. Please watch the video below for a demonstration on how a Wind Table maps the movement of air on a gird representing a region of Alaska.
\r\nWind Table
\r\n
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Wind direction is often measured with a weather vane or an air sock. When the wind blows, the weather vane rotates and lines up with the path that the air is flowing. So, wind direction is determined by what direction the wind is coming from. It is measured in degrees (°).
\r\n
The arrows on the model below represent the wind direction at each location. Your challenge using this model is to identify the two air masses and mark a line of cells that splits the map into two parts: one section with the wind coming from the same direction and the other section with the wind coming from a different direction.
\r\nRemember to click Startup and Run. Then,
\r\n- \r\n
- Use gray color to mark where the front is located \r\n
- Use blue to mark air mass 1 \r\n
- Use red color to mark air mass 2 \r\n
You can check your work at any time.
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\r\nAn air mass is a body of air with similar temperature and air moisture content.
\r\nIdentifying air masses and their properties is an important part of the work of atmospheric scientists. On the map you may have noticed a temperature number at the top of the square and an air moisture content number at the bottom of the square.
\r\n
Develop a way to identify the two air masses using temperature and air moisture content values provided on the map you just colored.
\r\n
Temperature: Compare Air Mass #1 to Air Mass #2.
\\nAir Mass 1 is:
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\\n\\rAir Mass #2 over land is:
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Air moisture: Compare Air Mass #2 to Air Mass #1.
\\nAir Mass #2 is:
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\r\n
Comparing these maps think about how air masses affect where it rains.
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How does a front affect where it rains?
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\r\n
Alaska Stations: Interpolated at 7 am
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\r\n
Radar Image for 7 am
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\r\nIf the front to the northwest is colder than 5 degrees than the front to the south, and the air moisture of the front to the south is 7 or above then it will rain in the front to the south.
\r\nThe model below allows you to change the temperature and air moisture content of the wind that enteres the model. Explore this model to see if the rule for rain (above) is obeyed. Also, try to discover if there may be other rules that produces rain and what they might be. Remember to click Setup and Run.
\r\n- \r\n
- The arrowheads show the incoming wind. \r\n
- The temperature and moisture content of the wind are set by the sliders on the South and West sides. \r\n
- When precipitation occurs, it is shown as green circles. The larger the circle, the heavier the rain. \r\n
Read the questions below to help focus your exploration of the model. Hint: start by identifying the fronts. Use city names to describe where fronts and rain occur.
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\r\nHere are the students’ ideas:
\r\n| Alex | \r\nDelana | \r\n||
|---|---|---|---|
| \r\nWe need to run the model longer. The longer you run a computer model the better the prediction will be. | \r\n | \r\nThere’s no way to make a computer model that can predict the weather. Computer models aren’t the real world, so they can’t predict what will happen in the real world. | \r\n
| Kalin | \r\nSage | \r\n||
| \r\n
| \r\nWe should keep working on the rules based on the science of weather prediction. If we get the science right, the model will be accurate. | \r\n\r\n
| \r\nWe should keep working on the rules and testing the model predictions using Alaska weather data. That way we’ll know the model works. | \r\n
Which student's idea do you agree with the most?
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\r\nHere are the students’ ideas:
\r\n| Alex | \r\nDelana | \r\n||
|---|---|---|---|
| \r\nWe need to run the model longer. The longer you run a computer model the better the prediction will be. | \r\n | \r\nThere’s no way to make a computer model that can predict the weather. Computer models aren’t the real world, so they can’t predict what will happen in the real world. | \r\n
| Kalin | \r\nSage | \r\n||
| \r\n
| \r\nWe should keep working on the rules based on the science of weather prediction. If we get the science right, the model will be accurate. | \r\n\r\n
| \r\nWe should keep working on the rules and testing the model predictions using Alaska weather data. That way we’ll know the model works. | \r\n
Why do you think the choice you picked is the best idea for improving the model? Please explain your reasoning.
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\r\nThroughout this unit you have been exploring different aspects of regional weather data. There is one more piece of information we need to figure out before you can make your final prediction for the unit challenge:
\r\nWhat will the weather be in Anchorage 24 hours from now?
\r\n
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Press Setup and Run on the model below. Watch as the arrows trace their path for 11am. Then do the same for 9pm and 7am. Take note of any differences you see between the times.
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So you may be wondering when it’s going to pass through there. Where the front is at the time of the Alaskan Native Youth Olympics (NYO Games) will greatly affect the weather.
\r\nTo best predict where the front will be in 24 hours, you will need to figure out how fast it is moving. This is a calculation of speed (distance divided by time). Once you know both speed and direction of the front, your weather analysis will help you answer the question, “Will it be raining in Anchorage?”
\r\nThe model below allows you to mark the fronts at three times and measure the distance between them. With the time and distance data you can calculate the approximate speed of the front and then calculate where it will be 24 hours after the last measurement. To do this you can use the tools built into this model.
\r\nFirst, mark the fronts.
\r\n• Click Setup and Run and see where the front forms. (Once the front has formed click Run again to turn it off.) See Mr. Neyhard's video for help.
• Click Draw Line and use the mouse to mark the front. (Be sure the mouse stays inside the map while dragging.)
• You can always start over by clicking Clear Last Line or Clear All Lines.
• Repeat this for 9pm and 7am. You can turn Run off or click Setup again if the map gets too dark.
Second, measure the distance between fronts.
\r\n• Turn off Run and click show-distance?. Now, lines that you draw will show their length in kilometers. (You can click Setup to see the map more clearly.)
• Draw a line from one front to the other to measure the distance between them. Start near Fairbanks because the front there will be close to where it will cross Anchorage. Do this for the distance between the first and second front and the second and third front.
Third, calculate the speed of the front. See Mr. Neyhard's video for help.
\r\n• Each set of data is separated by 10 hours.
• Divide the distance between the top and middle front by 10 to get the speed in kilometers per hour.
• Divide the distance between the middle and bottom front by 10 to get the speed in kilometers per hour.
• Average the two speeds by adding them together and then divide by 2.
Finally, calculate the location of the front 24 hours later.
\r\n• Mutliply the average speed by 24 hours to predict where it will be on April 23 at 7am.
• Will the front be on top of Anchorage? Should the NYO Games go on as planned?
You have marked three fronts. Please answer the following questions:
\\n(1) What distance did you measure between the fronts at April 21, 11am and April 21, 9pm?
\\n(2) What distance did you measure between the fronts at April 21, 9pm and April 22, 7am?
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\nIt’s time to put your computational thinking skills to work!
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\r\n| Definition | \r\n\r\n | Computational Thinking Skill | \r\n
|---|---|---|
| \r\n Organizing a large amount of information (data) into smaller more manageable parts. \r\n | \r\n | \r\n\r\n Decomposition \r\nIn Lesson 1, you organized weather station data over a two-day period and radar maps of Alaska every 6 hours to make a prediction. \r\n | \r\n
| \r\n Recognizing that data or information is repeating in a logical (expected) way. \r\n | \r\n | \r\n\r\n Pattern Recognition \r\nIn Lesson 2, you ran the model to see temperature data and patterns of data moving across the map. Before and after each run of the model, you interpolated data. You discovered that warm and cold spots on the map are at times on certain sides, and also you saw these spots change location over time. \r\nIn Lesson 3 and 4, you ran the models to develop a general statement to answer the question \"Where does it rain?\". \r\n | \r\n
| \r\n Estimating an unknown value based on surrounding information. \r\n | \r\n | \r\n\r\n Interpolation \r\nIn Lesson 2, you made best guess estimates of the temperatures that were missing on the map. \r\n | \r\n
| \r\n Following a pattern beyond the known data points. \r\n | \r\n | \r\n\r\n Extrapolation \r\nIn Lesson 2, you predicted future weather based on patterns you observed in the changing temperatures you collected and visualized. \r\n | \r\n
| \r\n Collecting and organizing data to better understand the topic. \r\n | \r\n | \r\n\r\n Data Aggregation \r\nIn Lesson 2, you observed temperature data from a model and organized the data to see the “big picture”. \r\n | \r\n
| \r\n Simplifying data to make it easier to interpret and find patterns. \r\n | \r\n | \r\n\r\n Data Abstraction \r\nIn Lesson 2, you came up with a color scheme for temperature and changed how the data was represented from numbers to temperature categories, and then to colors. \r\n | \r\n
| \r\n Developing a statement of how things work based on the patterns you observed. \r\n | \r\n | \r\n\r\n Rule Abstraction \r\nIn Lesson 3, you made a generic statement to answer the question, \"Where does it rain?\". \r\n | \r\n
| \r\n Looking at the big picture by putting all the components together in the model to see if it works. \r\n | \r\n | \r\n\r\n Model Evaluation \r\nIn Lesson 4 and 5, you ran a model to determine whether a rule was still true in different situations. \r\n | \r\n
| \r\n Modifying a rule to be more precise (exact, careful about details) to work in the model. \r\n | \r\n | \r\n\r\n Rule Refinement \r\nIn Lesson 4 and 5, as you ran the model, you were able to test your rule statements and make changes based on the model. \r\n | \r\n
| \r\n Forecast based on evidence about a future event. \r\n | \r\n | \r\n\r\n Data-based Prediction \r\nIn Lesson 6, you selected data including temperature, air moisture and wind direction to help form a forecast about a future event. \r\n | \r\n
Which skill was the easiest to use? Please explain why.
\\na) Decomposition
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\\nc) Interpolation
\\nd) Extrapolation
\\ne) Data Aggregation
\\nf) Data Abstraction
\\ng) Rule Abstraction
\\nh) Model Evaluation
\\ni) Rule Refinement
\\nj) Data-based Prediction
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\r\nUse all of this knowledge to look at the weather data and make a new prediction for what the weather will be on April 23rd at 7am? You may look back to previous lessons to help you with your prediction.
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How confident are you of your final prediction?
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In this lesson you will explore how air masses interact by setting up a wind table. You will also revisit weather station data and radar maps you used in Lesson 1 with some additions: wind data and five more weather stations. In your Science Notebook, go to Lesson 5 to locate the following information:
0 Map with Additional Weather Stations and Data Tables
0 Alaskan Stations 7 pm Readings
0 Alaskan Stations 7 pm Interpolated Map
0 Alaskan Stations 7 am Interpolated Map
\\n\\n* To print the wind rose, click [here](https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/WindCompass.jpg) to download. \",\"content2\":\"\",\"mediaType\":\"none\",\"mediaCaption\":\"Last, First. \\\"Title of Work.\\\" Year created. Site Title [OR] Publisher. Gallery [OR] Location. http://www.url.com.\",\"mediaURL\":\"\"}}",
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\nOne way wind direction can be measured is with a weather vane or air socks. When the wind blows, the weather vane rotates and lines up with the path the air is flowing. So, wind direction is determined by what direction the wind is blowing and measured in degrees (°).
\n![\"\"](\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/WindCompass.jpg\")
In this activity, you will use a Wind Table to map the movement of air on a grid representing a region in Alaska. Go to your Science Notebooks, Lesson 5, page 21, for further instructions and to record your observations.
\nWind Table
\n![](\"https://precipitatingchange-resources.concord.org/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/WindTunnels.png\")
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Weather scientists refer to these regions as fronts. \\n\\n###Wind Table Directions\\n * **1.Introduce the Wind Table.** Wind is one of the first things that atmospheric scientists look at when investigating the weather, but it can be difficult to understand by just looking at data and maps. A hands-on model is helpful to investigate a phenomenon like the wind.\\n\\n\\n * **2.Assign teams:** Assign research teams a Wind Table position number, either #1 or #2. \\n * **3.Wind tunnel position:** Have students place wind tunnel #1 and wind tunnel #2 according to the diagram in their Science Notebook for their assigned Team #.\\n * **4.Reminders:** Read over the things to keep in mind on page 21 in the Science Notebook, together as a class:\\n * **BE CAREFUL NOT TO PUT YOUR FINGERS NEAR THE FAN**\\n * Graph paper represents a region.\\n * A wind vane can be placed anywhere on the graph paper to determine what direction the wind is coming from.\\n * Record the wind direction by drawing an arrow in the direction the wind vane is pointing. (Recall that wind is always recorded showing the direction the wind is coming from.) If there is not a clear determination where the wind is coming from, then leave the square blank.\\n * Place a Styrofoam ball on the wind table to see the interaction between the two air masses.\\n * **5.Analyze air mass interactions** \\n\\n * Once all of the groups have finished mapping the wind direction, ask the students to determine the boundary of the two air masses by drawing a circle around the different air masses. \\n\\n * Ask the students if there was anywhere on the grid that they either had trouble deciding what direction to draw their arrow. Some students might remark that the wind vane wobbles or spins in the region between the two distinct air masses. Instruct the students to identify the diagonal region between the two air masses and circle this area with a green marker. \\n\\n* **6.Connecting the Wind Table to the interpolated map.** Ask students to compare Alaska Weather Stations: 7 pm Interpolated data with the wind map they created on their Wind Table. Lead a class conversation. See possible Discussion Points below. \\n\",\"content2\":\"\",\"mediaType\":\"none\",\"mediaCaption\":\"Last, First. \\\"Title of Work.\\\" Year created. Site Title [OR] Publisher. 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(Note that scientists also include pressure, but pressure is not covered in this unit.)\\n\\n###Wind Table Demonstration \\nThe compass rose describes the direction the wind is blowing in degrees. Wind coming directly from the South has a direction of 180°, from the East 90°, from the North 360°, etc. Place the fan to the “North” of the weather vane and turn it on. Move the weather vane so that it's at the center of the rose and have students read the wind direction from the rose. Then, move the fan to other locations. Ask students where you should move the fan to get a wind direction of, for example, 180°, 90°, 45°, etc. Move the fan to check their predictions. \\n\\n**Teacher Note:** Wind direction is determined by what direction the wind is coming from. This is a consequence of how it is measured. 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IDENTIFYING AIR MASSES
\nIn Lesson 5 of your Science Notebook on pages 21-23, you have additional data weather station data and maps that show you the direction of the wind. On page 22, you will find a map that shows you the 7 pm reading from the additional weather stations. The arrows on the map represent the wind direction. The data on page 23 of your Science Notebook, \"Weather Stations 7 pm Interpolated\" comes from an interpolation of wind direction across the mainland of Alaska at 7 pm. See map below. Using the map on page 23, draw a line that splits the map into two parts: one section with the wind coming from the same direction and the other section with the wind coming from a different direction. It is your job to determine where you see that change in the wind direction.
\nStrategy for Identifying Two Air Masses:
\n1. Make Sense of the Map:
• Look at each row and see if the arrows change direction as you move across the row.
• Look at each column and see if the arrows change direction as you move down the column.
2. Identify where you are going to place your line.
3. Draw your line on your paper map.
![](\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/Lesson57pmInterpolated.jpg\")
Why did you draw the line there?
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Develop a way to define the two air masses using the temperature and air moisture content values provided on the Alaskan Stations: Interpolated at 7 pm Map.
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Defined Air Masses for the Alaska Mainland at 7 pm
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\\r\\nTemperature: Compare Air Mass #1 to Air Mass #2.
\\r\\nAir Mass #1 is:
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Air moisture: Compare Air Mass #1 to Air Mass #2.
\\r\\nAir Mass #1 is:
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\\r\\nTemperature: Compare Air Mass #2 to Air Mass #1.
\\r\\nAir Mass #2 over land is:
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Air moisture: Compare Air Mass #2 to Air Mass #1.
\\r\\nAir Mass #2 is:
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\nThe region between two different air masses is called a front. Weather scientists are very interested in fronts because they are where the weather can change. Sometimes this change is very sudden.
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\r\n![\"\"](\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/Lesson5_7pmInterpolatedRADARMAPcomparison.jpg\")
Discuss with your research team and write a general statement that answers the question, “How do air masses affect where it rains?\"
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How do air masses affect where it rains?
\",\"defaultAnswer\":\"\",\"required\":false,\"questionType\":\"open_response\",\"hint\":\"• Where is the front? Where is it raining? How do they compare?
• How does the location of the precipitation on the radar map compare to the warm air mass, the cold air mass, and the front?
• What is the air like where it is raining?
Go to page 25 in your Science Notebook and work with you research team to make a prediction for where you think it could rain at 7 am by drawing on the 7 am weather station map in your notebook.
\r\n![](\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/L4_ACT1_Alaska%20Weather%20Stations_7am%20Interpolated.png\")
Alaska Stations: Interpolated at 7 am
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(Responses should center on temperature, moisture and wind direction.)\\n\\n* What have you learned about the wind?\\n\\n* What questions do you still have?\\n\\n* Why do you think the wind is important in understanding the weather?\\n\\n• Are there any connections between the location of the air masses, fronts and precipitation? \\n\\n• Why do you think it is raining in some places and not others?\\n\\n**Teacher note:** Because air is invisible, students tend to have a lot of misconceptions about it. For example, the idea that air is a substance that can move is central to this lesson. It is easy to assume that students understand this concept when they may not. Asking probing questions can help bring their preconceptions to the forefront. The wind table will help students by giving them a concrete experience.\\n\\n###Describing the Front\\n\\n**Teacher note:** Student responses should be in terms of the actual movement of air and not just wind directions. The front is a particularly important area as students should identify it as a place where warm and cold air from the two air masses is coming together or mixing. Students will need a solid understanding of this concept as it will be revisited in the next lesson when they look at how fronts move over a region. \\n\\n###What is Happening at the Front\\n\\n**Teacher Note:** Students will likely notice that there is precipitation outside the area of the front and there are areas along the front that don’t show precipitation. Make note of these discrepancies and remind them that, as we have seen before, we may not have all of the information to explain everything that we see. Some of their observations will be addressed in Lesson 5.\",\"content2\":\"\",\"mediaType\":\"none\",\"mediaCaption\":\"Last, First. \\\"Title of Work.\\\" Year created. Site Title [OR] Publisher. 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Radar Image for 7 am
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\r\nThen, by trying different settings of the temperature and moisture, see if you can make up a rule for what conditions produce precipitation along the front, and on which side of the front the precipitation will occur.
\r\nStart by pressing Setup and Run. As you change temperatures and moisture settings you may want to press Setup occasionally to start fresh. Be sure to discuss what you find with your research team.
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Virtual Model\\n\\n**Objective:** To build students’ rule refinement skills by experimenting with a model to figure out its built-in weather rules. In this model, precipitation falls under a variety of conditions that can be set by changing temperatures and moisture for two air masses. \\n\\nStudents can vary the temperature and moisture of two air masses in order to better understand how interacting air masses create patterns of rain at a front. Through this process, students will come up with an even more robust rule for predicting rain that involves interacting air masses. The specific computational thinking practice highlighted and practiced in this activity is **Rule Refinement**.\\n\\n**1. Class discussion about air mass properties.**Use the Alaska Weather Stations: 7am Interpolated map! [](https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/Lesson5AirMasses1and2.jpg) to remind students of the properties of the air masses in their regional weather system. See Discussion Points below for possible prompts. \\n\\n**2. Set up the model challenge.** \\n\\n* Have students recall the rule they developed to answer the question “How do air masses affect where it rains?” \\n\\n* Students will use the Lesson 5 virtual model to help refine their rule.\\n\\n**3. Exploring the Virtual Model.** \\n\\nIntroduce the task, and give students time to explore the model. Then let them tell you what they discovered. 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Ask students to discuss what they noticed about the model and what they learned from experimenting with it. The model is complex so there can be many viewpoints. The objective of this is to have students feel that they can learn from the model themselves. All observations are valid and up for discussion.\\n\\nPossible topics for discussion:\\n* It may be most valuable to discuss the questions student's answered on this page. An extended discussion could come from the question below.\\n\\n* What do the sizes and colors of the wind arrowheads mean? (The redder the warmer; the bluer the cooler; the larger the more moist; and the smaller the drier.)\\n\\n* Does precipitation fall only near the front? (No, it can fall where the arrowheads converge or come closer together.)\\n\\n* If the south settings and the west setting are the same, is there a front? (No, but the air may still converge.)\\n\\n* Do you see precipitation even where there is no front? What is a rule for it forming? 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\nNow, think about the best way to divide it up. How large should each square of the grid be to get meaningful interpolated temperature estimates across the state?
\nDiscuss this question with your group and then with your class. You may want to consider:
\n- \n
- How big is the area to be covered? (Alaska covers 663,000 square miles.) \n
- How big an area has about the same weather? \n
- How many real temperature measurements are available? \n
- How fast can you compute the interpolated values? \n
Consider two cases:
\n- \n
- You have 10 measurements for all of mainland Alaska, and you will compute the interpolation by hand. \n
- You have 100 measurements for all of mainland Alaska, and a computer program will compute the interpolation. \n
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"New video player ", + "enable_learner_state": true, + "full_window": false, + "has_report_url": false, + "image_url": null, + "name": "Video player (master)", + "native_height": 435, + "native_width": 576, + "no_snapshots": false, + "show_delete_data_button": false, + "thumbnail_url": "", + "customizable": true, + "authorable": true + } + }, + "type": "ManagedInteractive", + "ref_id": "1859-ManagedInteractive", + "linked_interactives": [] + }, + "section": "interactive_box" + } + ] + }, + { + "additional_sections": {}, + "embeddable_display_mode": "stacked", + "id": 308564, + "is_completion": false, + "is_hidden": false, + "layout": "l-6040", + "name": "Question Interactives 2 - Image / Draw Tool / DragNDrop", + "position": 3, + "show_header": true, + "show_info_assessment": true, + "show_interactive": true, + "show_sidebar": false, + "sidebar": null, + "sidebar_title": "Did you know?", + "toggle_info_assessment": false, + "embeddables": [ + { + "embeddable": { + "content": "Image Questions and Draw tool focus. Snapshot, upload, Image URL background, Draw Tool. Exercise resizing of uploaded images.
\r\n\r\n
- Images with no-cors in headers will be given a warning in the interactive with red text.
\r\n- Image Questions will not work in LARA runtime
", + "is_callout": true, + "is_full_width": true, + "is_hidden": false, + "name": "", + "type": "Embeddable::Xhtml", + "ref_id": "272855-Embeddable::Xhtml" + }, + "section": "header_block" + }, + { + "embeddable": { + "name": "", + "url_fragment": null, + "authored_state": "{\"version\":1,\"questionType\":\"image_question\",\"imageFit\":\"shrinkBackgroundToCanvas\",\"imagePosition\":\"center\",\"backgroundSource\":\"upload\",\"prompt\":\"Prompt: QI Image Interactive background source: Upload
\",\"defaultAnswer\":\"Custom default answer\",\"answerPrompt\":\"Here is the answer prompt...
\",\"hint\":\"Here is a hint\",\"stampCollections\":[{\"collection\":\"ngsaObjects\",\"name\":\"NGSA\"}]}", + "is_hidden": false, + "is_full_width": true, + "show_in_featured_question_report": true, + "inherit_aspect_ratio_method": true, + "custom_aspect_ratio_method": null, + "inherit_native_width": true, + "custom_native_width": 576, + "inherit_native_height": true, + "custom_native_height": 435, + "inherit_click_to_play": true, + "custom_click_to_play": false, + "inherit_full_window": true, + "custom_full_window": false, + "inherit_click_to_play_prompt": true, + "custom_click_to_play_prompt": null, + "inherit_image_url": true, + "custom_image_url": null, + "library_interactive": { + "hash": "217c48c2252f0bc168fe35f2297f54777aea07ce", + "data": { + "aspect_ratio_method": "DEFAULT", + "authoring_guidance": "", + "base_url": "https://models-resources.concord.org/question-interactives/version/v1.2.0-pre.1/image-question/", + "click_to_play": false, + "click_to_play_prompt": null, + "description": "", + "enable_learner_state": true, + "full_window": false, + "has_report_url": false, + "image_url": null, + "name": "Image Question (master)", + "native_height": 435, + "native_width": 576, + "no_snapshots": false, + "show_delete_data_button": false, + "thumbnail_url": "", + "customizable": false, + "authorable": true + } + }, + "type": "ManagedInteractive", + "ref_id": "1860-ManagedInteractive", + "linked_interactives": [] + }, + "section": null + }, + { + "embeddable": { + "name": "", + "url_fragment": null, + "authored_state": "{\"version\":1,\"questionType\":\"image_question\",\"imageFit\":\"shrinkBackgroundToCanvas\",\"imagePosition\":\"center\",\"prompt\":\"Question Interactive background source: snapshot
\",\"backgroundSource\":\"snapshot\",\"snapshotTarget\":\"interactive_1424326\",\"stampCollections\":[{\"collection\":\"molecules\",\"name\":\"Molecules\"}],\"answerPrompt\":\"Answer prompt text
\",\"defaultAnswer\":\"Custom default answer text\"}", + "is_hidden": false, + "is_full_width": true, + "show_in_featured_question_report": true, + "inherit_aspect_ratio_method": true, + "custom_aspect_ratio_method": null, + "inherit_native_width": true, + "custom_native_width": 576, + "inherit_native_height": true, + "custom_native_height": 435, + "inherit_click_to_play": true, + "custom_click_to_play": false, + "inherit_full_window": true, + "custom_full_window": false, + "inherit_click_to_play_prompt": true, + "custom_click_to_play_prompt": null, + "inherit_image_url": true, + "custom_image_url": null, + "library_interactive": { + "hash": "217c48c2252f0bc168fe35f2297f54777aea07ce", + "data": { + "aspect_ratio_method": "DEFAULT", + "authoring_guidance": "", + "base_url": "https://models-resources.concord.org/question-interactives/version/v1.2.0-pre.1/image-question/", + "click_to_play": false, + "click_to_play_prompt": null, + "description": "", + "enable_learner_state": true, + "full_window": false, + "has_report_url": false, + "image_url": null, + "name": "Image Question (master)", + "native_height": 435, + "native_width": 576, + "no_snapshots": false, + "show_delete_data_button": false, + "thumbnail_url": "", + "customizable": false, + "authorable": true + } + }, + "type": "ManagedInteractive", + "ref_id": "1861-ManagedInteractive", + "linked_interactives": [ + { + "ref_id": "1864-ManagedInteractive", + "label": "snapshotTarget" + } + ] + }, + "section": null + }, + { + "embeddable": { + "name": "", + "url_fragment": null, + "authored_state": "{\"version\":1,\"questionType\":\"iframe_interactive\",\"imageFit\":\"shrinkBackgroundToCanvas\",\"imagePosition\":\"center\",\"prompt\":\"QI Draw Tool background source: Upload (StAtic)
\",\"backgroundSource\":\"upload\"}", + "is_hidden": false, + "is_full_width": true, + "show_in_featured_question_report": true, + "inherit_aspect_ratio_method": true, + "custom_aspect_ratio_method": null, + "inherit_native_width": true, + "custom_native_width": 576, + "inherit_native_height": true, + "custom_native_height": 435, + "inherit_click_to_play": true, + "custom_click_to_play": false, + "inherit_full_window": true, + "custom_full_window": false, + "inherit_click_to_play_prompt": true, + "custom_click_to_play_prompt": null, + "inherit_image_url": true, + "custom_image_url": null, + "library_interactive": { + "hash": "804f09b3044de3808429dd0e26014dff312ea62b", + "data": { + "aspect_ratio_method": "DEFAULT", + "authoring_guidance": "", + "base_url": "https://models-resources.concord.org/question-interactives/version/v1.2.0-pre.1/drawing-tool/", + "click_to_play": false, + "click_to_play_prompt": null, + "description": "", + "enable_learner_state": true, + "full_window": false, + "has_report_url": false, + "image_url": null, + "name": "Drawing Tool (master)", + "native_height": 435, + "native_width": 576, + "no_snapshots": false, + "show_delete_data_button": false, + "thumbnail_url": "", + "customizable": false, + "authorable": true + } + }, + "type": "ManagedInteractive", + "ref_id": "1862-ManagedInteractive", + "linked_interactives": [] + }, + "section": null + }, + { + "embeddable": { + "name": "", + "url_fragment": null, + "authored_state": "{\"version\":1,\"questionType\":\"iframe_interactive\",\"imageFit\":\"shrinkBackgroundToCanvas\",\"imagePosition\":\"center\",\"backgroundSource\":\"url\",\"prompt\":\"Here is some text (LARA Static)
\",\"backgroundImageUrl\":\"https://building-models-resources.concord.org/Evaporation/water-drop-300-250.png\"}", + "is_hidden": false, + "is_full_width": true, + "show_in_featured_question_report": true, + "inherit_aspect_ratio_method": true, + "custom_aspect_ratio_method": null, + "inherit_native_width": true, + "custom_native_width": 576, + "inherit_native_height": true, + "custom_native_height": 435, + "inherit_click_to_play": true, + "custom_click_to_play": false, + "inherit_full_window": true, + "custom_full_window": false, + "inherit_click_to_play_prompt": true, + "custom_click_to_play_prompt": null, + "inherit_image_url": true, + "custom_image_url": null, + "library_interactive": { + "hash": "804f09b3044de3808429dd0e26014dff312ea62b", + "data": { + "aspect_ratio_method": "DEFAULT", + "authoring_guidance": "", + "base_url": "https://models-resources.concord.org/question-interactives/version/v1.2.0-pre.1/drawing-tool/", + "click_to_play": false, + "click_to_play_prompt": null, + "description": "", + "enable_learner_state": true, + "full_window": false, + "has_report_url": false, + "image_url": null, + "name": "Drawing Tool (master)", + "native_height": 435, + "native_width": 576, + "no_snapshots": false, + "show_delete_data_button": false, + "thumbnail_url": "", + "customizable": false, + "authorable": true + } + }, + "type": "ManagedInteractive", + "ref_id": "1863-ManagedInteractive", + "linked_interactives": [] + }, + "section": null + }, + { + "embeddable": { + "name": "", + "url_fragment": null, + "authored_state": "{\"version\":1,\"scaling\":\"fitWidth\",\"url\":\"https://building-models-resources.concord.org/Evaporation/water-drop-300-250.png\"}", + "is_hidden": false, + "is_full_width": true, + "show_in_featured_question_report": true, + "inherit_aspect_ratio_method": true, + "custom_aspect_ratio_method": "DEFAULT", + "inherit_native_width": true, + "custom_native_width": 576, + "inherit_native_height": true, + "custom_native_height": 435, + "inherit_click_to_play": true, + "custom_click_to_play": false, + "inherit_full_window": true, + "custom_full_window": false, + "inherit_click_to_play_prompt": true, + "custom_click_to_play_prompt": null, + "inherit_image_url": true, + "custom_image_url": null, + "library_interactive": { + "hash": "d3021e60ed42e1e90031676b9db83210e39b5c6a", + "data": { + "aspect_ratio_method": "DEFAULT", + "authoring_guidance": "", + "base_url": "https://models-resources.concord.org/question-interactives/version/v1.2.0-pre.1/image/", + "click_to_play": false, + "click_to_play_prompt": null, + "description": "", + "enable_learner_state": false, + "full_window": false, + "has_report_url": false, + "image_url": null, + "name": "Image Interactive (master)", + "native_height": 435, + "native_width": 576, + "no_snapshots": false, + "show_delete_data_button": false, + "thumbnail_url": "", + "customizable": true, + "authorable": true + } + }, + "type": "ManagedInteractive", + "ref_id": "1864-ManagedInteractive", + "linked_interactives": [] + }, + "section": "interactive_box" + }, + { + "embeddable": { + "name": "", + "url_fragment": null, + "authored_state": "{\"version\":1,\"questionType\":\"iframe_interactive\",\"draggingAreaPrompt\":\"Drag following items:\",\"canvasWidth\":392,\"canvasHeight\":342,\"initialState\":{\"itemPositions\":{\"5fdd7ef5-46e9-4be8-b64b-d9d17a031867\":{\"left\":17,\"top\":42},\"03f05474-23d9-4812-93db-f6654b4ccc8e\":{\"left\":96,\"top\":40},\"8c62252c-f90a-4625-aef0-d262e8a639f2\":{\"left\":193,\"top\":42},\"199c09d6-eef9-4753-bfff-22c53b54e238\":{\"left\":280,\"top\":38}}},\"prompt\":\"Drag the cats to the right positions
\",\"backgroundImageUrl\":\"https://placekitten.com/392/343\",\"draggableItems\":[{\"id\":\"5fdd7ef5-46e9-4be8-b64b-d9d17a031867\",\"imageUrl\":\"https://placekitten.com/50/60\"},{\"id\":\"03f05474-23d9-4812-93db-f6654b4ccc8e\",\"imageUrl\":\"https://placekitten.com/50/61\"},{\"id\":\"8c62252c-f90a-4625-aef0-d262e8a639f2\",\"imageUrl\":\"https://placekitten.com/50/62\"},{\"id\":\"199c09d6-eef9-4753-bfff-22c53b54e238\",\"imageUrl\":\"https://placekitten.com/50/65\"}]}", + "is_hidden": false, + "is_full_width": true, + "show_in_featured_question_report": true, + "inherit_aspect_ratio_method": true, + "custom_aspect_ratio_method": "DEFAULT", + "inherit_native_width": true, + "custom_native_width": 576, + "inherit_native_height": true, + "custom_native_height": 435, + "inherit_click_to_play": true, + "custom_click_to_play": false, + "inherit_full_window": true, + "custom_full_window": false, + "inherit_click_to_play_prompt": true, + "custom_click_to_play_prompt": null, + "inherit_image_url": true, + "custom_image_url": null, + "library_interactive": { + "hash": "c6fe379add61f7d2005b69a765d841b8c2fb9483", + "data": { + "aspect_ratio_method": "DEFAULT", + "authoring_guidance": "", + "base_url": "https://models-resources.concord.org/question-interactives/version/v1.2.0-pre.1/drag-and-drop/", + "click_to_play": false, + "click_to_play_prompt": null, + "description": "", + "enable_learner_state": true, + "full_window": false, + "has_report_url": false, + "image_url": null, + "name": "Drag and Drop (Master)", + "native_height": 435, + "native_width": 576, + "no_snapshots": false, + "show_delete_data_button": true, + "thumbnail_url": "", + "customizable": true, + "authorable": true + } + }, + "type": "ManagedInteractive", + "ref_id": "1865-ManagedInteractive", + "linked_interactives": [] + }, + "section": "interactive_box" + } + ] + }, + { + "additional_sections": {}, + "embeddable_display_mode": "stacked", + "id": 308565, + "is_completion": false, + "is_hidden": false, + "layout": "l-full-width", + "name": "Question Interactives 3 - Graph and Carousel", + "position": 4, + "show_header": true, + "show_info_assessment": true, + "show_interactive": true, + "show_sidebar": false, + "sidebar": null, + "sidebar_title": "Did you know?", + "toggle_info_assessment": false, + "embeddables": [ + { + "embeddable": { + "content": "Testing linked interactives with vortex and graph interactives
\r\n- Make sure to test navigation of carousel with keyboard
\r\n- Check reports for carousel in portal
\r\n- Each version of vortex interactive should be checked
\r\n- There is currently a bug in the graph interactive it seems
", + "is_callout": true, + "is_full_width": true, + "is_hidden": false, + "name": "", + "type": "Embeddable::Xhtml", + "ref_id": "272856-Embeddable::Xhtml" + }, + "section": "header_block" + }, + { + "embeddable": { + "name": "", + "url_fragment": null, + "authored_state": "{\"version\":2,\"questionType\":\"iframe_interactive\",\"subinteractives\":[{\"id\":\"60d92b9d-01e5-424e-9172-f2c18b1c60f0\",\"authoredState\":{\"version\":1,\"questionType\":\"open_response\",\"prompt\":\"Open response prompt
\",\"hint\":\"hint for OR
\",\"required\":true},\"libraryInteractiveId\":\"open-response\"},{\"id\":\"18b87d6d-8bfd-48a9-a121-e16b8b7c824c\",\"authoredState\":{\"version\":1,\"questionType\":\"iframe_interactive\",\"blanks\":[{\"id\":\"[blank-1]\",\"size\":20,\"matchTerm\":\"blank\"}],\"prompt\":\"Fill in the [blank-1]
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\",\"enableCheckAnswer\":true,\"customFeedback\":true,\"required\":true},\"libraryInteractiveId\":\"multiple-choice\"},{\"libraryInteractiveId\":\"video-player\",\"authoredState\":{\"version\":1,\"questionType\":\"iframe_interactive\",\"videoUrl\":\"https://project-resources.concord.org/test-project/Big_Buck_Bunny_360_10s_1MB.mp4\\n\",\"poster\":\"https://placekitten.com/600/400\",\"prompt\":\"Some small description\",\"credit\":\"Some long credits. Some long credits. Some long credits. Some long credits. Some long credits. Some long credits. Some long credits. Some long credits. Some long credits. Some long credits. Some long credits. Some long credits. Some long credits. Some long credits. Some long credits. \",\"creditLink\":\"https://concord.org\",\"creditLinkDisplayText\":\"Concord Home\"},\"id\":\"90df0a51-e5f8-44b1-8a30-ac713a5affd6\",\"navImageUrl\":\"\",\"navImageAltText\":\"\"},{\"libraryInteractiveId\":\"image\",\"authoredState\":{\"version\":1,\"scaling\":\"fitWidth\",\"url\":\"https://building-models-resources.concord.org/Evaporation/water-drop-300-250.png\",\"highResUrl\":\"https://placekitten.com/800/1200\",\"altText\":\"Some custom alt text in here\",\"caption\":\"Here is a beautiful flower which looks more like a tree once you zoom into it\",\"credit\":\"Credits out to CC\",\"creditLink\":\"https://concord.org\",\"creditLinkDisplayText\":\"Concord Home\",\"allowLightbox\":true},\"id\":\"85c2fa2d-5ac6-4024-80b2-c3ed71830601\",\"navImageUrl\":\"\",\"navImageAltText\":\"\"}],\"prompt\":\"QI Carousel Interactive. Contains 5 Interactives (Multiple Choice, Open Response, Fill-In-The-Blank, Image, Video) (Static)
\",\"hint\":\"\",\"required\":false}", + "is_hidden": false, + "is_full_width": true, + "show_in_featured_question_report": true, + "inherit_aspect_ratio_method": true, + "custom_aspect_ratio_method": "DEFAULT", + "inherit_native_width": true, + "custom_native_width": 576, + "inherit_native_height": true, + "custom_native_height": 435, + "inherit_click_to_play": true, + "custom_click_to_play": false, + "inherit_full_window": true, + "custom_full_window": false, + "inherit_click_to_play_prompt": true, + "custom_click_to_play_prompt": null, + "inherit_image_url": true, + "custom_image_url": null, + "library_interactive": { + "hash": "0389a9062aaab9afc5c21478d5cf85b468418842", + "data": { + "aspect_ratio_method": "DEFAULT", + "authoring_guidance": "", + "base_url": "https://models-resources.concord.org/question-interactives/version/v1.2.0-pre.1/carousel/", + "click_to_play": false, + "click_to_play_prompt": null, + "description": "", + "enable_learner_state": true, + "full_window": false, + "has_report_url": false, + "image_url": null, + "name": "Carousel Interactive (Master)", + "native_height": 435, + "native_width": 576, + "no_snapshots": false, + "show_delete_data_button": true, + "thumbnail_url": "", + "customizable": true, + "authorable": true + } + }, + "type": "ManagedInteractive", + "ref_id": "1866-ManagedInteractive", + "linked_interactives": [] + }, + "section": null + }, + { + "embeddable": { + "name": "", + "url_fragment": null, + "authored_state": "{\"version\":\"1.0\",\"experimentId\":\"e431af00-5ef9-44f8-a887-c76caa6ddde1\"}", + "is_hidden": false, + "is_full_width": true, + "show_in_featured_question_report": true, + "inherit_aspect_ratio_method": true, + "custom_aspect_ratio_method": "DEFAULT", + "inherit_native_width": true, + "custom_native_width": 576, + "inherit_native_height": true, + "custom_native_height": 435, + "inherit_click_to_play": true, + "custom_click_to_play": false, + "inherit_full_window": true, + "custom_full_window": false, + "inherit_click_to_play_prompt": true, + "custom_click_to_play_prompt": null, + "inherit_image_url": true, + "custom_image_url": null, + "library_interactive": { + "hash": "7b8d169a7f6315d6f724245c76048ddcc493964a", + "data": { + "aspect_ratio_method": "DEFAULT", + "authoring_guidance": "", + "base_url": "https://models-resources.concord.org/vortex/version/v1.3.0/lara-app/index.html", + "click_to_play": true, + "click_to_play_prompt": "", + "description": "WATERS LARA app (production)", + "enable_learner_state": true, + "full_window": false, + "has_report_url": false, + "image_url": "https://www.thelabradorsite.com/wp-content/uploads/2016/05/6t.jpg", + "name": "Monitor My World v1.3.0", + "native_height": 435, + "native_width": 576, + "no_snapshots": false, + "show_delete_data_button": false, + "thumbnail_url": "", + "customizable": true, + "authorable": true + } + }, + "type": "ManagedInteractive", + "ref_id": "1867-ManagedInteractive", + "linked_interactives": [] + }, + "section": 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They have different ideas for what the rule should be.\u003C/p\u003E\n\u003Cp\u003EHere are the students\u0026rsquo; ideas: The rule should be that precipitation happens\u0026hellip;\u003C/p\u003E\n\u003Ctable cellpadding=\"30\"\u003E\n\u003Ctbody\u003E\n\u003Ctr\u003E\n\u003Cth colspan=\"2\"\u003E\u003Cstrong\u003EAlex\u003C/strong\u003E\u003C/th\u003E\n\u003Cth colspan=\"2\"\u003E\u003Cstrong\u003EDelana\u003C/strong\u003E\u003C/th\u003E\n\u003C/tr\u003E\n\u003Ctr\u003E\n\u003Ctd width=\"88\"\u003E\u003Cimg src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/Alex4.png\" width=\"72\" height=\"90\" align=\"center\" hspace=\"10\" vspace=\"10\" /\u003E\u003C/td\u003E\n\u003Ctd style=\"padding: 10px;\" width=\"350\"\u003E\u003Cstrong\u003Ewith a warm front coming in\u003C/strong\u003E because warm air moves in and mixes with cold air, which leads to precipitation. 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We suggest teachers review the information below and think about ways to scaffold students toward developing knowledge and practice as appropriate for their classes. Also, we recommend that during the first implementation of the probe, teachers scaffold students to focus on students\u2019 own ideas about this problem. By discussing the different options, students can engage in productive talk related to the different response patterns, priming them to look for productive patterns to associate with precipitation in the upcoming lessons. \\n\\nDuring the ensuing two lessons and the second implementation of the probe, students should be able to use the data from the virtual storm to identify the patterns of temperature, humidity, and movement that are associated with precipitation.\\n\\nThis assessment probe is designed to assess and scaffold students in thinking and talking about how patterns of data (i.e., temperature, humidity, and air movement) are associated with precipitation in a location. To keep things simple, we only focus on two types of fronts: cold fronts and warm fronts. Both types of fronts can be associated with precipitation. Identifying patterns associated with precipitation is an example of the computational thinking practice of **Pattern Recognition**. Once patterns associated with precipitation are identified, they can be used in conjunction with data to make a **Data-based Prediction**, which is what Ms. Tevuk\u2019s students are trying to do in the scenario for this assessment probe. **Data-based Prediction** involves identifying patterns and trends within and across groups of data/information as seen in the observable world. The patterns of data associated with precipitation in turn can be used to create rules for the computer model in a process of **Rule Abstraction**. **Rule abstraction** involves creating a general statement derived from exploring patterns in data in order to establish rule(s) or principles. In other words, if you know the patterns of variable values associated with precipitation, you can use those patterns to write rules for predicting precipitation.\\n\\nAs a **cold front** moves into an area, the heavier cool air pushes under the lighter warm air. The air behind a cold front is colder and usually drier than the warm air in front. The warm air in front becomes cooler as it is pushed upward by the entering cold air. If the warm air is humid enough, the water vapor it contains will condense into clouds as it rises, and precipitation may fall. \\n\u003Cimg src=\\\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/L4L5AssessmentTeacherGuideImage2.png\\\" width=\\\"850\\\" height=\\\"180\\\" /\u003E\\n \\n\\nWhen a **warm front** moves into an area, warm air moves above a cool air mass. As the warm air rises, it condenses, often forming clouds and precipitation. \\n\u003Cimg src=\\\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/L4L5AssessmentTeacherGuideImage1.png\\\" width=\\\"850\\\" height=\\\"180\\\" /\u003E\\n\\nThe assessment is situated in the unit context to provide an opportunity for students to make sense about patterns when reasoning about air masses, fronts, and precipitation. In this assessment, one of the responses is scientifically correct while the other responses that relate to some informal ideas about weather that students may hold. \",\"content2\":\"\",\"mediaType\":\"none\",\"mediaCaption\":\"Last, First. \\\"Title of Work.\\\" Year created. Site Title [OR] Publisher. 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Students may associate sun with warm, and rain and snow with cold. Based on that experience, they may think that a cold front is connected to precipitation.\\n\\nStudents who choose Kalin\u2019s response could benefit from having experiences that challenge their simple association idea. For example, looking at weather maps that show warmer air often has more moisture in it and colder air is often drier can help these students develop understanding that relationships might not be as simple as they think. Students who choose Kalin\u2019s response may not think about weather as something that happens with matter. Instead, they may just think of weather in terms of the actions of natural \\\"actors\\\" (e.g., the sun makes it warm, the wind makes it cold). These students could use help in learning that air masses are matter (they are made up of molecules and have mass). If we didn\u2019t have air masses made of matter on Earth, then we wouldn\u2019t have weather. You might talk with students about concrete examples that they can extend to think about air masses as entities made of stuff \u2013 for example, they could compare an empty balloon, a balloon filled with warm air, and a balloon filled with cold air. There is very little stuff (matter or molecules of air) in the empty balloon, while there is more stuff (matter) in the balloons filled with warm and cold air.\\n\\n###Middle Level \\n\u2022\\t**Both Alex\u2019s response (precipitation occurs with a warm front coming in)** and **Sage\u2019s response (precipitation occurs after a cold front has passed by an area)** suggest that they are aware that precipitation is associated with bodies of air moving and with the different conditions in those bodies of air (i.e., temperature, levels of humidity). However, both Sage\u2019s and Alex\u2019s ideas include some incorrect patterns that lead to problematic rules. \\n\\n\u2022\\t**Alex** thinks that cold air and warm air mixing causes precipitation. However, warm and cold air masses don\u2019t mix very readily, and it is instead actually warm air rising, expanding, and condensing that generally leads to precipitation. In addition, while Alex knows that cold fronts can be drier than warm fronts, that doesn\u2019t mean that there won\u2019t be any precipitation with cold fronts. Precipitation can occur with a cold front when warm air is pushed up, expands, and condenses.\\n\\nStudents who choose Alex\u2019s response could benefit from working with data to observe the following patterns: (1) precipitation can occur with a cold front and (2) fronts do not necessarily mix.\\n\\n\u2022\\t**Sage** thinks that cold air is humid, which leads to condensation and precipitation. However, warm air masses often have a higher level of humidity compared with cold air masses. It can be confusing that condensation occurs with rising, expanding, and cooling. The unit does not go into this in depth, however. For students who choose Sage\u2019s response, it is probably sufficient here to scaffold experiences with data and virtual storm showing the general pattern of warm air masses having higher levels of humidity than cool air masses.\\n\\n\u2022\\tStudents who choose Alex or Sage\u2019s response can also benefit from discussion and emphasis on the importance of getting the rule right (enough) in order to create a computational model that works. The students working on their weather model will not be able to predict weather with any consistency or accuracy if there is a big problem with the rule (algorithm) they have written into their computer model. \\n\\n###More Formal Idea\\n\u2022\\t**Delana\u2019s response (precipitation occurs with both cold fronts and warm fronts coming in)** is the best answer. Delana\u2019s explanation does not include a more complete mechanistic sequence involving cold air pushing warm air up; warm air rising, expanding, and condensing; and precipitation occurring as a result. This is because the Precipitating Change curriculum simplifies weather phenomena by emphasizing important patterns and de-emphasizing complicated mechanisms. This focus allows the curriculum to scaffold students in connecting observed patterns with rules that can be used to create predictive weather forecasting computer models. Delana\u2019s response both recognizes that weather fronts are made of air (matter) and demonstrates recognition of the correct pattern of conditions in air masses (temperatures, levels of humidity) associated with precipitation forming. \",\"content2\":\"\",\"mediaType\":\"none\",\"mediaCaption\":\"Last, First. \\\"Title of Work.\\\" Year created. Site Title [OR] Publisher. 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They have different ideas for what the rule should be.\u003C/p\u003E\n\u003Cp\u003EHere are the students\u0026rsquo; ideas: The rule should be that precipitation happens\u0026hellip;\u003C/p\u003E\n\u003Ctable cellpadding=\"30\"\u003E\n\u003Ctbody\u003E\n\u003Ctr\u003E\n\u003Cth colspan=\"2\"\u003E\u003Cstrong\u003EAlex\u003C/strong\u003E\u003C/th\u003E\n\u003Cth colspan=\"2\"\u003E\u003Cstrong\u003EDelana\u003C/strong\u003E\u003C/th\u003E\n\u003C/tr\u003E\n\u003Ctr\u003E\n\u003Ctd width=\"88\"\u003E\u003Cimg src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/Alex4.png\" width=\"72\" height=\"90\" align=\"center\" hspace=\"10\" vspace=\"10\" /\u003E\u003C/td\u003E\n\u003Ctd style=\"padding: 10px;\" width=\"350\"\u003E\u003Cstrong\u003Ewith a warm front coming in\u003C/strong\u003E because warm air moves in and mixes with cold air, which leads to precipitation. You don\u0026rsquo;t get precipitation with a cold front because cold air is dry.\u003C/td\u003E\n\u003Ctd width=\"88\"\u003E\u003Cimg src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/Delana4.png\" width=\"70\" height=\"90\" align=\"center\" hspace=\"10\" vspace=\"10\" /\u003E\u003C/td\u003E\n\u003Ctd style=\"padding: 10px;\" width=\"350\"\u003E\u003Cstrong\u003Ewith both cold fronts and warm fronts coming in\u003C/strong\u003E because in both cases warm air and cold air meet, leading to condensation and precipitation.\u003C/td\u003E\n\u003C/tr\u003E\n\u003C/tbody\u003E\n\u003Ctbody\u003E\n\u003Ctr\u003E\n\u003Cth colspan=\"2\"\u003E\u003Cstrong\u003EKalin\u003C/strong\u003E\u003C/th\u003E\n\u003Cth colspan=\"2\"\u003E\u003Cstrong\u003ESage\u003C/strong\u003E\u003C/th\u003E\n\u003C/tr\u003E\n\u003Ctr\u003E\n\u003Ctd width=\"88\"\u003E\n\u003Cp\u003E\u003Cimg src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/Kalin6.png\" width=\"72\" height=\"90\" align=\"center\" hspace=\"10\" vspace=\"10\" /\u003E\u003C/p\u003E\n\u003C/td\u003E\n\u003Ctd style=\"padding: 10px;\" width=\"350\"\u003E\u003Cstrong\u003Ewith a cold front coming in\u003C/strong\u003E because it\u0026rsquo;s usually rainy or snowy when it\u0026rsquo;s cold out. You don\u0026rsquo;t get precipitation with a warm front because it\u0026rsquo;s warm when the sun is shining.\u003C/td\u003E\n\u003Ctd width=\"88\"\u003E\n\u003Cp\u003E\u003Cimg src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/Sage2.png\" width=\"72\" height=\"90\" align=\"center\" hspace=\"8\" vspace=\"8\" /\u003E\u003C/p\u003E\n\u003C/td\u003E\n\u003Ctd style=\"padding: 10px;\" width=\"350\"\u003E\u003Cstrong\u003Eafter a cold front has passed by\u003C/strong\u003E because the cold air the front leaves behind is humid, which leads to precipitation.\u003C/td\u003E\n\u003C/tr\u003E\n\u003C/tbody\u003E\n\u003C/table\u003E", + "is_callout": false, + "is_full_width": true, + "is_hidden": false, + "name": "", + "type": "Embeddable::Xhtml", + "ref_id": "272932-Embeddable::Xhtml" + }, + "section": "header_block" + }, { + "embeddable": { + "name": "Multiple Choice Question element", + "url_fragment": null, + "authored_state": "{\"version\":1,\"questionType\":\"multiple_choice\",\"choices\":[{\"id\":\"1\",\"content\":\"Alex\",\"correct\":false,\"choiceFeedback\":\"\"},{\"id\":\"2\",\"content\":\"Delana\",\"correct\":false,\"choiceFeedback\":\"\"},{\"id\":\"3\",\"content\":\"Kalin\",\"correct\":false,\"choiceFeedback\":\"\"},{\"id\":\"4\",\"content\":\"Sage\",\"correct\":false,\"choiceFeedback\":\"\"}],\"layout\":\"vertical\",\"prompt\":\"\u003Cp\u003EWhich student\u0026rsquo;s idea do you agree with the most?\u003C/p\u003E\"}", + "is_hidden": false, + "is_full_width": true, + "show_in_featured_question_report": true, + "inherit_aspect_ratio_method": true, + "custom_aspect_ratio_method": null, + "inherit_native_width": true, + "custom_native_width": 576, + "inherit_native_height": true, + "custom_native_height": 435, + "inherit_click_to_play": true, + "custom_click_to_play": false, + "inherit_full_window": true, + "custom_full_window": false, + "inherit_click_to_play_prompt": true, + "custom_click_to_play_prompt": null, + "inherit_image_url": true, + "custom_image_url": null, + "library_interactive": { + "hash": "98f3d10aa7f2fce6bdeb0ecda339fa56dc80b37c", + "data": { + "aspect_ratio_method": "DEFAULT", + "authoring_guidance": "", + "base_url": "https://models-resources.concord.org/question-interactives/version/v1.1.0/multiple-choice/", + "click_to_play": false, + "click_to_play_prompt": null, + "description": "", + "enable_learner_state": true, + "full_window": false, + "has_report_url": false, + "image_url": null, + "name": "Multiple Choice", + "native_height": 435, + "native_width": 576, + "no_snapshots": false, + "show_delete_data_button": false, + "thumbnail_url": "", + "customizable": true, + "authorable": true + } + }, + "type": "ManagedInteractive", + "ref_id": "1946-ManagedInteractive", + "linked_interactives": [] + }, + "section": null + }, { + "embeddable": { + "plugin": { + "description": null, + "author_data": "{\"tipType\":\"windowShade\",\"windowShade\":{\"windowShadeType\":\"teacherTip\",\"layout\":\"mediaLeft\",\"initialOpenState\":true,\"content\":\"###Pre-Assessment Implementation\\n*Lesson 4, Opening: What Are the Rules for Fronts and Precipitation? Pre-Assessment*\\nDuring the pre-assessment, each student will view the probe and make an individual choice. The request for explanation will only be on the post-assessment. After students make an individual choice for the pre-assessment, the teacher can lead discussion including, for example, a pair/share opportunity and/or full class discussion. \\n\\nAt this time, encourage students to share and discuss their ideas and reasons without indicating that any one answer is better or worse. Let the students know that they should keep thinking about this question and that the class will return to it at the end of the next lesson (Lesson 5).\",\"content2\":\"\",\"mediaType\":\"none\",\"mediaCaption\":\"Last, First. \\\"Title of Work.\\\" Year created. Site Title [OR] Publisher. Gallery [OR] Location. http://www.url.com.\",\"mediaURL\":\"\"}}", + "approved_script_label": "teacherEditionTips", + "component_label": "windowShade", + "approved_script": { + "name": "Teacher Edition", + "url": "https://teacher-edition-tips-plugin.concord.org/version/v3.6.0/plugin.js", + "label": "teacherEditionTips", + "description": "This plugin provides Teacher Edition components", + "version": 3, + "json_url": "https://teacher-edition-tips-plugin.concord.org/version/v3.6.0/manifest.json", + "authoring_metadata": "{\"components\":[{\"label\":\"windowShade\",\"name\":\"Window Shades\",\"scope\":\"embeddable\",\"guiAuthoring\":true},{\"label\":\"sideTip\",\"name\":\"Side Tips\",\"scope\":\"embeddable\",\"guiAuthoring\":true},{\"label\":\"questionWrapper\",\"name\":\"Question Wrapper\",\"scope\":\"embeddable-decoration\",\"decorates\":[\"Embeddable::MultipleChoice\",\"Embeddable::OpenResponse\",\"Embeddable::ImageQuestion\",\"ManagedInteractive\",\"MwInteractive\",\"ImageInteractive\",\"VideoInteractive\"],\"guiAuthoring\":true,\"guiPreview\":true}]}" + } + }, + "is_hidden": false, + "is_full_width": true, + "type": "Embeddable::EmbeddablePlugin", + "ref_id": "4239-Embeddable::EmbeddablePlugin" + }, + "section": null + }, { + "embeddable": { + "plugin": { + "description": null, + "author_data": "{\"tipType\":\"windowShade\",\"windowShade\":{\"windowShadeType\":\"theoryAndBackground\",\"layout\":\"mediaLeft\",\"initialOpenState\":true,\"content\":\"###Computational Thinking Concepts and Practices:\\n* Pattern Recognition\\n* Data-based Prediction\\n* Rule Abstraction\\n\\n###What is the Purpose of this Assessment Probe?\\nThe following information provides background for teachers. We suggest teachers review the information below and think about ways to scaffold students toward developing knowledge and practice as appropriate for their classes. Also, we recommend that during the first implementation of the probe, teachers scaffold students to focus on students\u2019 own ideas about this problem. By discussing the different options, students can engage in productive talk related to the different response patterns, priming them to look for productive patterns to associate with precipitation in the upcoming lessons. \\n\\nDuring the ensuing two lessons and the second implementation of the probe, students should be able to use the data from the virtual storm to identify the patterns of temperature, humidity, and movement that are associated with precipitation.\\n\\nThis assessment probe is designed to assess and scaffold students in thinking and talking about how patterns of data (i.e., temperature, humidity, and air movement) are associated with precipitation in a location. To keep things simple, we only focus on two types of fronts: cold fronts and warm fronts. Both types of fronts can be associated with precipitation. Identifying patterns associated with precipitation is an example of the computational thinking practice of **Pattern Recognition**. Once patterns associated with precipitation are identified, they can be used in conjunction with data to make a **Data-based Prediction**, which is what Ms. Tevuk\u2019s students are trying to do in the scenario for this assessment probe. **Data-based Prediction** involves identifying patterns and trends within and across groups of data/information as seen in the observable world. The patterns of data associated with precipitation in turn can be used to create rules for the computer model in a process of **Rule Abstraction**. **Rule abstraction** involves creating a general statement derived from exploring patterns in data in order to establish rule(s) or principles. In other words, if you know the patterns of variable values associated with precipitation, you can use those patterns to write rules for predicting precipitation.\\n\\nAs a **cold front** moves into an area, the heavier cool air pushes under the lighter warm air. The air behind a cold front is colder and usually drier than the warm air in front. The warm air in front becomes cooler as it is pushed upward by the entering cold air. If the warm air is humid enough, the water vapor it contains will condense into clouds as it rises, and precipitation may fall. \\n\u003Cimg src=\\\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/L4L5AssessmentTeacherGuideImage2.png\\\" width=\\\"850\\\" height=\\\"180\\\" /\u003E\\n \\n\\nWhen a **warm front** moves into an area, warm air moves above a cool air mass. As the warm air rises, it condenses, often forming clouds and precipitation. \\n\u003Cimg src=\\\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/L4L5AssessmentTeacherGuideImage1.png\\\" width=\\\"850\\\" height=\\\"180\\\" /\u003E\\n\\nThe assessment is situated in the unit context to provide an opportunity for students to make sense about patterns when reasoning about air masses, fronts, and precipitation. In this assessment, one of the responses is scientifically correct while the other responses that relate to some informal ideas about weather that students may hold. \",\"content2\":\"\",\"mediaType\":\"none\",\"mediaCaption\":\"Last, First. \\\"Title of Work.\\\" Year created. Site Title [OR] Publisher. Gallery [OR] Location. http://www.url.com.\",\"mediaURL\":\"\"}}", + "approved_script_label": "teacherEditionTips", + "component_label": "windowShade", + "approved_script": { + "name": "Teacher Edition", + "url": "https://teacher-edition-tips-plugin.concord.org/version/v3.6.0/plugin.js", + "label": "teacherEditionTips", + "description": "This plugin provides Teacher Edition components", + "version": 3, + "json_url": "https://teacher-edition-tips-plugin.concord.org/version/v3.6.0/manifest.json", + "authoring_metadata": "{\"components\":[{\"label\":\"windowShade\",\"name\":\"Window Shades\",\"scope\":\"embeddable\",\"guiAuthoring\":true},{\"label\":\"sideTip\",\"name\":\"Side Tips\",\"scope\":\"embeddable\",\"guiAuthoring\":true},{\"label\":\"questionWrapper\",\"name\":\"Question Wrapper\",\"scope\":\"embeddable-decoration\",\"decorates\":[\"Embeddable::MultipleChoice\",\"Embeddable::OpenResponse\",\"Embeddable::ImageQuestion\",\"ManagedInteractive\",\"MwInteractive\",\"ImageInteractive\",\"VideoInteractive\"],\"guiAuthoring\":true,\"guiPreview\":true}]}" + } + }, + "is_hidden": false, + "is_full_width": true, + "type": "Embeddable::EmbeddablePlugin", + "ref_id": "4240-Embeddable::EmbeddablePlugin" + }, + "section": null + }, { + "embeddable": { + "plugin": { + "description": null, + "author_data": "{\"tipType\":\"windowShade\",\"windowShade\":{\"windowShadeType\":\"discussionPoints\",\"layout\":\"mediaLeft\",\"initialOpenState\":true,\"content\":\"###What Are Common Student Ideas and What Supports Could Help Students?\\nBelow are some issues to consider in assessing students\u2019 ideas, and some suggestions of ways to support students in developing more formal reasoning about patterns associated with fronts and precipitation.\\n\\n###Less Formal Ideas\\n\u2022\\t**Kalin\u2019s response (precipitation with a cold front coming in)** suggests that Kalin may just be thinking about patterns of familiar things going together (cold and wet, warm and sunny) rather than thinking about patterns associated with different types of air masses interacting with one another. Students may associate sun with warm, and rain and snow with cold. Based on that experience, they may think that a cold front is connected to precipitation.\\n\\nStudents who choose Kalin\u2019s response could benefit from having experiences that challenge their simple association idea. For example, looking at weather maps that show warmer air often has more moisture in it and colder air is often drier can help these students develop understanding that relationships might not be as simple as they think. Students who choose Kalin\u2019s response may not think about weather as something that happens with matter. Instead, they may just think of weather in terms of the actions of natural \\\"actors\\\" (e.g., the sun makes it warm, the wind makes it cold). These students could use help in learning that air masses are matter (they are made up of molecules and have mass). If we didn\u2019t have air masses made of matter on Earth, then we wouldn\u2019t have weather. You might talk with students about concrete examples that they can extend to think about air masses as entities made of stuff \u2013 for example, they could compare an empty balloon, a balloon filled with warm air, and a balloon filled with cold air. There is very little stuff (matter or molecules of air) in the empty balloon, while there is more stuff (matter) in the balloons filled with warm and cold air.\\n\\n###Middle Level \\n\u2022\\t**Both Alex\u2019s response (precipitation occurs with a warm front coming in)** and **Sage\u2019s response (precipitation occurs after a cold front has passed by an area)** suggest that they are aware that precipitation is associated with bodies of air moving and with the different conditions in those bodies of air (i.e., temperature, levels of humidity). However, both Sage\u2019s and Alex\u2019s ideas include some incorrect patterns that lead to problematic rules. \\n\\n\u2022\\t**Alex** thinks that cold air and warm air mixing causes precipitation. However, warm and cold air masses don\u2019t mix very readily, and it is instead actually warm air rising, expanding, and condensing that generally leads to precipitation. In addition, while Alex knows that cold fronts can be drier than warm fronts, that doesn\u2019t mean that there won\u2019t be any precipitation with cold fronts. Precipitation can occur with a cold front when warm air is pushed up, expands, and condenses.\\n\\nStudents who choose Alex\u2019s response could benefit from working with data to observe the following patterns: (1) precipitation can occur with a cold front and (2) fronts do not necessarily mix.\\n\\n\u2022\\t**Sage** thinks that cold air is humid, which leads to condensation and precipitation. However, warm air masses often have a higher level of humidity compared with cold air masses. It can be confusing that condensation occurs with rising, expanding, and cooling. The unit does not go into this in depth, however. For students who choose Sage\u2019s response, it is probably sufficient here to scaffold experiences with data and virtual storm showing the general pattern of warm air masses having higher levels of humidity than cool air masses.\\n\\n\u2022\\tStudents who choose Alex or Sage\u2019s response can also benefit from discussion and emphasis on the importance of getting the rule right (enough) in order to create a computational model that works. The students working on their weather model will not be able to predict weather with any consistency or accuracy if there is a big problem with the rule (algorithm) they have written into their computer model. \\n\\n###More Formal Idea\\n\u2022\\t**Delana\u2019s response (precipitation occurs with both cold fronts and warm fronts coming in)** is the best answer. Delana\u2019s explanation does not include a more complete mechanistic sequence involving cold air pushing warm air up; warm air rising, expanding, and condensing; and precipitation occurring as a result. This is because the Precipitating Change curriculum simplifies weather phenomena by emphasizing important patterns and de-emphasizing complicated mechanisms. This focus allows the curriculum to scaffold students in connecting observed patterns with rules that can be used to create predictive weather forecasting computer models. Delana\u2019s response both recognizes that weather fronts are made of air (matter) and demonstrates recognition of the correct pattern of conditions in air masses (temperatures, levels of humidity) associated with precipitation forming. \",\"content2\":\"\",\"mediaType\":\"none\",\"mediaCaption\":\"Last, First. \\\"Title of Work.\\\" Year created. Site Title [OR] Publisher. 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One way to make sense of the data is to develop a rule, generalized statements of patterns you see again and again.\u003C/p\u003E\n\u003Cp\u003EExample: This rule has two parts that must happen to have a certain result. If it was a [ \u003Cstrong\u003Every nice summer\u003C/strong\u003E ] and if it is [ \u003Cstrong\u003EAugust\u003C/strong\u003E ], then there will be [ \u003Cstrong\u003Elots of berries to pick\u003C/strong\u003E ].\u0026nbsp;\u003C/p\u003E\n\u003Cp style=\"text-align: justify;\"\u003E\u003Cimg class=\"\" src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/RuleStatement.jpg\" alt=\"\" width=\"472\" height=\"221\" /\u003E\u003C/p\u003E\n\u003Cp\u003EThink about developing a similar statement that could be used to determine where it will rain.\u003C/p\u003E", + "is_callout": false, + "is_full_width": true, + "is_hidden": false, + "name": "", + "type": "Embeddable::Xhtml", + "ref_id": "272933-Embeddable::Xhtml" + }, + "section": "header_block" + }, { + "embeddable": { + "plugin": { + "description": "", + "author_data": "{\"tipType\":\"windowShade\",\"questionWrapper\":{\"correctExplanation\":\"correct\",\"distractorsExplanation\":\"distractor\",\"exemplar\":\"exemplar\",\"teacherTip\":\"teacherTip\",\"teacherTipImageOverlay\":\"\"},\"windowShade\":{\"windowShadeType\":\"theoryAndBackground\",\"layout\":\"mediaLeft\",\"initialOpenState\":false,\"content\":\"### LESSON 4: BUILDING RULES\\n**WHERE DOES IT RAIN?**\\n\\nIn this lesson, students develop a rule for where it will rain and test their rule using a Virtual Model. This lesson supports students to build their understanding of how observations of natural phenomena (weather) can be generalized (rule abstraction) for computational modeling (rule testing and rule refinement) and predictive purposes. This lesson introduces new technology, a Virtual Model, that allows students to test rules with the dataset they have been exploring in Lesson 3. \\n\\n**LEARNING GOALS**\\n\\nStudents will be able to:\\n\\n* Describe the relationship between moisture content and temperature by identifying key patterns in weather data\\n\\n* Develop a rule for where precipitation will occur using precise language\\n\\n\\n\\nComputational thinking (CT) Skills introduced in this lesson can be found in the table below:\\n\\n| CT Skill | CT Skill Definition | Use in Lesson |\\n|---------------------|---------------------------------------------------------------------------------------------------|------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|\\n| Pattern Recognition | Recognizing that data or information is repeating in a logical (expected) way. | Students develop a general statement to answer the question, \\\"Where does it rain?\\\" |\\n| Rule Abstraction | Developing a statement of how things work based on the patterns you observed. | Students make a generic statement to answer, \\\"Where does it rain?\\\" |\\n| Rule Testing | Investigating whether a rule will still be true in different situations. | Virtual Model activity|\\n| Rule Refinement | Modifying a rule to be more precise to work in the model. Precise (exact, careful about details) | The Virtual Model allows students to be able to test their rule statements and make changes based on the model. |\\t\",\"content2\":\"\",\"mediaType\":\"none\",\"mediaCaption\":\"Last, First. \\\"Title of Work.\\\" Year created. Site Title [OR] Publisher. Gallery [OR] Location. http://www.url.com.\",\"mediaURL\":\"\"}}", + "approved_script_label": "teacherEditionTips", + "component_label": "windowShade", + "approved_script": { + "name": "Teacher Edition", + "url": "https://teacher-edition-tips-plugin.concord.org/version/v3.6.0/plugin.js", + "label": "teacherEditionTips", + "description": "This plugin provides Teacher Edition components", + "version": 3, + "json_url": "https://teacher-edition-tips-plugin.concord.org/version/v3.6.0/manifest.json", + "authoring_metadata": "{\"components\":[{\"label\":\"windowShade\",\"name\":\"Window Shades\",\"scope\":\"embeddable\",\"guiAuthoring\":true},{\"label\":\"sideTip\",\"name\":\"Side Tips\",\"scope\":\"embeddable\",\"guiAuthoring\":true},{\"label\":\"questionWrapper\",\"name\":\"Question Wrapper\",\"scope\":\"embeddable-decoration\",\"decorates\":[\"Embeddable::MultipleChoice\",\"Embeddable::OpenResponse\",\"Embeddable::ImageQuestion\",\"ManagedInteractive\",\"MwInteractive\",\"ImageInteractive\",\"VideoInteractive\"],\"guiAuthoring\":true,\"guiPreview\":true}]}" + } + }, + "is_hidden": false, + "is_full_width": true, + "type": "Embeddable::EmbeddablePlugin", + "ref_id": "4242-Embeddable::EmbeddablePlugin" + }, + "section": null + }, { + "embeddable": { + "plugin": { + "description": "", + "author_data": "{\"tipType\":\"windowShade\",\"questionWrapper\":{\"correctExplanation\":\"correct\",\"distractorsExplanation\":\"distractor\",\"exemplar\":\"exemplar\",\"teacherTip\":\"teacherTip\",\"teacherTipImageOverlay\":\"\"},\"windowShade\":{\"windowShadeType\":\"teacherTip\",\"layout\":\"mediaLeft\",\"initialOpenState\":false,\"content\":\"### IMPLEMENTATION TIME 1 class period with Pre-Assessment (45 minutes)\\n\\n**KEY ACTIVITIES:**\\n\\n**Activity 1 - Rule Abstraction Conversation (20 mins)\\n\\n**Activity 2 - Refining and Testing Rules using a Virtual Model (25 mins)\\n\\n### MATERIALS AND SET-UP\\n\\nPer Student:\\n\\n* Science Notebooks\\n* Access to Student Online Activities\\n\",\"content2\":\"\",\"mediaType\":\"none\",\"mediaCaption\":\"Last, First. \\\"Title of Work.\\\" Year created. 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Anchorage, AK. \",\"mediaURL\":\"https://precipitatingchange-resources.concord.org/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/JackieLesson4_88.mp4\"}}", + "approved_script_label": "teacherEditionTips", + "component_label": "windowShade", + "approved_script": { + "name": "Teacher Edition", + "url": "https://teacher-edition-tips-plugin.concord.org/version/v3.6.0/plugin.js", + "label": "teacherEditionTips", + "description": "This plugin provides Teacher Edition components", + "version": 3, + "json_url": "https://teacher-edition-tips-plugin.concord.org/version/v3.6.0/manifest.json", + "authoring_metadata": "{\"components\":[{\"label\":\"windowShade\",\"name\":\"Window Shades\",\"scope\":\"embeddable\",\"guiAuthoring\":true},{\"label\":\"sideTip\",\"name\":\"Side Tips\",\"scope\":\"embeddable\",\"guiAuthoring\":true},{\"label\":\"questionWrapper\",\"name\":\"Question Wrapper\",\"scope\":\"embeddable-decoration\",\"decorates\":[\"Embeddable::MultipleChoice\",\"Embeddable::OpenResponse\",\"Embeddable::ImageQuestion\",\"ManagedInteractive\",\"MwInteractive\",\"ImageInteractive\",\"VideoInteractive\"],\"guiAuthoring\":true,\"guiPreview\":true}]}" + } + }, + "is_hidden": false, + "is_full_width": true, + "type": "Embeddable::EmbeddablePlugin", + "ref_id": "4244-Embeddable::EmbeddablePlugin" + }, + "section": null + }] + }, { + "additional_sections": null, + "embeddable_display_mode": "stacked", + "id": 308633, + "is_completion": false, + "is_hidden": false, + "layout": "l-full-width", + "name": "Activity 1 - Rule Abstraction", + "position": 2, + "show_header": true, + "show_info_assessment": true, + "show_interactive": false, + "show_sidebar": false, + "sidebar": null, + "sidebar_title": "Did you know?", + "toggle_info_assessment": false, + "embeddables": [{ + "embeddable": { + "content": "\u003Cp\u003EVIRTUAL STORM: RULE ABSTRACTION CONVERSATION\u003C/p\u003E\n\u003Cp\u003EYour task is to take a deeper look at your data and start summarizing the patterns that you see with the goal of writing a one-sentence statement that brings together the most important patterns to answer the question, \u0026ldquo;Where does it rain?\u0026rdquo;.\u003C/p\u003E\n\u003Cp\u003ELet's start by looking at the data you recorded on your Storm Tracker sheet for 3pm in your Science Notebook (page 12).\u003C/p\u003E\n\u003Cp\u003EWork within your research team and circle the areas where you think it will rain based on temperature data.\u0026nbsp;\u003C/p\u003E\n\u003Cp\u003E\u003Cimg style=\"display: block; margin-left: auto; margin-right: auto;\" src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/Lesson4StormTracker7pm.png\" width=\"444\" height=\"444\" /\u003E\u003C/p\u003E\n\u003Cp\u003ENow let's look at the Weather Map of the Alaska area at 7pm (see below). Work with your research team to find patterns that could help you identify where it will rain.\u003C/p\u003E\n\u003Cp\u003E\u003Cimg class=\"\" style=\"display: block; margin-left: auto; margin-right: auto;\" src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/WeatherMAPB.jpg\" alt=\"\" width=\"750\" height=\"583\" /\u003E\u003C/p\u003E", + "is_callout": false, + "is_full_width": true, + "is_hidden": false, + "name": "", + "type": "Embeddable::Xhtml", + "ref_id": "272934-Embeddable::Xhtml" + }, + "section": "header_block" + }, { + "embeddable": { + "name": "", + "url_fragment": null, + "authored_state": "{\"version\":1,\"prompt\":\"\u003Cp\u003EDiscuss with your research team where you expect it will rain at 7 pm on the Weather Map based on the patterns that you saw for 3 pm. 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The specific computational thinking practices highlighted and practiced in this activity are **Rule Abstraction**, **Rule Testing**, and **Rule Refinement**. We anticipate that this conversation is going to require heavy scaffolding to get students acquainted and comfortable with writing rules. Efforts here will pay off later in Lessons 5 when students must write additional rules for other weather phenomena.\\n\\n**1. Abstracting a rule.**\\n\\n* Introduce the task of writing a one-sentence statement that brings together the most important patterns to answer the question, \u201cWhere does it rain?\u201d \\n\\n**2. Gathering more information.**\\n\\n* Have students look at their Virtual Storm Tracker in their Science Notebook on page 12 and circle where they think it will rain at \\n 7 pm, using temperature only.\\n\\n* Have students look at the Weather Map 7 pm with Precipitation \u0026 Air Moisture Content in their Science Notebook on page 17 and discuss with their research teams where you think it will rain with this new information. \\n\\n* Once they have decided on where they think it will rain, direct students to enter their answer to the question in the appropriate place on this page. \\n\\n**3. Introduce rule abstraction.** Rule Abstraction is creating a general statement derived from exploring patterns in data in order to establish rule(s), principles, or insights that may be generalized to other contexts. 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To help students develop a stronger voice and build a statement, they are asked to apply their understandings to another time step (7 pm). By applying their thinking at two different time steps, students validate their ideas and develop more formalized ideas on how they think the weather variables relate to each other. \\n\\n* Advise students to try to merge ideas from what they learned in Lessons 2 and 3. \\n\\n* Ask students to be selective in what patterns they think are strongest in explaining precipitation. \\n\\n* Explain to students that they just did something that weather scientists do called Rule Abstraction (creating a general statement derived from exploring patterns in data in order to establish rule(s), principles or insights that may be generalized to other contexts). 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Explore all the features of this model. Discuss with your research team what each feature shows you.\u0026nbsp;\u003C/p\u003E\r\n\u003Cp\u003E\u003Cbr /\u003EAfter you have explored the model, refine your precipitation rule until you have found the best fit between the actual precipitation and the precipitation predicted by the rule. 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"sidebar_title": "Did you know?", + "toggle_info_assessment": false, + "embeddables": [{ + "embeddable": { + "content": "\u003Cp\u003EMs. Tevuk\u0026rsquo;s class is studying weather. The students will make a computer model to predict weather in Alaska. They need to break Alaska into smaller chunks of area so their model can use information (data) about each chunk to predict the weather. Four students have different ideas about what size the chunks should be.\u0026nbsp;Alaska is approximately 663,00 square miles. The map below shows Alaska with a grid that divides the map into squares.\u003C/p\u003E\n\u003Cp\u003E\u003Cimg class=\"\" style=\"display: block; margin-left: auto; margin-right: auto;\" src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/Alaska200grid.jpg\" alt=\"\" width=\"557\" height=\"510\" /\u003E\u003C/p\u003E\n\u003Cp\u003EHere are the students\u0026rsquo; ideas:\u003C/p\u003E\n\u003Ctable cellpadding=\"30\"\u003E\n\u003Ctbody\u003E\n\u003Ctr\u003E\n\u003Cth colspan=\"2\"\u003E\u003Cstrong\u003EAlex\u003C/strong\u003E\u003C/th\u003E\n\u003Cth colspan=\"2\"\u003E\u003Cstrong\u003EDelana\u003C/strong\u003E\u003C/th\u003E\n\u003C/tr\u003E\n\u003Ctr\u003E\n\u003Ctd width=\"88\"\u003E\u003Cimg src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/Alex5.png\" width=\"80\" height=\"100\" align=\"center\" hspace=\"10\" vspace=\"10\" /\u003E\u003C/td\u003E\n\u003Ctd style=\"padding: 10px;\" width=\"350\"\u003E\n\u003Cp\u003EWe need to include as much data as possible so our model will be accurate. Let\u0026rsquo;s break Alaska down into chunks that are each one square yard in size (three feet on each side).\u003C/p\u003E\n\u003Cp\u003E\u003Cimg style=\"display: block; margin-left: auto; margin-right: auto;\" src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/3ftx3ft.png\" width=\"223\" height=\"200\" /\u003E\u003C/p\u003E\n\u003C/td\u003E\n\u003Ctd width=\"88\"\u003E\u003Cimg src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/Delana5.png\" width=\"80\" height=\"100\" align=\"center\" hspace=\"10\" vspace=\"10\" /\u003E\u003C/td\u003E\n\u003Ctd style=\"padding: 10px;\" width=\"350\"\u003E\n\u003Cp\u003EWe want to predict weather for villages, so our chunks should be about the size of an Alaska village. Let\u0026rsquo;s make chunks that are each a square mile (5,280 feet on each side).\u003C/p\u003E\n\u003Cp\u003E\u003Cimg src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/1milex1mile.png\" width=\"222\" height=\"200\" /\u003E\u003C/p\u003E\n\u003C/td\u003E\n\u003C/tr\u003E\n\u003C/tbody\u003E\n\u003Ctbody\u003E\n\u003Ctr\u003E\n\u003Cth colspan=\"2\"\u003E\u003Cstrong\u003EKalin\u003C/strong\u003E\u003C/th\u003E\n\u003Cth colspan=\"2\"\u003E\u003Cstrong\u003ESage\u003C/strong\u003E\u003C/th\u003E\n\u003C/tr\u003E\n\u003Ctr\u003E\n\u003Ctd width=\"88\"\u003E\n\u003Cp\u003E\u003Cimg src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/Kalin5.png\" width=\"80\" height=\"100\" align=\"center\" hspace=\"10\" vspace=\"10\" /\u003E\u003C/p\u003E\n\u003C/td\u003E\n\u003Ctd style=\"padding: 10px;\" width=\"350\"\u003E\n\u003Cp\u003EThe chunks can be even bigger because there\u0026rsquo;s space in between villages. Let\u0026rsquo;s break Alaska down into chunks that are each 20 miles by 20 miles in size.\u003C/p\u003E\n\u003Cp\u003E\u003Cimg style=\"display: block; margin-left: auto; margin-right: auto;\" src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/20milesx20miles.png\" width=\"230\" height=\"204\" /\u003E\u003C/p\u003E\n\u003C/td\u003E\n\u003Ctd width=\"88\"\u003E\n\u003Cp\u003E\u003Cimg src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/Sage3.png\" width=\"80\" height=\"100\" align=\"center\" hspace=\"8\" vspace=\"8\" /\u003E\u003C/p\u003E\n\u003C/td\u003E\n\u003Ctd style=\"padding: 10px;\" width=\"350\"\u003E\n\u003Cp\u003EIf we use 20 miles by 20 miles, we\u0026rsquo;ll have over 1,500 chunks for Alaska. That\u0026rsquo;s a lot. Let\u0026rsquo;s use 200 miles by 200 miles so we\u0026rsquo;ll only need about 16 chunks.\u003C/p\u003E\n\u003Cp\u003E\u003Cimg style=\"display: block; margin-left: auto; margin-right: auto;\" src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/200milesx200miles.png\" width=\"230\" height=\"206\" /\u003E\u003C/p\u003E\n\u003C/td\u003E\n\u003C/tr\u003E\n\u003C/tbody\u003E\n\u003C/table\u003E", + "is_callout": false, + "is_full_width": true, + "is_hidden": false, + "name": "", + "type": "Embeddable::Xhtml", + "ref_id": "272918-Embeddable::Xhtml" + }, + "section": "header_block" + }, { + "embeddable": { + "name": "Multiple Choice Question element", + "url_fragment": null, + "authored_state": "{\"version\":1,\"questionType\":\"multiple_choice\",\"choices\":[{\"id\":\"1\",\"content\":\"Alex\",\"correct\":false,\"choiceFeedback\":\"\"},{\"id\":\"2\",\"content\":\"Delana\",\"correct\":false,\"choiceFeedback\":\"\"},{\"id\":\"3\",\"content\":\"Kalin\",\"correct\":false,\"choiceFeedback\":\"\"},{\"id\":\"4\",\"content\":\"Sage\",\"correct\":false,\"choiceFeedback\":\"\"}],\"layout\":\"vertical\",\"prompt\":\"\u003Cp\u003EWhich student\u0026rsquo;s idea do you agree with the most?\u003C/p\u003E\"}", + "is_hidden": false, + "is_full_width": true, + "show_in_featured_question_report": true, + "inherit_aspect_ratio_method": true, + "custom_aspect_ratio_method": null, + "inherit_native_width": true, + "custom_native_width": 576, + "inherit_native_height": true, + "custom_native_height": 435, + "inherit_click_to_play": true, + "custom_click_to_play": false, + "inherit_full_window": true, + "custom_full_window": false, + "inherit_click_to_play_prompt": true, + "custom_click_to_play_prompt": null, + "inherit_image_url": true, + "custom_image_url": null, + "library_interactive": { + "hash": "98f3d10aa7f2fce6bdeb0ecda339fa56dc80b37c", + "data": { + "aspect_ratio_method": "DEFAULT", + "authoring_guidance": "", + "base_url": "https://models-resources.concord.org/question-interactives/version/v1.1.0/multiple-choice/", + "click_to_play": false, + "click_to_play_prompt": null, + "description": "", + "enable_learner_state": true, + "full_window": false, + "has_report_url": false, + "image_url": null, + "name": "Multiple Choice", + "native_height": 435, + "native_width": 576, + "no_snapshots": false, + "show_delete_data_button": false, + "thumbnail_url": "", + "customizable": true, + "authorable": true + } + }, + "type": "ManagedInteractive", + "ref_id": "1930-ManagedInteractive", + "linked_interactives": [] + }, + "section": null + }, { + "embeddable": { + "name": "", + "url_fragment": null, + "authored_state": "{\"version\":1,\"prompt\":\"\u003Cp\u003EWhy do you agree with that student\u0026rsquo;s idea the most? Please explain your reasoning.\u003C/p\u003E\",\"defaultAnswer\":\"\",\"required\":false,\"questionType\":\"open_response\",\"hint\":\"\"}", + "is_hidden": false, + "is_full_width": true, + "show_in_featured_question_report": true, + "inherit_aspect_ratio_method": true, + "custom_aspect_ratio_method": null, + "inherit_native_width": true, + "custom_native_width": 576, + "inherit_native_height": true, + "custom_native_height": 435, + "inherit_click_to_play": true, + "custom_click_to_play": false, + "inherit_full_window": true, + "custom_full_window": false, + "inherit_click_to_play_prompt": true, + "custom_click_to_play_prompt": null, + "inherit_image_url": true, + "custom_image_url": null, + "library_interactive": { + "hash": "512e0a0a74a0e1cd6247a8ec98fa94dabb8a6132", + "data": { + "aspect_ratio_method": "DEFAULT", + "authoring_guidance": "", + "base_url": "https://models-resources.concord.org/question-interactives/version/v1.1.0/open-response/", + "click_to_play": false, + "click_to_play_prompt": null, + "description": "", + "enable_learner_state": true, + "full_window": false, + "has_report_url": false, + "image_url": null, + "name": "Open Response", + "native_height": 435, + "native_width": 576, + "no_snapshots": false, + "show_delete_data_button": false, + "thumbnail_url": "", + "customizable": true, + "authorable": true + } + }, + "type": "ManagedInteractive", + "ref_id": "1931-ManagedInteractive", + "linked_interactives": [] + }, + "section": null + }, { + "embeddable": { + "plugin": { + "description": null, + "author_data": "{\"tipType\":\"windowShade\",\"windowShade\":{\"windowShadeType\":\"teacherTip\",\"layout\":\"mediaLeft\",\"initialOpenState\":true,\"content\":\"###Post-Assessment Implementation\\n*Lesson 5, Conclusion: How Should We Break It Down? Post-Assessment*\\nDuring the post-assessment, each student will view the scenario again and make a new individual choice, and enter an individual explanation. However, students can work in pairs to discuss their choices and explanations. Student pairs do not have to agree. After students submit their responses, you can lead a discussion and engage the class in talking about some of the issues described below. You should work to lead the class to come to a consensus about which is the best response. Ideally, the students should come to a consensus. If needed, though, you should help the class understand why some responses are better than others.\",\"content2\":\"\",\"mediaType\":\"none\",\"mediaCaption\":\"Last, First. \\\"Title of Work.\\\" Year created. Site Title [OR] Publisher. Gallery [OR] Location. http://www.url.com.\",\"mediaURL\":\"\"}}", + "approved_script_label": "teacherEditionTips", + "component_label": "windowShade", + "approved_script": { + "name": "Teacher Edition", + "url": "https://teacher-edition-tips-plugin.concord.org/version/v3.6.0/plugin.js", + "label": "teacherEditionTips", + "description": "This plugin provides Teacher Edition components", + "version": 3, + "json_url": "https://teacher-edition-tips-plugin.concord.org/version/v3.6.0/manifest.json", + "authoring_metadata": "{\"components\":[{\"label\":\"windowShade\",\"name\":\"Window Shades\",\"scope\":\"embeddable\",\"guiAuthoring\":true},{\"label\":\"sideTip\",\"name\":\"Side Tips\",\"scope\":\"embeddable\",\"guiAuthoring\":true},{\"label\":\"questionWrapper\",\"name\":\"Question Wrapper\",\"scope\":\"embeddable-decoration\",\"decorates\":[\"Embeddable::MultipleChoice\",\"Embeddable::OpenResponse\",\"Embeddable::ImageQuestion\",\"ManagedInteractive\",\"MwInteractive\",\"ImageInteractive\",\"VideoInteractive\"],\"guiAuthoring\":true,\"guiPreview\":true}]}" + } + }, + "is_hidden": false, + "is_full_width": true, + "type": "Embeddable::EmbeddablePlugin", + "ref_id": "4223-Embeddable::EmbeddablePlugin" + }, + "section": null + }, { + "embeddable": { + "plugin": { + "description": null, + "author_data": "{\"tipType\":\"windowShade\",\"windowShade\":{\"windowShadeType\":\"theoryAndBackground\",\"layout\":\"mediaLeft\",\"initialOpenState\":true,\"content\":\"###Computational Thinking Concepts and Practices:\\n* Decomposition\\n* Data Abstraction\\n\\n###What is the Purpose of this Assessment Probe?\\nThe following information provides background for **teachers** and is not necessarily representative of the learning goals for everything students should understand. We suggest you review the information below and think about ways to scaffold students toward developing **knowledge and practice** as appropriate for their classes. We also recommend emphasizing the underlying ideas and practices, rather than on vocabulary terms such as **decomposition** or **data abstraction**. By discussing the different options, students can engage in productive talk related to these computational thinking concepts without using technical terminology. \\n\\nThis assessment probe is designed to assess and scaffold students in thinking and talking about **decomposition**, which is *breaking down data, processes, or problems into smaller components and manageable parts so they can be more easily solved.*\\n\\nIn particular, the probe addresses physical decomposition of a system, which involves *dividing a continuous representation of a system into smaller, discrete parts.* In computational modeling, *physical decomposition makes it possible to apply values to various parameters in each small part (cell) of the model domain, which in turn makes it possible to apply mathematical approaches to the problem.*\\n\\nAt the broader level, this type of discretization is an example of the computational thinking concept of **data abstraction**. Abstraction *involves letting one object stand for many by \u201ccapturing essential properties common to a set of objects while hiding irrelevant distinctions among them\u201d* (Wing, 2014, http://socialissues.cs.toronto.edu/index.html%3Fp=279.html). When we divide the Alaska map into cells, we are stripping away a lot of information about each cell (e.g., how many trees or houses are in that area) so that we can focus on just the pieces of information we need for addressing our particular problem (in this case, we will want to understand some other things about each cell at certain points in time to help us predict the weather, i.e., the temperature of the air, the wind speed and direction, the humidity level in each cell). \\n\\nThis assessment is situated within the unit context to provide an opportunity for students to make sense about decomposition of a specific, tangible weather problem. While one of the responses makes the most sense from a practical standpoint for this problem, there\u2019s no absolutely correct answer. Using an indefinite problem provides space for students to think and talk about the pros and cons of using different sized chunks for predicting weather. This is the kind of real-world problem that weather modelers need to think about as they do their work. \",\"content2\":\"\",\"mediaType\":\"none\",\"mediaCaption\":\"Last, First. \\\"Title of Work.\\\" Year created. Site Title [OR] Publisher. Gallery [OR] Location. http://www.url.com.\",\"mediaURL\":\"\"}}", + "approved_script_label": "teacherEditionTips", + "component_label": "windowShade", + "approved_script": { + "name": "Teacher Edition", + "url": "https://teacher-edition-tips-plugin.concord.org/version/v3.6.0/plugin.js", + "label": "teacherEditionTips", + "description": "This plugin provides Teacher Edition components", + "version": 3, + "json_url": "https://teacher-edition-tips-plugin.concord.org/version/v3.6.0/manifest.json", + "authoring_metadata": "{\"components\":[{\"label\":\"windowShade\",\"name\":\"Window Shades\",\"scope\":\"embeddable\",\"guiAuthoring\":true},{\"label\":\"sideTip\",\"name\":\"Side Tips\",\"scope\":\"embeddable\",\"guiAuthoring\":true},{\"label\":\"questionWrapper\",\"name\":\"Question Wrapper\",\"scope\":\"embeddable-decoration\",\"decorates\":[\"Embeddable::MultipleChoice\",\"Embeddable::OpenResponse\",\"Embeddable::ImageQuestion\",\"ManagedInteractive\",\"MwInteractive\",\"ImageInteractive\",\"VideoInteractive\"],\"guiAuthoring\":true,\"guiPreview\":true}]}" + } + }, + "is_hidden": false, + "is_full_width": true, + "type": "Embeddable::EmbeddablePlugin", + "ref_id": "4224-Embeddable::EmbeddablePlugin" + }, + "section": null + }, { + "embeddable": { + "plugin": { + "description": null, + "author_data": "{\"tipType\":\"windowShade\",\"windowShade\":{\"windowShadeType\":\"discussionPoints\",\"layout\":\"mediaLeft\",\"initialOpenState\":true,\"content\":\"###What Are Common Student Ideas and What Supports Could Help Students?\\nBelow are some issues to consider in assessing students\u2019 ideas, and some suggestions of ways to support students in developing more formal reasoning about decomposition.\\n\\n###Less Formal Ideas\\n\u2022\\t**Alex\u2019s response (3 feet by 3 feet chunks)** is probably too small for this problem. A model decomposed into cells of this size over the state of Alaska would require a very large amount of interpolation because, of course, there are not that many weather stations available to provide observed data for each cell (although satellites could potentially collect this data over land surfaces). Assuming data come from weather stations though, a model composed of one square yard sized cells would provide a false level of accuracy based on an insufficient amount of data for understanding weather at that scale. In addition, this model would require a great deal of computing power. It would take a lot of time and energy for the model to process all the data, and because so much of the data will need to be interpolated, the results will not really be trustworthy at the scale of one square yard.\\n\\nSome students might find Alex\u2019s response appealing because they think it is important to be very accurate with a computer model and/or because they think computer models have the capacity to make very accurate predictions. These students could use support in understanding that computer model outputs are based on computer model inputs. With relatively few data inputs from weather stations compared to the outputs (predictions at the level of each square yard. Alex\u2019s model will not be able to perform very well. \\n\\n\u2022\\t**Sage\u2019s response (200 miles by 200 miles chunks)** will not provide enough detail for Alaskans to make the decisions they need to make related to the weather. The map below shows an area of about 200 by 200 miles. If this area were used for the weather model, then it would not be possible to give people in Port Lay a separate weather prediction than people in Utqiagvik. While Alex and Delana\u2019s responses have problems with false accuracy, Sage\u2019s response has problems with insufficient precision for the real-world problem (predicting the weather at a scale that will be useful for people in different villages and towns). \\n\\nStudents who choose Sage\u2019s response may think there is a need to enter actual data (i.e., from a weather station) for every cell in a computer model. These students could benefit from discussions that connect this assessment probe to the idea of interpolation \u2013 we don\u2019t necessarily need to enter data for every single cell in a computer model. Much of the data can be interpolated. If we didn\u2019t have the capacity to interpolate data, then Sage would be right, - it would be a whole lot of work to make a computer model for Alaska, even at the scale of 20 by 20 mile cells. Interpolation helps solve this problem (within limits of course, because if we interpolate too much data we end up with the problems associated with Alex\u2019s and Delana\u2019s models). \\n\\n\u003Cimg src=\\\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/200x200milechunkofAlaska.png\\\" width=\\\"300\\\" height=\\\"300\\\" /\u003E\\n\\n\\n###Middle Level \\n\u2022\\t**Delana\u2019s response (1 mile by 1 mile chunks)** is also probably too small for the problem. There would be approximately 663,000 cells in this model. Because of the number of cells, a lot of the data for this model would need to be interpolated. There is not necessarily a need for weather information at this fine-grained scale. While less so than Alex\u2019s response, this model would still have problems with too much interpolation leading to a false level of accuracy at the square mile scale and an excessive amount of computing power needed.\\n\\nDelana\u2019s response shows that she\u2019s doing important thinking about the scale of information that is needed by the audience for the model (i.e., people living in villages and towns). Students often think about computer models and their outputs in terms of what can be shown or seen. While visualizations are an important output of computer models, students can also use support in developing deeper understandings about the need for sufficient data and appropriate processing algorithms for a computer model to show something. Students often think about computer models as black boxes that do something mysterious and then provide an answer. Over the course of the unit, students should develop deeper understanding of how data and rules (algorithms) are the guts of the computer model that help modelers use the model to explain and predict things like weather. \\n\\n\\n###More Formal Ideas\\n\u2022\\t**Kalin\u2019s answer (20 miles by 20 miles chunks)** provides the ability to process data at a reasonable scale for an area as large as the state of Alaska. There would be approximately 1650 cells in this model. If the chunks were much bigger, it would not be possible to process and provide information at a small enough scale for what is needed in terms of weather information for individual villages, towns, and cities. If the chunks were much smaller, they would be subject to the same problems associated with Alex\u2019s and Delana\u2019s responses.\",\"content2\":\"\",\"mediaType\":\"none\",\"mediaCaption\":\"Last, First. \\\"Title of Work.\\\" Year created. Site Title [OR] Publisher. Gallery [OR] Location. http://www.url.com.\",\"mediaURL\":\"\"}}", + "approved_script_label": "teacherEditionTips", + "component_label": "windowShade", + "approved_script": { + "name": "Teacher Edition", + "url": "https://teacher-edition-tips-plugin.concord.org/version/v3.6.0/plugin.js", + "label": "teacherEditionTips", + "description": "This plugin provides Teacher Edition components", + "version": 3, + "json_url": "https://teacher-edition-tips-plugin.concord.org/version/v3.6.0/manifest.json", + "authoring_metadata": "{\"components\":[{\"label\":\"windowShade\",\"name\":\"Window Shades\",\"scope\":\"embeddable\",\"guiAuthoring\":true},{\"label\":\"sideTip\",\"name\":\"Side Tips\",\"scope\":\"embeddable\",\"guiAuthoring\":true},{\"label\":\"questionWrapper\",\"name\":\"Question Wrapper\",\"scope\":\"embeddable-decoration\",\"decorates\":[\"Embeddable::MultipleChoice\",\"Embeddable::OpenResponse\",\"Embeddable::ImageQuestion\",\"ManagedInteractive\",\"MwInteractive\",\"ImageInteractive\",\"VideoInteractive\"],\"guiAuthoring\":true,\"guiPreview\":true}]}" + } + }, + "is_hidden": false, + "is_full_width": true, + "type": "Embeddable::EmbeddablePlugin", + "ref_id": "4225-Embeddable::EmbeddablePlugin" + }, + "section": null + }] + }, { + "additional_sections": {}, + "embeddable_display_mode": "stacked", + "id": 308644, + "is_completion": true, + "is_hidden": false, + "layout": "l-6040", + "name": null, + "position": 2, + "show_header": false, + "show_info_assessment": false, + "show_interactive": false, + "show_sidebar": false, + "sidebar": null, + "sidebar_title": "Did you know?", + "toggle_info_assessment": false, + "embeddables": [] + }], + "plugins": [], + "type": "LightweightActivity", + "export_site": "Lightweight Activities Runtime and Authoring" +} diff --git a/src/public/offline-activities/staging-precipitating-change/lesson-5-pre-v1.json b/src/public/offline-activities/staging-precipitating-change/lesson-5-pre-v1.json new file mode 100644 index 00000000..be34f9b5 --- /dev/null +++ b/src/public/offline-activities/staging-precipitating-change/lesson-5-pre-v1.json @@ -0,0 +1,184 @@ +{ + "description": "", + "editor_mode": 0, + "layout": 0, + "name": "AP - Lesson 5: Alaska Mainland 2 - Pre - What Do You Think?", + "notes": "", + "project_id": null, + "related": "", + "runtime": "Activity Player", + "show_submit_button": true, + "student_report_enabled": true, + "thumbnail_url": "https://learn-resources.concord.org/images/stem-resources/icons/pc-lesson1.png", + "time_to_complete": 5, + "version": 1, + "theme_name": "Precipitating Change", + "pages": [{ + "additional_sections": null, + "embeddable_display_mode": "stacked", + "id": 308630, + "is_completion": false, + "is_hidden": false, + "layout": "l-full-width", + "name": "How Should We Break It Down?", + "position": 1, + "show_header": true, + "show_info_assessment": true, + "show_interactive": false, + "show_sidebar": false, + "sidebar": null, + "sidebar_title": "Did you know?", + "toggle_info_assessment": false, + "embeddables": [{ + "embeddable": { + "content": "\u003Cp\u003EMs. Tevuk\u0026rsquo;s class is studying weather. The students will make a computer model to predict weather in Alaska. They need to break Alaska into smaller chunks of area so their model can use information (data) about each chunk to predict the weather. Four students have different ideas about what size the chunks should be.\u0026nbsp;Alaska is approximately 663,000 square miles. The map below shows Alaska with a grid that divides the map into squares.\u003C/p\u003E\n\u003Cp\u003E\u003Cimg class=\"\" style=\"display: block; margin-left: auto; margin-right: auto;\" src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/Alaska200grid.jpg\" alt=\"\" width=\"557\" height=\"510\" /\u003E\u003C/p\u003E\n\u003Cp\u003EHere are the students\u0026rsquo; ideas:\u003C/p\u003E\n\u003Ctable cellpadding=\"30\"\u003E\n\u003Ctbody\u003E\n\u003Ctr\u003E\n\u003Cth colspan=\"2\"\u003E\u003Cstrong\u003EAlex\u003C/strong\u003E\u003C/th\u003E\n\u003Cth colspan=\"2\"\u003E\u003Cstrong\u003EDelana\u003C/strong\u003E\u003C/th\u003E\n\u003C/tr\u003E\n\u003Ctr\u003E\n\u003Ctd width=\"88\"\u003E\u003Cimg src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/Alex5.png\" width=\"80\" height=\"100\" align=\"center\" hspace=\"10\" vspace=\"10\" /\u003E\u003C/td\u003E\n\u003Ctd style=\"padding: 10px;\" width=\"350\"\u003E\n\u003Cp\u003EWe need to include as much data as possible so our model will be accurate. Let\u0026rsquo;s break Alaska down into chunks that are each one square yard in size (three feet on each side).\u003C/p\u003E\n\u003Cp\u003E\u003Cimg style=\"display: block; margin-left: auto; margin-right: auto;\" src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/3ftx3ft.png\" width=\"223\" height=\"200\" /\u003E\u003C/p\u003E\n\u003C/td\u003E\n\u003Ctd width=\"88\"\u003E\u003Cimg src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/Delana5.png\" width=\"80\" height=\"100\" align=\"center\" hspace=\"10\" vspace=\"10\" /\u003E\u003C/td\u003E\n\u003Ctd style=\"padding: 10px;\" width=\"350\"\u003E\n\u003Cp\u003EWe want to predict weather for villages, so our chunks should be about the size of an Alaska village. Let\u0026rsquo;s make chunks that are each a square mile (5,280 feet on each side).\u003C/p\u003E\n\u003Cp\u003E\u003Cimg src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/1milex1mile.png\" width=\"222\" height=\"200\" /\u003E\u003C/p\u003E\n\u003C/td\u003E\n\u003C/tr\u003E\n\u003C/tbody\u003E\n\u003Ctbody\u003E\n\u003Ctr\u003E\n\u003Cth colspan=\"2\"\u003E\u003Cstrong\u003EKalin\u003C/strong\u003E\u003C/th\u003E\n\u003Cth colspan=\"2\"\u003E\u003Cstrong\u003ESage\u003C/strong\u003E\u003C/th\u003E\n\u003C/tr\u003E\n\u003Ctr\u003E\n\u003Ctd width=\"88\"\u003E\n\u003Cp\u003E\u003Cimg src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/Kalin5.png\" width=\"80\" height=\"100\" align=\"center\" hspace=\"10\" vspace=\"10\" /\u003E\u003C/p\u003E\n\u003C/td\u003E\n\u003Ctd style=\"padding: 10px;\" width=\"350\"\u003E\n\u003Cp\u003EThe chunks can be even bigger because there\u0026rsquo;s space in between villages. Let\u0026rsquo;s break Alaska down into chunks that are each 20 miles by 20 miles in size.\u003C/p\u003E\n\u003Cp\u003E\u003Cimg style=\"display: block; margin-left: auto; margin-right: auto;\" src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/20milesx20miles.png\" width=\"230\" height=\"204\" /\u003E\u003C/p\u003E\n\u003C/td\u003E\n\u003Ctd width=\"88\"\u003E\n\u003Cp\u003E\u003Cimg src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/Sage3.png\" width=\"80\" height=\"100\" align=\"center\" hspace=\"8\" vspace=\"8\" /\u003E\u003C/p\u003E\n\u003C/td\u003E\n\u003Ctd style=\"padding: 10px;\" width=\"350\"\u003E\n\u003Cp\u003EIf we use 20 miles by 20 miles, we\u0026rsquo;ll have over 1,500 chunks for Alaska. That\u0026rsquo;s a lot. Let\u0026rsquo;s use 200 miles by 200 miles so we\u0026rsquo;ll only need about 16 chunks.\u003C/p\u003E\n\u003Cp\u003E\u003Cimg style=\"display: block; margin-left: auto; margin-right: auto;\" src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/200milesx200miles.png\" width=\"230\" height=\"206\" /\u003E\u003C/p\u003E\n\u003C/td\u003E\n\u003C/tr\u003E\n\u003C/tbody\u003E\n\u003C/table\u003E", + "is_callout": false, + "is_full_width": true, + "is_hidden": false, + "name": "", + "type": "Embeddable::Xhtml", + "ref_id": "272931-Embeddable::Xhtml" + }, + "section": "header_block" + }, { + "embeddable": { + "name": "Multiple Choice Question element", + "url_fragment": null, + "authored_state": "{\"version\":1,\"questionType\":\"multiple_choice\",\"choices\":[{\"id\":\"1\",\"content\":\"Alex\",\"correct\":false,\"choiceFeedback\":\"\"},{\"id\":\"2\",\"content\":\"Delana\",\"correct\":false,\"choiceFeedback\":\"\"},{\"id\":\"3\",\"content\":\"Kalin\",\"correct\":false,\"choiceFeedback\":\"\"},{\"id\":\"4\",\"content\":\"Sage\",\"correct\":false,\"choiceFeedback\":\"\"}],\"layout\":\"vertical\",\"prompt\":\"\u003Cp\u003EWhich student\u0026rsquo;s idea do you agree with the most?\u003C/p\u003E\"}", + "is_hidden": false, + "is_full_width": false, + "show_in_featured_question_report": true, + "inherit_aspect_ratio_method": true, + "custom_aspect_ratio_method": null, + "inherit_native_width": true, + "custom_native_width": 576, + "inherit_native_height": true, + "custom_native_height": 435, + "inherit_click_to_play": true, + "custom_click_to_play": false, + "inherit_full_window": true, + "custom_full_window": false, + "inherit_click_to_play_prompt": true, + "custom_click_to_play_prompt": null, + "inherit_image_url": true, + "custom_image_url": null, + "library_interactive": { + "hash": "98f3d10aa7f2fce6bdeb0ecda339fa56dc80b37c", + "data": { + "aspect_ratio_method": "DEFAULT", + "authoring_guidance": "", + "base_url": "https://models-resources.concord.org/question-interactives/version/v1.1.0/multiple-choice/", + "click_to_play": false, + "click_to_play_prompt": null, + "description": "", + "enable_learner_state": true, + "full_window": false, + "has_report_url": false, + "image_url": null, + "name": "Multiple Choice", + "native_height": 435, + "native_width": 576, + "no_snapshots": false, + "show_delete_data_button": false, + "thumbnail_url": "", + "customizable": true, + "authorable": true + } + }, + "type": "ManagedInteractive", + "ref_id": "1945-ManagedInteractive", + "linked_interactives": [] + }, + "section": null + }, { + "embeddable": { + "plugin": { + "description": null, + "author_data": "{\"tipType\":\"windowShade\",\"windowShade\":{\"windowShadeType\":\"teacherTip\",\"layout\":\"mediaLeft\",\"initialOpenState\":true,\"content\":\"###Pre-Assessment Implementation\\n*Lesson 5, Opening: How Should We Break It Down? Pre-Assessment*\\nDuring the pre-assessment, each student will view the scenario above and make an individual choice. The request for an explanation will only be on the post-assessment. After students make an individual choice for the pre-assessment, you can lead the discussion including, for example, a pair/share opportunity and/or full class discussion. \\n\\nAt this time, encourage students to share and discuss their ideas and reasons without indicating that any answer is better or worse. Let the students know that they should keep thinking about this question and that the class will return to it at the end of the lesson.\",\"content2\":\"\",\"mediaType\":\"none\",\"mediaCaption\":\"Last, First. \\\"Title of Work.\\\" Year created. Site Title [OR] Publisher. Gallery [OR] Location. http://www.url.com.\",\"mediaURL\":\"\"}}", + "approved_script_label": "teacherEditionTips", + "component_label": "windowShade", + "approved_script": { + "name": "Teacher Edition", + "url": "https://teacher-edition-tips-plugin.concord.org/version/v3.6.0/plugin.js", + "label": "teacherEditionTips", + "description": "This plugin provides Teacher Edition components", + "version": 3, + "json_url": "https://teacher-edition-tips-plugin.concord.org/version/v3.6.0/manifest.json", + "authoring_metadata": "{\"components\":[{\"label\":\"windowShade\",\"name\":\"Window Shades\",\"scope\":\"embeddable\",\"guiAuthoring\":true},{\"label\":\"sideTip\",\"name\":\"Side Tips\",\"scope\":\"embeddable\",\"guiAuthoring\":true},{\"label\":\"questionWrapper\",\"name\":\"Question Wrapper\",\"scope\":\"embeddable-decoration\",\"decorates\":[\"Embeddable::MultipleChoice\",\"Embeddable::OpenResponse\",\"Embeddable::ImageQuestion\",\"ManagedInteractive\",\"MwInteractive\",\"ImageInteractive\",\"VideoInteractive\"],\"guiAuthoring\":true,\"guiPreview\":true}]}" + } + }, + "is_hidden": false, + "is_full_width": true, + "type": "Embeddable::EmbeddablePlugin", + "ref_id": "4236-Embeddable::EmbeddablePlugin" + }, + "section": null + }, { + "embeddable": { + "plugin": { + "description": null, + "author_data": "{\"tipType\":\"windowShade\",\"windowShade\":{\"windowShadeType\":\"theoryAndBackground\",\"layout\":\"mediaLeft\",\"initialOpenState\":true,\"content\":\"###Computational Thinking Concepts and Practices:\\n* Decomposition\\n* Data Abstraction\\n\\n###What is the Purpose of this Assessment Probe?\\nThe following information provides background for **teachers** and is not necessarily representative of the learning goals for everything students should understand. We suggest you review the information below and think about ways to scaffold students toward developing **knowledge and practice** as appropriate for their classes. We also recommend emphasizing the underlying ideas and practices, rather than on vocabulary terms such as **decomposition** or **data abstraction**. By discussing the different options, students can engage in productive talk related to these computational thinking concepts without using technical terminology. \\n\\nThis assessment probe is designed to assess and scaffold students in thinking and talking about **decomposition**, which is *breaking down data, processes, or problems into smaller components and manageable parts so they can be more easily solved.*\\n\\nIn particular, the probe addresses physical decomposition of a system, which involves *dividing a continuous representation of a system into smaller, discrete parts.* In computational modeling, *physical decomposition makes it possible to apply values to various parameters in each small part (cell) of the model domain, which in turn makes it possible to apply mathematical approaches to the problem.*\\n\\nAt the broader level, this type of discretization is an example of the computational thinking concept of **data abstraction**. Abstraction *involves letting one object stand for many by \u201ccapturing essential properties common to a set of objects while hiding irrelevant distinctions among them\u201d* (Wing, 2014, http://socialissues.cs.toronto.edu/index.html%3Fp=279.html). When we divide the Alaska map into cells, we are stripping away a lot of information about each cell (e.g., how many trees or houses are in that area) so that we can focus on just the pieces of information we need for addressing our particular problem (in this case, we will want to understand some other things about each cell at certain points in time to help us predict the weather, i.e., the temperature of the air, the wind speed and direction, the humidity level in each cell). \\n\\nThis assessment is situated within the unit context to provide an opportunity for students to make sense about decomposition of a specific, tangible weather problem. While one of the responses makes the most sense from a practical standpoint for this problem, there\u2019s no absolutely correct answer. Using an indefinite problem provides space for students to think and talk about the pros and cons of using different sized chunks for predicting weather. This is the kind of real-world problem that weather modelers need to think about as they do their work. \\n\\n\",\"content2\":\"\",\"mediaType\":\"none\",\"mediaCaption\":\"Last, First. \\\"Title of Work.\\\" Year created. Site Title [OR] Publisher. Gallery [OR] Location. http://www.url.com.\",\"mediaURL\":\"\"}}", + "approved_script_label": "teacherEditionTips", + "component_label": "windowShade", + "approved_script": { + "name": "Teacher Edition", + "url": "https://teacher-edition-tips-plugin.concord.org/version/v3.6.0/plugin.js", + "label": "teacherEditionTips", + "description": "This plugin provides Teacher Edition components", + "version": 3, + "json_url": "https://teacher-edition-tips-plugin.concord.org/version/v3.6.0/manifest.json", + "authoring_metadata": "{\"components\":[{\"label\":\"windowShade\",\"name\":\"Window Shades\",\"scope\":\"embeddable\",\"guiAuthoring\":true},{\"label\":\"sideTip\",\"name\":\"Side Tips\",\"scope\":\"embeddable\",\"guiAuthoring\":true},{\"label\":\"questionWrapper\",\"name\":\"Question Wrapper\",\"scope\":\"embeddable-decoration\",\"decorates\":[\"Embeddable::MultipleChoice\",\"Embeddable::OpenResponse\",\"Embeddable::ImageQuestion\",\"ManagedInteractive\",\"MwInteractive\",\"ImageInteractive\",\"VideoInteractive\"],\"guiAuthoring\":true,\"guiPreview\":true}]}" + } + }, + "is_hidden": false, + "is_full_width": true, + "type": "Embeddable::EmbeddablePlugin", + "ref_id": "4237-Embeddable::EmbeddablePlugin" + }, + "section": null + }, { + "embeddable": { + "plugin": { + "description": null, + "author_data": "{\"tipType\":\"windowShade\",\"windowShade\":{\"windowShadeType\":\"discussionPoints\",\"layout\":\"mediaLeft\",\"initialOpenState\":true,\"content\":\"###What Are Common Student Ideas and What Supports Could Help Students?\\nBelow are some issues to consider in assessing students\u2019 ideas, and some suggestions of ways to support students in developing more formal reasoning about decomposition.\\n\\n###Less Formal Ideas\\n\u2022\\t**Alex\u2019s response (3 feet by 3 feet chunks)** is probably too small for this problem. A model decomposed into cells of this size over the state of Alaska would require a very large amount of interpolation because, of course, there are not that many weather stations available to provide observed data for each cell (although satellites could potentially collect this data over land surfaces). Assuming data come from weather stations though, a model composed of one square yard sized cells would provide a false level of accuracy based on an insufficient amount of data for understanding weather at that scale. In addition, this model would require a great deal of computing power. It would take a lot of time and energy for the model to process all the data, and because so much of the data will need to be interpolated, the results will not really be trustworthy at the scale of one square yard.\\n\\nSome students might find Alex\u2019s response appealing because they think it is important to be very accurate with a computer model and/or because they think computer models have the capacity to make very accurate predictions. These students could use support in understanding that computer model outputs are based on computer model inputs. With relatively few data inputs from weather stations compared to the outputs (predictions at the level of each square yard. Alex\u2019s model will not be able to perform very well. \\n\\n\u2022\\t**Sage\u2019s response (200 miles by 200 miles chunks)** will not provide enough detail for Alaskans to make the decisions they need to make related to the weather. The map below shows an area of about 200 by 200 miles. If this area were used for the weather model, then it would not be possible to give people in Port Lay a separate weather prediction than people in Utqiagvik. While Alex and Delana\u2019s responses have problems with false accuracy, Sage\u2019s response has problems with insufficient precision for the real-world problem (predicting the weather at a scale that will be useful for people in different villages and towns). \\n\\nStudents who choose Sage\u2019s response may think there is a need to enter actual data (i.e., from a weather station) for every cell in a computer model. These students could benefit from discussions that connect this assessment probe to the idea of interpolation \u2013 we don\u2019t necessarily need to enter data for every single cell in a computer model. Much of the data can be interpolated. If we didn\u2019t have the capacity to interpolate data, then Sage would be right, - it would be a whole lot of work to make a computer model for Alaska, even at the scale of 20 by 20 mile cells. Interpolation helps solve this problem (within limits of course, because if we interpolate too much data we end up with the problems associated with Alex\u2019s and Delana\u2019s models). \\n\\n\u003Cimg src=\\\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/200x200milechunkofAlaska.png\\\" width=\\\"300\\\" height=\\\"300\\\" /\u003E\\n\\n\\n###Middle Level \\n\u2022\\t**Delana\u2019s response (1 mile by 1 mile chunks)** is also probably too small for the problem. There would be approximately 663,000 cells in this model. Because of the number of cells, a lot of the data for this model would need to be interpolated. There is not necessarily a need for weather information at this fine-grained scale. While less so than Alex\u2019s response, this model would still have problems with too much interpolation leading to a false level of accuracy at the square mile scale and an excessive amount of computing power needed.\\n\\nDelana\u2019s response shows that she\u2019s doing important thinking about the scale of information that is needed by the audience for the model (i.e., people living in villages and towns). Students often think about computer models and their outputs in terms of what can be shown or seen. While visualizations are an important output of computer models, students can also use support in developing deeper understandings about the need for sufficient data and appropriate processing algorithms for a computer model to show something. Students often think about computer models as black boxes that do something mysterious and then provide an answer. Over the course of the unit, students should develop deeper understanding of how data and rules (algorithms) are the guts of the computer model that help modelers use the model to explain and predict things like weather. \\n\\n\\n###More Formal Ideas\\n\u2022\\t**Kalin\u2019s answer (20 miles by 20 miles chunks)** provides the ability to process data at a reasonable scale for an area as large as the state of Alaska. There would be approximately 1650 cells in this model. If the chunks were much bigger, it would not be possible to process and provide information at a small enough scale for what is needed in terms of weather information for individual villages, towns, and cities. If the chunks were much smaller, they would be subject to the same problems associated with Alex\u2019s and Delana\u2019s responses.\\n\",\"content2\":\"\",\"mediaType\":\"none\",\"mediaCaption\":\"Last, First. \\\"Title of Work.\\\" Year created. Site Title [OR] Publisher. 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As weather scientists, you will explore a new component of the\u0026nbsp;weather\u0026nbsp;- wind! The direction of the wind can give you clues about what\u0026nbsp;weather\u0026nbsp;to expect. And when the wind changes its direction drastically, interesting\u0026nbsp;weather\u0026nbsp;events can happen.\u003C/p\u003E\n\u003Cp\u003E\u003Cbr /\u003EIn this lesson you will explore how air masses interact by\u0026nbsp;setting up a wind table. You will also revisit weather station data and radar maps you used in Lesson 1 with some additions: wind data and five more\u0026nbsp;weather\u0026nbsp;stations. In your Science Notebook, go to Lesson 5 to locate the following information:\u0026nbsp;\u003Cbr /\u003E\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; 0 Map with Additional Weather Stations and Data Tables\u0026nbsp;\u003Cbr /\u003E\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; 0 Alaskan Stations 7 pm Readings \u003Cbr /\u003E\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; 0 Alaskan Stations 7 pm Interpolated Map\u003Cbr /\u003E\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;0 Alaskan Stations 7 am Interpolated Map\u003Cbr /\u003E\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u003C/p\u003E", + "is_callout": false, + "is_full_width": true, + "is_hidden": false, + "name": "", + "type": "Embeddable::Xhtml", + "ref_id": "272919-Embeddable::Xhtml" + }, + "section": "header_block" + }, { + "embeddable": { + "plugin": { + "description": "", + "author_data": "{\"tipType\":\"windowShade\",\"questionWrapper\":{\"correctExplanation\":\"correct\",\"distractorsExplanation\":\"distractor\",\"exemplar\":\"exemplar\",\"teacherTip\":\"teacherTip\",\"teacherTipImageOverlay\":\"\"},\"windowShade\":{\"windowShadeType\":\"theoryAndBackground\",\"layout\":\"mediaLeft\",\"initialOpenState\":false,\"content\":\"###LESSON 5: IDENTIFYING AIR MASSES\\n\\n**WHERE DOES THE AIR COME FROM?**\\n\\nIn this lesson, students investigate the role that wind plays in determining the weather and are introduced to ways to identify and define an air mass. Air masses have a similar range of weather variables (temperature and moisture), have indistinct boundaries, and are categorized by the range of weather variables within them. The air within an air mass is constantly moving and precipitation can occur where air from different air masses mixes/interacts. Scientists use models to predict where precipitation will occur based on where different air masses interact, the type of air in each, and the movement of that air.\\n\\nTo begin to identify air masses, students will do a hands-on wind table activity, and get new temperature, air moisture content, and wind direction data for five additional weather stations. As in Lesson 4, the students once again construct a set of rules through a series of activities that allow them to uncover patterns in the data, investigate the mechanisms for these patterns, and abstract a rule that describes the relationship between wind direction, its associated air mass, and the resulting precipitation. \\n\\n###LEARNING GOALS\\nStudents will be able to:\\n\\n* Identify and define an air mass\\n\\n* Explain that air masses are defined by where they come from\\n\\n* Explain the role of wind in weather events\\n\\n* Identify where on a map two different masses are interacting/mixing\\n\\n* Develop a rule for how wind moves and test the rule with multiple kinds of air masses\\n\\n* Develop a rule to express the relationship between weather components (temperature and moisture) and air masses\\n\\nComputational Thinking (CT) skills introduced in this lessons can be found in the table below:\\n\\n| CT Skill | Definition |\\n|---------------------|---------------------------------------------------------------------------------------------------|------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|\\n| Pattern Recognition | Recognizing that data or information is repeating in a logical (expected) way |\\n| Rule Abstraction | Developing a statement of how things work based on the patterns you observed |\\n| Rule Testing | Investigating whether a rule will still be true in different situations |\\n| Rule Refinement | Modifying a rule to be more precise (exact, careful about details) to work in the model |\",\"content2\":\"\",\"mediaType\":\"none\",\"mediaCaption\":\"Last, First. \\\"Title of Work.\\\" Year created. 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(25 mins)\\n\\n* Post-Assessment - What Are the Rules for Fronts and Precipitation? (10 mins)\\n\\n###MATERIALS AND SET-UP\\n\\nActivity 1 - What is an Air Mass?\\n\\nPer Research Team:\\n\\n* Direct students to Lesson 5 in their Science Notebooks to find the following information:\\n * Lesson 5, Activity 1: Wind Table Instructions and Questions\\n * Lesson 5, Activity 2: Additional Weather Station Data\\n * Lesson 5, Activity 2: Weather Stations 7 pm Readings\\n * Lesson 5, Activity 2: Weather Stations 7 pm Interpolated\\n * Lesson 5, Activity 2: 7 pm Weather Station Data and 7 pm Radar Map\\n * Lesson 5, Activity 2: 7 am Weather Station Data \\n\\nPer Class:\\n\\n* Set up on one demonstration table that students can gather around: a wind fan, a piece of paper with a wind rose taped to the table, and a single weather vane. See below for a top-down view. \\n\\n\u003Cimg src=\\\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/Lesson5WIndTablesTopDownView1.jpg\\\" width=\\\"400\\\" height=\\\"350\\\"\u003E\\n\\n* To print the wind rose, click [here](https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/WindCompass.jpg) to download. \",\"content2\":\"\",\"mediaType\":\"none\",\"mediaCaption\":\"Last, First. \\\"Title of Work.\\\" Year created. Site Title [OR] Publisher. Gallery [OR] Location. http://www.url.com.\",\"mediaURL\":\"\"}}", + "approved_script_label": "teacherEditionTips", + "component_label": "windowShade", + "approved_script": { + "name": "Teacher Edition", + "url": "https://teacher-edition-tips-plugin.concord.org/version/v3.6.0/plugin.js", + "label": "teacherEditionTips", + "description": "This plugin provides Teacher Edition components", + "version": 3, + "json_url": "https://teacher-edition-tips-plugin.concord.org/version/v3.6.0/manifest.json", + "authoring_metadata": "{\"components\":[{\"label\":\"windowShade\",\"name\":\"Window Shades\",\"scope\":\"embeddable\",\"guiAuthoring\":true},{\"label\":\"sideTip\",\"name\":\"Side Tips\",\"scope\":\"embeddable\",\"guiAuthoring\":true},{\"label\":\"questionWrapper\",\"name\":\"Question Wrapper\",\"scope\":\"embeddable-decoration\",\"decorates\":[\"Embeddable::MultipleChoice\",\"Embeddable::OpenResponse\",\"Embeddable::ImageQuestion\",\"ManagedInteractive\",\"MwInteractive\",\"ImageInteractive\",\"VideoInteractive\"],\"guiAuthoring\":true,\"guiPreview\":true}]}" + } + }, + "is_hidden": false, + "is_full_width": true, + "type": "Embeddable::EmbeddablePlugin", + "ref_id": "4227-Embeddable::EmbeddablePlugin" + }, + "section": null + }, { + "embeddable": { + "plugin": { + "description": null, + "author_data": "{\"tipType\":\"windowShade\",\"windowShade\":{\"windowShadeType\":\"framing\",\"layout\":\"mediaLeft\",\"initialOpenState\":true,\"content\":\"Watch this video with your class to give students a perspective on the importance of weather and to build weather science career awareness.\",\"content2\":\"\",\"mediaType\":\"video\",\"mediaCaption\":\"Purcell, Jackie. \\\"Lesson 5.\\\" 2019. Good Life Productions. Anchorage, AK.\",\"mediaURL\":\"https://precipitatingchange-resources.concord.org/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/JackieLesson5_88.mp4\"}}", + "approved_script_label": "teacherEditionTips", + "component_label": "windowShade", + "approved_script": { + "name": "Teacher Edition", + "url": "https://teacher-edition-tips-plugin.concord.org/version/v3.6.0/plugin.js", + "label": "teacherEditionTips", + "description": "This plugin provides Teacher Edition components", + "version": 3, + "json_url": "https://teacher-edition-tips-plugin.concord.org/version/v3.6.0/manifest.json", + "authoring_metadata": "{\"components\":[{\"label\":\"windowShade\",\"name\":\"Window Shades\",\"scope\":\"embeddable\",\"guiAuthoring\":true},{\"label\":\"sideTip\",\"name\":\"Side Tips\",\"scope\":\"embeddable\",\"guiAuthoring\":true},{\"label\":\"questionWrapper\",\"name\":\"Question Wrapper\",\"scope\":\"embeddable-decoration\",\"decorates\":[\"Embeddable::MultipleChoice\",\"Embeddable::OpenResponse\",\"Embeddable::ImageQuestion\",\"ManagedInteractive\",\"MwInteractive\",\"ImageInteractive\",\"VideoInteractive\"],\"guiAuthoring\":true,\"guiPreview\":true}]}" + } + }, + "is_hidden": false, + "is_full_width": true, + "type": "Embeddable::EmbeddablePlugin", + "ref_id": "4228-Embeddable::EmbeddablePlugin" + }, + "section": null + }] + }, { + "additional_sections": null, + "embeddable_display_mode": "stacked", + "id": 308623, + "is_completion": false, + "is_hidden": false, + "layout": "l-full-width", + "name": " Activity 1 - What is an air mass?", + "position": 2, + "show_header": true, + "show_info_assessment": true, + "show_interactive": false, + "show_sidebar": false, + "sidebar": null, + "sidebar_title": "Did you know?", + "toggle_info_assessment": false, + "embeddables": [{ + "embeddable": { + "content": "\u003Cp\u003E\u003Cstrong\u003EMeasuring Wind with the Compass\u0026nbsp;\u003C/strong\u003E\u003C/p\u003E\n\u003Cp\u003EOne way wind direction\u0026nbsp;can be measured is with\u0026nbsp;a weather\u0026nbsp;vane or air socks. When the wind blows, the\u0026nbsp;weather\u0026nbsp;vane rotates and lines up with the path the air is flowing. So,\u0026nbsp;wind direction\u0026nbsp;is determined by what direction the wind is blowing and measured in degrees (\u0026deg;).\u003C/p\u003E\n\u003Cp\u003E\u003Cimg class=\"\" style=\"display: block; margin-left: auto; margin-right: auto;\" src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/WindCompass.jpg\" alt=\"\" width=\"323\" height=\"328\" /\u003E\u003C/p\u003E\n\u003Cp\u003EIn this activity, you will use a Wind Table to map the movement of air on a grid representing a region in Alaska. Go to your Science Notebooks, Lesson 5, page 21, for further instructions and to record your observations.\u003C/p\u003E\n\u003Cp\u003E\u003Cstrong\u003EWind Table\u003C/strong\u003E\u003C/p\u003E\n\u003Cp\u003E\u003Cimg style=\"display: block; margin-left: auto; margin-right: auto;\" src=\"https://precipitatingchange-resources.concord.org/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/WindTunnels.png\" width=\"576\" height=\"510\" /\u003E\u003C/p\u003E\n\u003Cp\u003E\u0026nbsp;\u003C/p\u003E", + "is_callout": false, + "is_full_width": true, + "is_hidden": false, + "name": "", + "type": "Embeddable::Xhtml", + "ref_id": "272920-Embeddable::Xhtml" + }, + "section": "header_block" + }, { + "embeddable": { + "plugin": { + "description": "", + "author_data": "{\"tipType\":\"windowShade\",\"questionWrapper\":{\"correctExplanation\":\"correct\",\"distractorsExplanation\":\"distractor\",\"exemplar\":\"exemplar\",\"teacherTip\":\"teacherTip\",\"teacherTipImageOverlay\":\"\"},\"windowShade\":{\"windowShadeType\":\"theoryAndBackground\",\"layout\":\"mediaLeft\",\"initialOpenState\":false,\"content\":\"\\n###Activity 1 - **What is an Air Mass?**\\nIn this activity students explore the patterns of air movement within and between air masses. Using a hands-on \u201cwind table,\u201d they engage in a tangible interaction with wind. By leveraging patterns from the previous activity dataset and the wind table, they will discover that when two air masses meet, the air converges. Weather scientists refer to these regions as fronts. \\n\\n###Wind Table Directions\\n * **1.Introduce the Wind Table.** Wind is one of the first things that atmospheric scientists look at when investigating the weather, but it can be difficult to understand by just looking at data and maps. A hands-on model is helpful to investigate a phenomenon like the wind.\\n\\n\\n * **2.Assign teams:** Assign research teams a Wind Table position number, either #1 or #2. \\n * **3.Wind tunnel position:** Have students place wind tunnel #1 and wind tunnel #2 according to the diagram in their Science Notebook for their assigned Team #.\\n * **4.Reminders:** Read over the things to keep in mind on page 21 in the Science Notebook, together as a class:\\n * **BE CAREFUL NOT TO PUT YOUR FINGERS NEAR THE FAN**\\n * Graph paper represents a region.\\n * A wind vane can be placed anywhere on the graph paper to determine what direction the wind is coming from.\\n * Record the wind direction by drawing an arrow in the direction the wind vane is pointing. (Recall that wind is always recorded showing the direction the wind is coming from.) If there is not a clear determination where the wind is coming from, then leave the square blank.\\n * Place a Styrofoam ball on the wind table to see the interaction between the two air masses.\\n * **5.Analyze air mass interactions** \\n\\n * Once all of the groups have finished mapping the wind direction, ask the students to determine the boundary of the two air masses by drawing a circle around the different air masses. \\n\\n * Ask the students if there was anywhere on the grid that they either had trouble deciding what direction to draw their arrow. Some students might remark that the wind vane wobbles or spins in the region between the two distinct air masses. Instruct the students to identify the diagonal region between the two air masses and circle this area with a green marker. \\n\\n* **6.Connecting the Wind Table to the interpolated map.** Ask students to compare Alaska Weather Stations: 7 pm Interpolated data with the wind map they created on their Wind Table. Lead a class conversation. See possible Discussion Points below. \\n\",\"content2\":\"\",\"mediaType\":\"none\",\"mediaCaption\":\"Last, First. \\\"Title of Work.\\\" Year created. Site Title [OR] Publisher. 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(Note that scientists also include pressure, but pressure is not covered in this unit.)\\n\\n###Wind Table Demonstration \\nThe compass rose describes the direction the wind is blowing in degrees. Wind coming directly from the South has a direction of 180\u00b0, from the East 90\u00b0, from the North 360\u00b0, etc. Place the fan to the \u201cNorth\u201d of the weather vane and turn it on. Move the weather vane so that it's at the center of the rose and have students read the wind direction from the rose. Then, move the fan to other locations. Ask students where you should move the fan to get a wind direction of, for example, 180\u00b0, 90\u00b0, 45\u00b0, etc. Move the fan to check their predictions. \\n\\n**Teacher Note:** Wind direction is determined by what direction the wind is coming from. This is a consequence of how it is measured. A weather scientist says, \u201cwinds coming from the northeast\u201d not \u201cwinds heading southwest.\u201d This distinction becomes very important when trying to map the flow of air over a region.\",\"content2\":\"\",\"mediaType\":\"none\",\"mediaCaption\":\"Last, First. \\\"Title of Work.\\\" Year created. Site Title [OR] Publisher. 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(continued)", + "position": 3, + "show_header": true, + "show_info_assessment": true, + "show_interactive": false, + "show_sidebar": false, + "sidebar": null, + "sidebar_title": "Did you know?", + "toggle_info_assessment": false, + "embeddables": [{ + "embeddable": { + "content": "\u003Cp\u003EIDENTIFYING AIR MASSES\u003C/p\u003E\n\u003Cp\u003EIn Lesson 5 of your Science Notebook on pages 21-23, you have additional data weather station data and maps that show you the direction of the wind. On page 22, you will find a map that shows you the 7 pm reading from the additional weather stations. The arrows on the map represent the\u0026nbsp;wind direction. The data on page 23 of your Science Notebook, \"Weather Stations 7 pm Interpolated\" comes from an\u0026nbsp;interpolation\u0026nbsp;of wind direction\u0026nbsp;across the mainland of Alaska at 7 pm. See map below. Using the map on page 23, draw a line that splits the map into two parts: one section with the wind coming from the same direction and the other section with the wind coming from a different direction. It is your job to determine where you see that change in the\u0026nbsp;wind direction.\u003C/p\u003E\n\u003Cp\u003EStrategy for Identifying Two Air Masses:\u003C/p\u003E\n\u003Cp\u003E1. Make Sense of the Map:\u0026nbsp;\u003Cbr /\u003E\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026bull; Look at each row and see if the arrows change direction as you move across the row.\u0026nbsp;\u003Cbr /\u003E\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026bull; Look at each column and see if the arrows change direction as you move down the column.\u0026nbsp;\u003Cbr /\u003E2. Identify where you are going to place your line.\u0026nbsp;\u003Cbr /\u003E3. 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(continued)", + "position": 4, + "show_header": true, + "show_info_assessment": true, + "show_interactive": false, + "show_sidebar": false, + "sidebar": null, + "sidebar_title": "Did you know?", + "toggle_info_assessment": false, + "embeddables": [{ + "embeddable": { + "content": "\u003Cp\u003EThe line that you drew across your map represents a boundary between two\u0026nbsp;air masses. An air mass is a body of air with similar temperature and\u0026nbsp;air moisture\u0026nbsp;content. Identifying air masses and their properties is an important part of the work of atmospheric scientists. On the map you may have noticed a temperature number at the top of the square and an\u0026nbsp;air moisture\u0026nbsp;content number at the bottom of the square.\u003C/p\u003E\n\u003Cp\u003E\u003Cimg style=\"display: block; margin-left: auto; margin-right: auto;\" src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/TempMoisture.jpg\" width=\"212\" height=\"292\" /\u003E\u003C/p\u003E", + "is_callout": false, + "is_full_width": true, + "is_hidden": false, + "name": "", + "type": "Embeddable::Xhtml", + "ref_id": "272922-Embeddable::Xhtml" + }, + "section": "header_block" + }, { + "embeddable": { + "content": "\u003Cp\u003EDevelop a way to define the two air masses using the temperature and\u0026nbsp;air moisture\u0026nbsp;content values provided on the Alaskan Stations: Interpolated at 7 pm Map.\u003C/p\u003E\r\n\u003Cp\u003E\u003Cimg 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Sometimes this change is very sudden.\u003C/p\u003E", + "is_callout": false, + "is_full_width": true, + "is_hidden": false, + "name": "", + "type": "Embeddable::Xhtml", + "ref_id": "272924-Embeddable::Xhtml" + }, + "section": "header_block" + }, { + "embeddable": { + "content": "\u003Cp\u003EGo to page 24 in your Science Notebook and compare the 7 pm interpolated map and the 7 pm radar map.\u003C/p\u003E\r\n\u003Cp\u003E\u003Cimg class=\"\" src=\"https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/Lesson5_7pmInterpolatedRADARMAPcomparison.jpg\" alt=\"\" width=\"860\" height=\"300\" /\u003E\u003C/p\u003E\r\n\u003Cp\u003EDiscuss with your research team and write a general statement that answers the question, \u0026ldquo;How do air masses affect where it rains?\"\u0026nbsp;\u0026nbsp;\u003C/p\u003E\r\n\u003Cp\u003E\u0026nbsp;\u003C/p\u003E", + "is_callout": true, + "is_full_width": true, + "is_hidden": false, + "name": "TASK", + "type": "Embeddable::Xhtml", + "ref_id": "272925-Embeddable::Xhtml" + }, + "section": null + }, { + "embeddable": { + "name": "", + "url_fragment": null, + "authored_state": "{\"version\":1,\"prompt\":\"\u003Cp\u003EHow do air masses affect where it rains?\u003C/p\u003E\",\"defaultAnswer\":\"\",\"required\":false,\"questionType\":\"open_response\",\"hint\":\"\u003Cp\u003E\u0026bull; Where is the front? 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Sometimes it feels cold; sometimes it feels warm. The wind is what moves air. Weather scientists use\u0026nbsp;wind direction\u0026nbsp;to distinguish multiple air masses. What happens at the boundary of those two air masses? You will explore that question using a new Virtual Model. \u0026nbsp;\u003C/p\u003E", + "is_callout": false, + "is_full_width": true, + "is_hidden": false, + "name": "", + "type": "Embeddable::Xhtml", + "ref_id": "272928-Embeddable::Xhtml" + }, + "section": "header_block" + }, { + "embeddable": { + "content": "\u003Cp\u003EThis model shows wind as moving arrowheads and precipitation as green circles. There are two air masses. 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Virtual Model\\n\\n**Objective:** To build students\u2019 rule refinement skills by experimenting with a model to figure out its built-in weather rules. In this model, precipitation falls under a variety of conditions that can be set by changing temperatures and moisture for two air masses. \\n\\nStudents can vary the temperature and moisture of two air masses in order to better understand how interacting air masses create patterns of rain at a front. Through this process, students will come up with an even more robust rule for predicting rain that involves interacting air masses. The specific computational thinking practice highlighted and practiced in this activity is **Rule Refinement**.\\n\\n**1. Class discussion about air mass properties.**Use the Alaska Weather Stations: 7am Interpolated map! [](https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/Lesson5AirMasses1and2.jpg) to remind students of the properties of the air masses in their regional weather system. See Discussion Points below for possible prompts. \\n\\n**2. Set up the model challenge.** \\n\\n* Have students recall the rule they developed to answer the question \u201cHow do air masses affect where it rains?\u201d \\n\\n* Students will use the Lesson 5 virtual model to help refine their rule.\\n\\n**3. Exploring the Virtual Model.** \\n\\nIntroduce the task, and give students time to explore the model. Then let them tell you what they discovered. They may notice:\\n\\n * The properties of the incoming air can be changed using the sliders on the left and bottom.\\n\\n * The direction of the wind can be seen with arrows and trails that can be turned on or off.\\n\\n * Precipitation appears as green circles with bigger circles meaning heavier rain.\\n\\n * Color of arrows correspond to temperature (Red = Warm, Blue = Cold, Purple = In Between)\\n\\n * Size of arrows correspond to air moisture (Small = dry, Large = moist or humid)\\n\\nYou may want to point out that\\n\\n * Even though the air in the model moves, the model shows airflow for a certain time. Time does not change.\\n\\n**4. Experiment with the Model to find the Rule**\\n\\nTell students that this model has a built-in rule for precipitation made by the model\u2019s programmer. Students\u2019 challenge is to discover the rule by experimenting with the model. \\n\\n * Students may find it helpful to express their experiments comparing warmer or colder temperatures and moister or drier moisture values instead of specific temperatures or air moisture values.\\n\\n * Give students time to play with the model and record their understanding of the model rule design in the questions that follow.\\n\\nNOTE: This is a fairly sophisticated weather model. Don\u2019t expect that students will discover the full precipitation rule. However, students should discover that the front runs up from the southwestern corner through Bethel and Anchorage with one air mass coming down from the northwest and the other up from the south and southwest. They may discover that generally, precipitation occurs along the front if there is a difference in temperature between the two air masses, and tends to form on the warmer side of the front. 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"https://project-resources.concord.org/precipitatingchange/audio/Athabaskan/Xidetriyh_it_is_windy.mp3", + "https://project-resources.concord.org/precipitatingchange/audio/Athabaskan/Xiyhtuxiyoth_It_snows_during_the_winter.mp3", + "https://project-resources.concord.org/precipitatingchange/videos/AbstractionMovie.mp4", + "https://project-resources.concord.org/precipitatingchange/videos/Aggregation.mp4", + "https://project-resources.concord.org/precipitatingchange/videos/PatternRecognition.mp4", + "https://project-resources.concord.org/precipitatingchange/videos/WindDirection.mp4", + "https://project-resources.concord.org/precipitatingchange/videos/moisture-amount.mp4", + "https://project-resources.concord.org/precipitatingchange/videos/precipitation_snow_v2.mp4", + "https://project-resources.concord.org/precipitatingchange/videos/weather-movie.mp4", + "https://project-resources.concord.org/test-project/Big_Buck_Bunny_360_10s_1MB.mp4", + "https://project-resources.concord.org/test-project/Big_Buck_Bunny_360_10s_1MB.mp4\n", + "https://www.thelabradorsite.com/wp-content/uploads/2016/05/6t.jpg", + "models-resources/question-interactives/version/v1.2.0-pre.1/carousel/", + "models-resources/question-interactives/version/v1.2.0-pre.1/carousel/assets/index.4625e4716a2dfe8f0462.css", + "models-resources/question-interactives/version/v1.2.0-pre.1/carousel/assets/index.4625e4716a2dfe8f0462.js", + "models-resources/question-interactives/version/v1.2.0-pre.1/drag-and-drop/", + "models-resources/question-interactives/version/v1.2.0-pre.1/drag-and-drop/assets/index.4625e4716a2dfe8f0462.css", + "models-resources/question-interactives/version/v1.2.0-pre.1/drag-and-drop/assets/index.4625e4716a2dfe8f0462.js", + "models-resources/question-interactives/version/v1.2.0-pre.1/drawing-tool/", + "models-resources/question-interactives/version/v1.2.0-pre.1/drawing-tool/assets/index.4625e4716a2dfe8f0462.css", + "models-resources/question-interactives/version/v1.2.0-pre.1/drawing-tool/assets/index.4625e4716a2dfe8f0462.js", + "models-resources/question-interactives/version/v1.2.0-pre.1/fill-in-the-blank/", + "models-resources/question-interactives/version/v1.2.0-pre.1/fill-in-the-blank/assets/index.4625e4716a2dfe8f0462.css", + "models-resources/question-interactives/version/v1.2.0-pre.1/fill-in-the-blank/assets/index.4625e4716a2dfe8f0462.js", + "models-resources/question-interactives/version/v1.2.0-pre.1/graph/", + "models-resources/question-interactives/version/v1.2.0-pre.1/graph/assets/index.4625e4716a2dfe8f0462.css", + "models-resources/question-interactives/version/v1.2.0-pre.1/graph/assets/index.4625e4716a2dfe8f0462.js", + "models-resources/question-interactives/version/v1.2.0-pre.1/image-question/", + "models-resources/question-interactives/version/v1.2.0-pre.1/image-question/assets/index.4625e4716a2dfe8f0462.css", + "models-resources/question-interactives/version/v1.2.0-pre.1/image-question/assets/index.4625e4716a2dfe8f0462.js", + "models-resources/question-interactives/version/v1.2.0-pre.1/image/", + "models-resources/question-interactives/version/v1.2.0-pre.1/image/assets/index.4625e4716a2dfe8f0462.css", + "models-resources/question-interactives/version/v1.2.0-pre.1/image/assets/index.4625e4716a2dfe8f0462.js", + "models-resources/question-interactives/version/v1.2.0-pre.1/multiple-choice/", + "models-resources/question-interactives/version/v1.2.0-pre.1/multiple-choice/assets/index.4625e4716a2dfe8f0462.css", + "models-resources/question-interactives/version/v1.2.0-pre.1/multiple-choice/assets/index.4625e4716a2dfe8f0462.js", + "models-resources/question-interactives/version/v1.2.0-pre.1/open-response/", + "models-resources/question-interactives/version/v1.2.0-pre.1/open-response/assets/index.4625e4716a2dfe8f0462.css", + "models-resources/question-interactives/version/v1.2.0-pre.1/open-response/assets/index.4625e4716a2dfe8f0462.js", + "models-resources/question-interactives/version/v1.2.0-pre.1/scaffolded-question/", + "models-resources/question-interactives/version/v1.2.0-pre.1/scaffolded-question/assets/index.4625e4716a2dfe8f0462.css", + "models-resources/question-interactives/version/v1.2.0-pre.1/scaffolded-question/assets/index.4625e4716a2dfe8f0462.js", + "models-resources/question-interactives/version/v1.2.0-pre.1/video-player/", + "models-resources/question-interactives/version/v1.2.0-pre.1/video-player/assets/index.4625e4716a2dfe8f0462.css", + "models-resources/question-interactives/version/v1.2.0-pre.1/video-player/assets/index.4625e4716a2dfe8f0462.js", + "models-resources/vortex/version/v1.3.0/lara-app/assets/index.ec7bceae2a203a9db004.css", + "models-resources/vortex/version/v1.3.0/lara-app/index.html" + ] +} diff --git a/src/public/offline-manifests/staging-precipitating-change-v1.json b/src/public/offline-manifests/staging-precipitating-change-v1.json new file mode 100644 index 00000000..1631a917 --- /dev/null +++ b/src/public/offline-manifests/staging-precipitating-change-v1.json @@ -0,0 +1,86 @@ +{ + "name": "Precipitating Change Offline Manifest", + "activities": [ + { + "name": "Lesson 4 Pre", + "contentUrl": "offline-activities/staging-precipitating-change/lesson-4-pre-v1.json", + "resourceUrl": "https://authoring.staging.concord.org/activities/20955" + }, + { + "name": "Lesson 4", + "contentUrl": "offline-activities/staging-precipitating-change/lesson-4-v1.json", + "resourceUrl": "https://authoring.staging.concord.org/activities/20956" + }, + { + "name": "Lesson 4 Post", + "contentUrl": "offline-activities/staging-precipitating-change/lesson-4-post-v1.json", + "resourceUrl": "https://authoring.staging.concord.org/activities/20957" + }, + { + "name": "Lesson 5 Pre", + "contentUrl": "offline-activities/staging-precipitating-change/lesson-5-pre-v1.json", + "resourceUrl": "https://authoring.staging.concord.org/activities/20954" + }, + { + "name": "Lesson 5", + "contentUrl": "offline-activities/staging-precipitating-change/lesson-5-v1.json", + "resourceUrl": "https://authoring.staging.concord.org/activities/20953" + }, + { + "name": "Lesson 5 Post", + "contentUrl": "offline-activities/staging-precipitating-change/lesson-5-post-v1.json", + "resourceUrl": "https://authoring.staging.concord.org/activities/20952" + } + ], + "cacheList": [ + "https://activity-player-offline.concord.org/icons/apple-icon-144x144.png", + "https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/1milex1mile.png", + "https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/200milesx200miles.png", + "https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/20milesx20miles.png", + "https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/3ftx3ft.png", + "https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/Alaska200grid.jpg", + "https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/Alex4.png", + "https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/Alex5.png", + "https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/Delana4.png", + "https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/Delana5.png", + "https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/Kalin5.png", + "https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/Kalin6.png", + "https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/L1AKRADARMAPAPRIL22_7am.png", + "https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/L4_ACT1_Alaska%20Weather%20Stations_7am%20Interpolated.png", + "https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/Lesson4NWImage.png", + "https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/Lesson4RuleRefinementABCquestionRVSD", + "https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/Lesson4StormTracker7pm.png", + "https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/Lesson57pmInterpolated.jpg", + "https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/Lesson5AirMasses1and2.jpg", + "https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/Lesson5_7pmInterpolatedRADARMAPcomparison.jpg", + "https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/RuleStatement.jpg", + "https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/TempMoisture.jpg", + "https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/WeatherMAPB.jpg", + "https://cc-project-resources.s3.amazonaws.com/precipitatingchange/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/WindCompass.jpg", + "https://cc-project-resources.s3.amazonaws.com/precipitatingchange/Sage2.png", + "https://cc-project-resources.s3.amazonaws.com/precipitatingchange/Sage3.png", + "https://cc-project-resources.s3.amazonaws.com/precipitatingchange/images/air-moisture-scale.png", + "https://code.jquery.com/ui/1.12.1/themes/base/jquery-ui.css", + "https://fonts.googleapis.com/css2?family=Lato:wght@400;700;900&display=swap", + "https://fonts.googleapis.com/css?family=Lato", + "https://fonts.gstatic.com/s/lato/v17/S6u9w4BMUTPHh50XSwiPGQ3q5d0.woff2", + "https://fonts.gstatic.com/s/lato/v17/S6u9w4BMUTPHh6UVSwiPGQ3q5d0.woff2", + "https://fonts.gstatic.com/s/lato/v17/S6uyw4BMUTPHjx4wXiWtFCc.woff2", + "https://learn-resources.concord.org/images/stem-resources/icons/pc-lesson1.png", + "https://learn-resources.concord.org/images/stem-resources/icons/pc-lesson3.png", + "https://learn-resources.concord.org/images/stem-resources/icons/pc-lesson4.jpg", + "https://precipitatingchange-resources.concord.org/2019_20_Curriculum_%20Documents/PrecipitatingChangeClassHandouts-AK/WindTunnels.png", + "models-resources/precip-models/ak-base-map-with-rose.png", + "models-resources/precip-models/ak-w-cities.png", + "models-resources/precip-models/lesson-4-ak-v3.html", + "models-resources/precip-models/precip-rule-ak-v5.html", + "models-resources/question-interactives/version/v1.1.0/multiple-choice/", + "models-resources/question-interactives/version/v1.1.0/multiple-choice/assets/index.43fd80fcbaa142f3b07e.css", + "models-resources/question-interactives/version/v1.1.0/multiple-choice/assets/index.43fd80fcbaa142f3b07e.js", + "models-resources/question-interactives/version/v1.1.0/open-response/", + "models-resources/question-interactives/version/v1.1.0/open-response/assets/index.43fd80fcbaa142f3b07e.css", + "models-resources/question-interactives/version/v1.1.0/open-response/assets/index.43fd80fcbaa142f3b07e.js", + "models-resources/teacher-edition-tips-plugin/version/v3.6.0/manifest.json", + "models-resources/teacher-edition-tips-plugin/version/v3.6.0/plugin.js" + ] +} diff --git a/src/scripts/update-offline-manifest.config.ts b/src/scripts/update-offline-manifest.config.ts new file mode 100644 index 00000000..df998034 --- /dev/null +++ b/src/scripts/update-offline-manifest.config.ts @@ -0,0 +1,12 @@ +// UPDATE THIS TO CHANGE HOW ACTIVITIES ARE REWRITTEN + +export const config = { + glossary: { + s3Url: "https://models-resources.s3.amazonaws.com/glossary-resources/custom-apo/alaska-v3.json", + pluginUrl: "https://glossary-plugin.concord.org/version/v3.13.0-pre.3/plugin.js", + manifestUrl: "https://glossary-plugin.concord.org/version/v3.13.0-pre.3/manifest.json" + }, + questionInteractives: { + version: "v1.2.0-pre.1" + } +}; diff --git a/src/scripts/update-offline-manifest.ts b/src/scripts/update-offline-manifest.ts new file mode 100644 index 00000000..7d17e7e5 --- /dev/null +++ b/src/scripts/update-offline-manifest.ts @@ -0,0 +1,267 @@ +import fs from "fs"; +import path from "path"; +import { Activity, OfflineManifest, OfflineManifestActivity } from "../types"; +import request from "superagent"; +import { getAllUrlsInActivity, removeDuplicateUrls, rewriteProxiableIframeUrls, + walkObject } from "../utilities/activity-utils"; +import fetch from "node-fetch"; +import { config } from "./update-offline-manifest.config"; + +interface OutputInfo { + outputManifestPath: string; + outputActivityDir: string; + createOutputDir: boolean; + sourceVersionName: string; + outputVersionName: string; +} + +// pretend to be chrome, this helps with google fonts +// might be a problem if we want to support iPad offline +// This approach was taken from here: +// https://github.com/node-fetch/node-fetch/issues/591#issuecomment-474457866 +(global as any).fetch = (url:any , args:any = {}) => { + args.headers = args.headers || {}; + args.headers["user-agent"] = "Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/89.0.4389.90 Safari/537.36"; + return fetch(url, args); +}; + +let bumpVersion = false; +let fetchActivities = true; + +const die = (message: string) => { + console.error(message); + process.exit(1); +}; + +const getManifestPath = () => { + const args = process.argv.slice(2); + const options = args.filter(arg => /--/.test(arg)); + const nonOptions = args.filter(arg => options.indexOf(arg) === -1); + + const filename = nonOptions[0]; + bumpVersion = options.indexOf("--bump-version") !== -1; + fetchActivities = !(options.indexOf("--no-fetch-activities") !== -1); + + if (!filename) { + die("Usage: npm run update-offline-manifestWrite something:
"}`, @@ -62,10 +62,7 @@ describe("Firestore", () => { }; const exportableAnswer = getAnswerWithMetadata(interactiveState, embeddable) as IExportableAnswerMetadata; - - createOrUpdateAnswer(exportableAnswer); - - expect(appMock.firestore().doc().set).not.toHaveBeenCalled(); + expect(() => createOrUpdateAnswer(exportableAnswer) ).toThrow("No portal Data"); }); it("creates answers with the correct metadata for authenticated users", () => { @@ -88,7 +85,8 @@ describe("Firestore", () => { resourceUrl: "http://example/resource", toolId: "activity-player.concord.org", userType: "learner", - runRemoteEndpoint: "https://example.com/learner/1234" + runRemoteEndpoint: "https://example.com/learner/1234", + loggingUsername: "1@example.com" }); const embeddable = { @@ -130,7 +128,7 @@ describe("Firestore", () => { }); it("creates answers with the correct metadata for an anonymous user", () => { - setAnonymousPortalData({ + setPortalData({ type: "anonymous", database: { appName: "report-service-dev", @@ -193,7 +191,7 @@ describe("Firestore", () => { describe("with anonymous portal data", () => { beforeEach(() => { - setAnonymousPortalData({ + setPortalData({ type: "anonymous", database: { appName: "report-service-dev", @@ -250,7 +248,8 @@ describe("Firestore", () => { class_info_url: "http://example.com/4", offering_id: 8 }, - runRemoteEndpoint: "http://example.com/5" + runRemoteEndpoint: "http://example.com/5", + loggingUsername: "1@example.com" }); }); diff --git a/src/firebase-db.ts b/src/storage/firebase-db.ts similarity index 78% rename from src/firebase-db.ts rename to src/storage/firebase-db.ts index 268f7220..48f2f9c6 100644 --- a/src/firebase-db.ts +++ b/src/storage/firebase-db.ts @@ -10,14 +10,18 @@ import firebase from "firebase/app"; import "firebase/auth"; import "firebase/firestore"; -import { IPortalData, IAnonymousPortalData, anonymousPortalData } from "./portal-api"; -import { refIdToAnswersQuestionId } from "./utilities/embeddable-utils"; -import { IExportableAnswerMetadata, LTIRuntimeAnswerMetadata, AnonymousRuntimeAnswerMetadata, IAuthenticatedLearnerPluginState, IAnonymousLearnerPluginState } from "./types"; -import { queryValueBoolean } from "./utilities/url-query"; -import { RequestTracker } from "./utilities/request-tracker"; +// import "firebase/database"; // TODO: add if we want to use for testing if connected +import { IPortalData, IAnonymousPortalData, anonymousPortalData } from "../portal-api"; +import { refIdToAnswersQuestionId } from "../utilities/embeddable-utils"; +import { IExportableAnswerMetadata, LTIRuntimeAnswerMetadata, AnonymousRuntimeAnswerMetadata, IAuthenticatedLearnerPluginState, IAnonymousLearnerPluginState } from "../types"; +import { queryValueBoolean } from "../utilities/url-query"; +import { RequestTracker } from "../utilities/request-tracker"; +import { docToWrappedAnswer, IWrappedDBAnswer } from "./storage-facade"; export type FirebaseAppName = "report-service-dev" | "report-service-pro"; +export const kLocalApplicationName = "activity-player"; + let portalData: IPortalData | IAnonymousPortalData | null; const answersPath = (answerId?: string) => @@ -26,11 +30,8 @@ const answersPath = (answerId?: string) => const learnerPluginStatePath = (docId: string) => `sources/${portalData?.database.sourceKey}/plugin_states/${docId}`; -export interface WrappedDBAnswer { - meta: IExportableAnswerMetadata; - interactiveState: any; -} -export type DBChangeListener = (wrappedDBAnswer: WrappedDBAnswer | null) => void; + +export type DBChangeListener = (wrappedDBAnswer: IWrappedDBAnswer | null) => void; interface IConfig { apiKey: string; @@ -82,7 +83,19 @@ let app: firebase.app.App; // preview mode will run Firestore in offline mode and clear it (as otherwise the local data is persisted). export async function initializeDB({ name, preview }: { name: FirebaseAppName, preview: boolean }) { const config = configurations[name]; - app = firebase.initializeApp(config, "activity-player"); + try { + // The API will throw an exception if the app doesn't exist yet: + // See: https://firebase.google.com/docs/reference/js/firebase.app + const existing = firebase.app(kLocalApplicationName); + if(existing) { + console.debug(`Firebase-db.ts: found existing application to use ${kLocalApplicationName}`); + app = existing; + return existing; + } + } catch { + console.debug(`Firebase-db.ts: no existing application for ${kLocalApplicationName}`); + } + app = firebase.initializeApp(config, kLocalApplicationName); // Save action seems to be failing when you try to save a document with a property explicitly set to undefined value. // `null` or empty string are fine. ActivityPlayer was not saving some interactive states because of that. @@ -128,7 +141,18 @@ export const signInWithToken = async (rawFirestoreJWT: string) => { return app.auth().signInWithCustomToken(rawFirestoreJWT); }; -export const setPortalData = (_portalData: IPortalData | null) => { +export const signOut = async() =>{ + try { + await app.auth().signOut(); + } + catch(e) { + // maybe we weren't signed in? + console.error("unable to signout from FireStore:"); + console.error(e); + } +}; + +export const setPortalData = (_portalData: IPortalData | IAnonymousPortalData | null) => { portalData = _portalData; }; @@ -138,9 +162,6 @@ export const getPortalData = (): IPortalData | IAnonymousPortalData | null => { return portalData; }; -export const setAnonymousPortalData = (_portalData: IAnonymousPortalData) => { - portalData = _portalData; -}; type DocumentsListener = (docs: firebase.firestore.DocumentData[]) => void; @@ -181,21 +202,10 @@ const watchAnswerDocs = (listener: DocumentsListener, questionId?: string) => { }); }; -const firestoreDocToWrappedAnswer = (doc: firebase.firestore.DocumentData) => { - const getInteractiveState = () => { - const reportState = JSON.parse(doc.report_state); - return JSON.parse(reportState.interactiveState); - }; - const interactiveState = getInteractiveState(); - const wrappedAnswer: WrappedDBAnswer = { - meta: doc as IExportableAnswerMetadata, - interactiveState - }; - return wrappedAnswer; -}; + // Watches ONE question answer defined by embeddableRefId. -export const watchAnswer = (embeddableRefId: string, callback: (wrappedAnswer: WrappedDBAnswer | null) => void) => { +export const watchAnswer = (embeddableRefId: string, callback: (wrappedAnswer: IWrappedDBAnswer | null) => void) => { const questionId = refIdToAnswersQuestionId(embeddableRefId); // Note that watchAnswerDocs returns unsubscribe method. return watchAnswerDocs((answers: firebase.firestore.DocumentData[]) => { @@ -209,22 +219,20 @@ export const watchAnswer = (embeddableRefId: string, callback: (wrappedAnswer: W "ActivityPlayer versions. Your data might be corrupted." ); } - callback(firestoreDocToWrappedAnswer(answers[0])); + callback(docToWrappedAnswer(answers[0])); }, questionId); // limit observer to single question }; // Watches ALL the answers for the given activity. -export const watchAllAnswers = (callback: (wrappedAnswer: WrappedDBAnswer[]) => void) => { +export const watchAllAnswers = (callback: (wrappedAnswer: IWrappedDBAnswer[]) => void) => { // Note that watchAnswerDocs returns unsubscribe method. return watchAnswerDocs((answers: firebase.firestore.DocumentData[]) => { - callback(answers.map(doc => firestoreDocToWrappedAnswer(doc))); + callback(answers.map(doc => docToWrappedAnswer(doc))); }); }; -export function createOrUpdateAnswer(answer: IExportableAnswerMetadata) { - if (!portalData) { - return; - } +function prepareAnswerForFireStore(answer: IExportableAnswerMetadata) { + if (!portalData) { throw("No portal Data"); } let answerDocData: LTIRuntimeAnswerMetadata | AnonymousRuntimeAnswerMetadata; @@ -254,6 +262,11 @@ export function createOrUpdateAnswer(answer: IExportableAnswerMetadata) { }; answerDocData = anonymousAnswer; } + return answerDocData; +} + +export function createOrUpdateAnswer(answer: IExportableAnswerMetadata) { + const answerDocData = prepareAnswerForFireStore(answer); // TODO: LARA stores a created field with the date the answer was created // I'm not sure how to do that easily in Firestore, we could at least add @@ -263,10 +276,19 @@ export function createOrUpdateAnswer(answer: IExportableAnswerMetadata) { .set(answerDocData as Partial