{"id":186,"date":"2025-03-21T13:39:49","date_gmt":"2025-03-21T13:39:49","guid":{"rendered":"https:\/\/textbook.mediasmarts.ca\/navigating-teacher\/chapter\/optimizing-algorithms-2\/"},"modified":"2025-07-30T17:57:01","modified_gmt":"2025-07-30T17:57:01","slug":"optimizing-algorithms-2","status":"publish","type":"chapter","link":"https:\/\/textbook.mediasmarts.ca\/navigating-teacher\/chapter\/optimizing-algorithms-2\/","title":{"raw":"Optimizing Algorithms","rendered":"Optimizing Algorithms"},"content":{"raw":"Explain to students that algorithms are not <strong>programmed <\/strong>like regular computer programs. Instead, they are <strong>trained <\/strong>on data and then <strong>optimized <\/strong>for a particular goal. That means that they constantly test themselves to see how well they're doing at meeting that goal, and then make changes to do it better.\r\n\r\nFor instance, the Netflix algorithm is <strong>optimized <\/strong>to help you find something that you want to watch in less than 90 seconds. It does this sorting and choosing thumbnails, as the last activity showed.\r\n\r\nTell students to think of another app they are familiar with that uses algorithmic recommendations. (Examples: TikTok, Instagram, YouTube, Spotify.)\r\n\r\nHave them open the <a href=\"https:\/\/textbook.mediasmarts.ca\/navigatingstudent\/chapter\/optimizing-algorithms\/\">Optimizing Algorithms<\/a> student chapter and go through the different [pb_glossary id=\"281\"]optimization[\/pb_glossary] goals. (Point out that these are not the <strong>only<\/strong> possible goals, but they are common ones.)\r\n\r\nNext, have them rank the optimization goals according to which they feel are the most important to the app or website. (You can have them do this individually, in pairs, or in small groups.)\r\n<div class=\"textbox textbox--exercises\"><header class=\"textbox__header\">\r\n<p class=\"textbox__title\"><strong>If students have difficulty ranking the goals, tell them to think about what the algorithm rewards. For example:<\/strong><\/p>\r\n\r\n<\/header>\r\n<div class=\"textbox__content\">\r\n<ul>\r\n \t<li>If it shows you more long videos and fewer short videos, it\u2019s trying to boost <strong>watch time<\/strong>.<\/li>\r\n \t<li>If it shows you things that get you upset, it\u2019s trying to boost <strong>engagement<\/strong>.<\/li>\r\n \t<li>If you worry about missing things if you\u2019re away too long, it\u2019s trying to boost <strong>daily active use<\/strong>.<\/li>\r\n<\/ul>\r\n<\/div>\r\n<\/div>\r\nHave students share their ranking with the class:\r\n\r\n&nbsp;\r\n<ul>\r\n \t<li>How did they decide on their ranking?<\/li>\r\n \t<li>Did students (or groups) who evaluated the same app rank the goals similarly?<\/li>\r\n \t<li>If so, what makes it so clear what the app is optimized for?<\/li>\r\n \t<li>If not, why do they disagree?<\/li>\r\n<\/ul>\r\n&nbsp;","rendered":"<p>Explain to students that algorithms are not <strong>programmed <\/strong>like regular computer programs. Instead, they are <strong>trained <\/strong>on data and then <strong>optimized <\/strong>for a particular goal. That means that they constantly test themselves to see how well they&#8217;re doing at meeting that goal, and then make changes to do it better.<\/p>\n<p>For instance, the Netflix algorithm is <strong>optimized <\/strong>to help you find something that you want to watch in less than 90 seconds. It does this sorting and choosing thumbnails, as the last activity showed.<\/p>\n<p>Tell students to think of another app they are familiar with that uses algorithmic recommendations. (Examples: TikTok, Instagram, YouTube, Spotify.)<\/p>\n<p>Have them open the <a href=\"https:\/\/textbook.mediasmarts.ca\/navigatingstudent\/chapter\/optimizing-algorithms\/\">Optimizing Algorithms<\/a> student chapter and go through the different <a class=\"glossary-term\" aria-haspopup=\"dialog\" aria-describedby=\"definition\" href=\"#term_186_281\">optimization<\/a> goals. (Point out that these are not the <strong>only<\/strong> possible goals, but they are common ones.)<\/p>\n<p>Next, have them rank the optimization goals according to which they feel are the most important to the app or website. (You can have them do this individually, in pairs, or in small groups.)<\/p>\n<div class=\"textbox textbox--exercises\">\n<header class=\"textbox__header\">\n<p class=\"textbox__title\"><strong>If students have difficulty ranking the goals, tell them to think about what the algorithm rewards. For example:<\/strong><\/p>\n<\/header>\n<div class=\"textbox__content\">\n<ul>\n<li>If it shows you more long videos and fewer short videos, it\u2019s trying to boost <strong>watch time<\/strong>.<\/li>\n<li>If it shows you things that get you upset, it\u2019s trying to boost <strong>engagement<\/strong>.<\/li>\n<li>If you worry about missing things if you\u2019re away too long, it\u2019s trying to boost <strong>daily active use<\/strong>.<\/li>\n<\/ul>\n<\/div>\n<\/div>\n<p>Have students share their ranking with the class:<\/p>\n<p>&nbsp;<\/p>\n<ul>\n<li>How did they decide on their ranking?<\/li>\n<li>Did students (or groups) who evaluated the same app rank the goals similarly?<\/li>\n<li>If so, what makes it so clear what the app is optimized for?<\/li>\n<li>If not, why do they disagree?<\/li>\n<\/ul>\n<p>&nbsp;<\/p>\n<div class=\"glossary\"><span class=\"screen-reader-text\" id=\"definition\">definition<\/span><template id=\"term_186_281\"><div class=\"glossary__definition\" role=\"dialog\" data-id=\"term_186_281\"><div tabindex=\"-1\"><p>Training an algorithm to achieve a particular goal.<\/p>\n<\/div><button><span aria-hidden=\"true\">&times;<\/span><span class=\"screen-reader-text\">Close definition<\/span><\/button><\/div><\/template><\/div>","protected":false},"author":2,"menu_order":4,"template":"","meta":{"pb_show_title":"on","pb_short_title":"","pb_subtitle":"","pb_authors":[],"pb_section_license":""},"chapter-type":[],"contributor":[],"license":[],"class_list":["post-186","chapter","type-chapter","status-publish","hentry"],"part":181,"_links":{"self":[{"href":"https:\/\/textbook.mediasmarts.ca\/navigating-teacher\/wp-json\/pressbooks\/v2\/chapters\/186","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/textbook.mediasmarts.ca\/navigating-teacher\/wp-json\/pressbooks\/v2\/chapters"}],"about":[{"href":"https:\/\/textbook.mediasmarts.ca\/navigating-teacher\/wp-json\/wp\/v2\/types\/chapter"}],"author":[{"embeddable":true,"href":"https:\/\/textbook.mediasmarts.ca\/navigating-teacher\/wp-json\/wp\/v2\/users\/2"}],"version-history":[{"count":2,"href":"https:\/\/textbook.mediasmarts.ca\/navigating-teacher\/wp-json\/pressbooks\/v2\/chapters\/186\/revisions"}],"predecessor-version":[{"id":927,"href":"https:\/\/textbook.mediasmarts.ca\/navigating-teacher\/wp-json\/pressbooks\/v2\/chapters\/186\/revisions\/927"}],"part":[{"href":"https:\/\/textbook.mediasmarts.ca\/navigating-teacher\/wp-json\/pressbooks\/v2\/parts\/181"}],"metadata":[{"href":"https:\/\/textbook.mediasmarts.ca\/navigating-teacher\/wp-json\/pressbooks\/v2\/chapters\/186\/metadata\/"}],"wp:attachment":[{"href":"https:\/\/textbook.mediasmarts.ca\/navigating-teacher\/wp-json\/wp\/v2\/media?parent=186"}],"wp:term":[{"taxonomy":"chapter-type","embeddable":true,"href":"https:\/\/textbook.mediasmarts.ca\/navigating-teacher\/wp-json\/pressbooks\/v2\/chapter-type?post=186"},{"taxonomy":"contributor","embeddable":true,"href":"https:\/\/textbook.mediasmarts.ca\/navigating-teacher\/wp-json\/wp\/v2\/contributor?post=186"},{"taxonomy":"license","embeddable":true,"href":"https:\/\/textbook.mediasmarts.ca\/navigating-teacher\/wp-json\/wp\/v2\/license?post=186"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}