Un rapport de l\u2019institut de recherche am\u00e9ricain RAND analyse le co\u00fbt de mise en \u0153uvre du programme num\u00e9rique Zearn Math dans un grand district scolaire du Texas, aux \u00c9tats-Unis. Ce travail s\u2019inscrit dans un contexte de baisse r\u00e9cente des performances en math\u00e9matiques des \u00e9l\u00e8ves am\u00e9ricains, aggrav\u00e9e par les pertes d\u2019apprentissage li\u00e9es \u00e0 la pand\u00e9mie, en particulier \u00e0 la fin de l\u2019\u00e9cole \u00e9l\u00e9mentaire, phase jug\u00e9e d\u00e9terminante pour la r\u00e9ussite ult\u00e9rieure en alg\u00e8bre et en sciences, technologies, ing\u00e9nierie et math\u00e9matiques (STEM).<\/p>\n
Zearn Math est une technologie \u00e9ducative de math\u00e9matiques visant \u00e0 renforcer l\u2019apprentissage au niveau de la classe tout en comblant les lacunes de comp\u00e9tences, selon une logique d\u2019\u201cacc\u00e9l\u00e9ration\u201d plut\u00f4t que de rem\u00e9diation pr\u00e9alable des seuls fondamentaux. Le rapport pr\u00e9sente une \u00e9tude de co\u00fbts qui vient compl\u00e9ter une \u00e9tude d\u2019impact men\u00e9e parall\u00e8lement dans le m\u00eame district texan, portant sur les effets de Zearn Math en classes de 3e \u00e0 5e ann\u00e9e (\u00e9quivalent de la fin de l\u2019\u00e9cole primaire) sur deux ans, selon un protocole d\u2019essai randomis\u00e9 contr\u00f4l\u00e9.<\/p>\n
Les auteurs concluent que, combin\u00e9s, les r\u00e9sultats de l\u2019\u00e9tude de co\u00fbts et de l\u2019essai randomis\u00e9 indiquent que Zearn Math constitue une option prometteuse pour am\u00e9liorer les r\u00e9sultats en math\u00e9matiques, tout en \u00e9tant moins co\u00fbteuse que des produits concurrents de math\u00e9matiques. Le rapport ne fournit pas de d\u00e9tails chiffr\u00e9s pr\u00e9cis dans l\u2019extrait disponible, mais met en avant la dimension comparative des co\u00fbts par rapport \u00e0 d\u2019autres solutions num\u00e9riques.<\/p>\n
L\u2019\u00e9tude est publi\u00e9e dans la s\u00e9rie des rapports de recherche de RAND Education, Employment, and Infrastructure. Les rapports RAND font l\u2019objet d\u2019une \u00e9valuation par les pairs et ont pour objectif d\u2019\u00e9clairer les d\u00e9cideurs publics et priv\u00e9s. RAND rappelle que ses publications ne refl\u00e8tent pas n\u00e9cessairement les positions de ses clients ou financeurs, et que leurs contenus sont prot\u00e9g\u00e9s par le droit de la propri\u00e9t\u00e9 intellectuelle, avec des conditions sp\u00e9cifiques de r\u00e9utilisation, en particulier \u00e0 des fins commerciales.<\/p>\n
Pour le suivi des politiques publiques, ce document illustre l\u2019usage d\u2019essais randomis\u00e9s contr\u00f4l\u00e9s et d\u2019analyses de co\u00fbts pour \u00e9valuer des solutions d\u2019enseignement assist\u00e9 par technologie num\u00e9rique, dans un contexte de rattrapage des pertes d\u2019apprentissage post-pand\u00e9mie et de recherche de dispositifs d\u2019instruction diff\u00e9renci\u00e9e en math\u00e9matiques \u00e0 l\u2019\u00e9cole \u00e9l\u00e9mentaire. Il fournit un exemple international de comparaison co\u00fbt\u2011efficacit\u00e9 entre outils num\u00e9riques de soutien aux apprentissages.(contenu r\u00e9sum\u00e9 en fran\u00e7ais par l’IA)\u00a0Lire la Suite<\/a><\/p>","protected":false},"excerpt":{"rendered":" Un rapport de l\u2019institut de recherche am\u00e9ricain RAND analyse le co\u00fbt de mise en \u0153uvre du programme num\u00e9rique Zearn Math dans un grand district scolaire du Texas, aux \u00c9tats-Unis. Ce […]<\/p>\n","protected":false},"author":1,"featured_media":10675,"comment_status":"","ping_status":"","sticky":false,"template":"","format":"standard","meta":{"site-sidebar-layout":"default","site-content-layout":"","ast-site-content-layout":"default","site-content-style":"default","site-sidebar-style":"default","ast-global-header-display":"","ast-banner-title-visibility":"","ast-main-header-display":"","ast-hfb-above-header-display":"","ast-hfb-below-header-display":"","ast-hfb-mobile-header-display":"","site-post-title":"","ast-breadcrumbs-content":"","ast-featured-img":"","footer-sml-layout":"","ast-disable-related-posts":"","theme-transparent-header-meta":"","adv-header-id-meta":"","stick-header-meta":"","header-above-stick-meta":"","header-main-stick-meta":"","header-below-stick-meta":"","astra-migrate-meta-layouts":"default","ast-page-background-enabled":"default","ast-page-background-meta":{"desktop":{"background-color":"var(--ast-global-color-5)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"tablet":{"background-color":"","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"mobile":{"background-color":"","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""}},"ast-content-background-meta":{"desktop":{"background-color":"var(--ast-global-color-4)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"tablet":{"background-color":"var(--ast-global-color-4)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"mobile":{"background-color":"var(--ast-global-color-4)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""}},"footnotes":""},"categories":[26],"tags":[234,227,226],"class_list":["post-17348","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-donnees-etudes-evaluation-et-prospective","tag-rand","tag-ia","tag-sources-etrangeres"],"_links":{"self":[{"href":"https:\/\/veilles-affaires-sociales.fr\/index.php?rest_route=\/wp\/v2\/posts\/17348","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/veilles-affaires-sociales.fr\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/veilles-affaires-sociales.fr\/index.php?rest_route=\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/veilles-affaires-sociales.fr\/index.php?rest_route=\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/veilles-affaires-sociales.fr\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=17348"}],"version-history":[{"count":0,"href":"https:\/\/veilles-affaires-sociales.fr\/index.php?rest_route=\/wp\/v2\/posts\/17348\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/veilles-affaires-sociales.fr\/index.php?rest_route=\/wp\/v2\/media\/10675"}],"wp:attachment":[{"href":"https:\/\/veilles-affaires-sociales.fr\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=17348"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/veilles-affaires-sociales.fr\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=17348"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/veilles-affaires-sociales.fr\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=17348"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}