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Lorsque l'IA générative est apparue, le réflexe courant dans l'éducation a été de « simplement exiger des compétences cognitives plus élevées ». Si la machine peut résumer, nous demanderons aux étudiants d'évaluer. Si elle peut coder, nous demanderons une analyse critique. Mais augmenter simplement les exigences cognitives dans l'espoir de rendre une tâche résistante à l'IA est un piège dangereux. Premièrement, cela ne fonctionne pas.","Série de webinaires #2 – L'IA et la robustesse des tâches d'évaluation | Switch",[226,232],{"__typename":227,"_id":228,"paragraph_id":229,"title":230,"text":231},"TextItem","b7b1c7a8-5b69-430c-a50e-000a94a85e73",3573,"Thème du webinar","\u003Cdiv>\u003Cdiv data-test-render-count=\"1\">\u003Cdiv class=\"group\" style=\"height:auto;opacity:1;transform:none;\">\u003Cdiv class=\"contents\">\u003Cdiv class=\"group relative pb-3\" style=\"opacity:1;transform:none;\" data-is-streaming=\"false\">\u003Cdiv class=\"font-claude-response relative leading-[1.65rem] [&_pre>div]:bg-bg-000/50 [&_pre>div]:border-0.5 [&_pre>div]:border-border-400 [&_.ignore-pre-bg>div]:bg-transparent [&_.standard-markdown_:is(p,blockquote,h1,h2,h3,h4,h5,h6)]:pl-2 [&_.standard-markdown_:is(p,blockquote,ul,ol,h1,h2,h3,h4,h5,h6)]:pr-8 [&_.progressive-markdown_:is(p,blockquote,h1,h2,h3,h4,h5,h6)]:pl-2 [&_.progressive-markdown_:is(p,blockquote,ul,ol,h1,h2,h3,h4,h5,h6)]:pr-8\">\u003Cdiv>\u003Cdiv class=\"standard-markdown grid-cols-1 grid [&_>_*]:min-w-0 gap-3\">\u003Cp class=\"font-claude-response-body break-words whitespace-normal leading-[1.7]\">\u003Cstrong>L'IA générative « lisse » les textes avec une telle fluidité qu'elle peut imiter de manière transparente une évaluation ou une synthèse de haut niveau, créant un fossé silencieux entre ce qui est pratiqué et ce qui est réellement compris.\u003C/strong> Deuxièmement, si nous changeons la façon dont nous évaluons, nous devrons peut-être aussi changer la façon dont nous enseignons. Dans notre prochain webinaire, nous présentons une alternative : une grille de coordonnées pragmatique 6×4 croisant les six niveaux de la taxonomie de Bloom avec quatre colonnes clairement définies de répartition du travail entre l'humain et l'IA – de la performance entièrement humaine, à l'humain qui guide l'IA, l'humain qui opère l'IA, jusqu'à la délégation totale. \u003Cstrong>La robustesse ne signifie pas interdire la technologie ou augmenter artificiellement la difficulté des tâches. Elle signifie définir clairement qui fait quoi, quelle réflexion est requise à quel moment, et ce qui constitue une preuve solide de compétence.\u003C/strong> Dans le webinaire, nous analyserons cette matrice et examinerons des stratégies de transition concrètes et pratiques. \u003Cstrong>Nous dévoilerons une première version d'un assistant IA portable conçu pour aider les enseignants à formuler des instructions IA sur mesure et des modèles de déclaration pour les étudiants, en complément des tâches d'évaluation existantes.\u003C/strong>\u003C/p>\u003Cp class=\"font-claude-response-body break-words whitespace-normal leading-[1.7]\"> \u003C/p>\u003Cp class=\"font-claude-response-body break-words whitespace-normal leading-[1.7]\">Ce webinaire sera animé par \u003Cstrong>Thomas Steiner\u003C/strong>, professeur ordinaire à la Haute École de Gestion du Canton du Valais (HES-SO Valais-Wallis), responsable stratégique de Cyberlearn (le centre d'e-learning de la HES-SO) et membre du Comité de pilotage IA pour l'éducation. 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