Résumés
Résumé
L’intelligence artificielle générative (IAg) connaît actuellement un essor sans précédent en éducation. Parmi les potentialités de l’IAg pour favoriser l’apprentissage étudiant en enseignement supérieur, on retrouve sa capacité à fournir une rétroaction personnalisée. Pour comprendre l’état de la recherche actuelle, cet examen de la portée synthétise les recherches traitant de l’usage d’IAg pour fournir de la rétroaction sur une production étudiante. Les résultats montrent une variété d’IAg utilisées et les caractéristiques des rétroactions. La discussion souligne le besoin de mieux documenter les approches conceptuelles mobilisées pour concevoir les IAg afin de favoriser la compréhension des études et le transfert des connaissances.
Mots-clés :
- Intelligence artificielle générative,
- rétroaction,
- étayage,
- évaluation des apprentissages,
- enseignement supérieur,
- enseignement postsecondaire,
- enseignement universitaire
Abstract
Generative artificial intelligence (GenAI) is currently undergoing unprecedented growth in education. Among the ways that GenAI could potentially enhance learning in higher education is its ability to provide personalized feedback. To understand the current state of research, this scoping review synthesizes studies focusing on the use of GenAI to provide feedback on student work. The results reveal a variety of GenAI tools used and the characteristics of the feedback provided. The discussion emphasizes the need for better documentation of the methodological design processes used for GenAI, in order to promote understanding of the studies and the transfer of knowledge.
Keywords:
- Generative artificial intelligence,
- feedback,
- scaffolding,
- learning assessment,
- higher education,
- postsecondary education,
- university students
Parties annexes
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Note. Les astérisques devant les notices désignent les douze articles de la recension.