Proposition d’un guide pour un usage responsable de l’IAG dans les rendus académiques des étudiants

Mickaël David (), Fabienne Garcia () and Laurent Chevalier ()
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Mickaël David: VALLOREM - Val de Loire Recherche en Management - UO - Université d'Orléans - UT - Université de Tours
Fabienne Garcia: VALLOREM - Val de Loire Recherche en Management - UO - Université d'Orléans - UT - Université de Tours
Laurent Chevalier: VALLOREM - Val de Loire Recherche en Management - UO - Université d'Orléans - UT - Université de Tours, IAE Tours Val de Loire - Institut d'Administration des Entreprises (IAE) - Tours Val de Loire

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Abstract: The massive use of Generative Artificial Intelligence (GenAI) by students raises questions for teachers about the teaching content, the required outputs, and the evaluation and criteria for assessment. This paper presents a best practice guide delivered to students of an IAE this year to support them in their GenAI use, particularly for writing their dissertation. The guide sets out the expectations for academic work, explains how GenAI can be used in a dissertation and the issues that require attention. It also defines rules of transparency to ensure that student use is in line with teachers' expectations. The primary goal of this guide is not to restrain GenAI use, but to explain their use as part of a pedagogical approach and to restore trust between student and teacher in the assessment of academic work. This proposal is intended to support the sharing of best practices and debate within the Pedagogy and Mediation track of the conference.

Keywords: Intelligence artificielle générative; mémoire; usage des TI; étudiants; pédagogie (search for similar items in EconPapers)
Date: 2025-05-21
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Published in 30e Conférence de l’Association Information et Management, AIM, May 2025, Lyon, France

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Persistent link: https://EconPapers.repec.org/RePEc:hal:journl:hal-05312234

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