Apprentissage expérientiel pour soutenir la littératie numérique et en intelligence artificielle en enseignement supérieur
DOI :
https://doi.org/10.21432/cjlt28998Mots-clés :
littératie en intelligence artificielle, éthique, théorie de l’apprentissage expérientiel, littératie numérique, intelligence artificielle générativeRésumé
Cette étude à méthodes mixtes a examiné la façon dont la théorie de l’apprentissage expérientiel (AE) peut soutenir le développement de la littératie numérique et la littératie en intelligence artificielle dans l’enseignement supérieur grâce à l’intégration d’outils d’intelligence artificielle générative (IAg). Guidée par le cycle en quatre étapes de l’AE, à savoir l’expérience concrète, l’observation réfléchie, la conceptualisation abstraite et l’expérimentation active, cette étude a exploré la manière dont les personnes étudiantes ont utilisé l’IAg pour améliorer leur apprentissage, leur esprit critique et leur conscience éthique. Les données ont été recueillies auprès de 17 personnes étudiantes et d’une personne enseignante à l’aide de sondages et d’entretiens semi-structurés. Des analyses descriptives et thématiques ont révélé que les personnes étudiantes initialement identifiées comme débutantes dans l’utilisation de l’IAg utilisaient principalement cette technologie pour des tâches fonctionnelles telles que l’organisation d’informations ou la réalisation de recherches superficielles. Grâce à une approche expérientielle et à une réflexion guidée, les personnes étudiantes ont démontré une amélioration de leur confiance, de leur compréhension éthique et de leur évaluation critique des résultats générés par l’IA. Les conclusions de la personne enseignante ont convergé avec les points de vue des personnes étudiantes, soulignant la valeur d’une approche étayée et réfléchie pour le développement des compétences. L’intégration des résultats quantitatifs et qualitatifs a mis en évidence l’efficacité de l’AE dans un cours conçu par l’IAg.
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© Nadia Delanoy 2025
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