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Vers des intelligences artificielles pour l'enseignement de la démarche d'investigation

Abstract : Virtual learning environments have been used as a tool to teach science during almost three decades. The potentialities of artificial intelligence (AI) to teach science methodology, despite of the design of various intelligent tutoring systems in the field of science, remain largely unexplored. In this article, we propose a review of the literature to put into context the rise of these AIs among the main families of technologies that have been used to foster the acquisition of inquiry skills in STEM, from computer-assisted experimentation to scaffolding tools. Some of the AIs that have been developed aim at diagnosing automatically learners' mastery of the scientific approach, through the hypotheses they test, or the interpretations they make. The learning environment can incorporate a virtual world that allows the learner to control some variables and simulate some experiments based on the values of the variables they have set. Alternatively, the diagnosis of the learner's inquiry skills can be made by analyzing the requests he performs on a dataset.
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Contributor : Matthieu Cisel <>
Submitted on : Saturday, March 28, 2020 - 7:23:18 PM
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Matthieu Cisel, Georges-Louis Baron. Vers des intelligences artificielles pour l'enseignement de la démarche d'investigation. SIEST, Apr 2019, Patras, Grèce. ⟨10.26220/une.2990⟩. ⟨hal-02523391⟩



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