MAGAM: A Multi-Aspect Generic Adaptation Model for Learning Environments

Abstract : Adaptation in learning environments can be performed according to various aspects, such as didactics, pedagogy or game mechanics. While most current approaches propose to adapt according to a single aspect, this paper proposes a Multi-Aspect Generic Adaptation Model (MAGAM). Based on the Q-matrix, this model aims at taking into account heterogeneous data to select adapted activities. It has been implemented and used into an experiment which allowed the adaptation of learning activities for 97 students based on both knowl‐ edge and gaming profiles. This experiment has shown the usefulness of MAGAM to combine various aspects of adaptation in ecological conditions.
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Baptiste Monterrat, Amel Yessad, François Bouchet, Elise Lavoué, Vanda Luengo. MAGAM: A Multi-Aspect Generic Adaptation Model for Learning Environments. European Conference on Technology Enhanced Learning (EC-TEL 2017), Sep 2017, Tallinn, Estonia. pp.139-152, ⟨10.1007/978-3-319-66610-5_11⟩. ⟨hal-01578380⟩

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