Framework for Learner Assessment in Learning Games

Abstract : Learner assessment in learning games (LG) is an interesting research area for both academia and industry. The play traces resulting from the learner’s activity in LGs with large state spaces and a large amount of free interactions, are hard to analyze and to interpret by teachers. In this paper, we present a framework to assist the building of an expert’s solving process that is the base of the algorithm that analyzes player’s traces and generates pedagogical labels about the learner’s behavior.
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Communication dans un congrès
11th European Conference on Technology Enhanced Learning, Sep 2016, Lyon, France. Springer, Adaptive and Adaptable Learning, 9891, pp.622-626, Lecture Notes in Computer Science. 〈10.1007/978-3-319-45153-4_77〉
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https://hal.archives-ouvertes.fr/hal-01359636
Contributeur : Mathieu Muratet <>
Soumis le : vendredi 2 septembre 2016 - 18:18:50
Dernière modification le : vendredi 31 août 2018 - 09:25:56

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Mathieu Muratet, Amel Yessad, Thibault Carron. Framework for Learner Assessment in Learning Games. 11th European Conference on Technology Enhanced Learning, Sep 2016, Lyon, France. Springer, Adaptive and Adaptable Learning, 9891, pp.622-626, Lecture Notes in Computer Science. 〈10.1007/978-3-319-45153-4_77〉. 〈hal-01359636〉

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