Comparing two CbKST approaches for adapting learning paths in serious games

Abstract : Competence-based Knowledge Space Theory (CbKST) is considered a well-fitting basis for adapting Serious Games (SGs). CbKST relies on the domain model associated to a given SG to infer the so-called competence structure. However, building such a model can be time-consuming and a tough task for experts. We propose another approach to overcome this issue by considering the Q-Matrix that contains the mapping between the SG activities and the addressed competences. We compare the two approaches, one based on the domain model and the other on the Q-Matrix, in three SGs. We apply both approaches to two SGs, while in a third one, we apply only the Q-Matrix approach since no domain model is available. The main findings when comparing both approaches refer to the issues derived from the generated competence structures and the definition of competences at a suitable granularity level. This exploratory work can provide meaningful insights when applying CbKST for adapting SGs.
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Communication dans un congrès
EC-TEL 2015 - 10th European Conference on Technology Enhanced Learning, Sep 2015, Toledo, Spain. Springer, 9307, pp.211-224, Lecture Notes in Computer Science. 〈10.1007/978-3-319-24258-3_16〉
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https://hal-auf.archives-ouvertes.fr/hal-01329129
Contributeur : Jean-Marc Labat <>
Soumis le : mercredi 8 juin 2016 - 17:05:47
Dernière modification le : mercredi 21 mars 2018 - 18:58:10

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Javier Melero, Naima El Kechai, Jean-Marc Labat. Comparing two CbKST approaches for adapting learning paths in serious games. EC-TEL 2015 - 10th European Conference on Technology Enhanced Learning, Sep 2015, Toledo, Spain. Springer, 9307, pp.211-224, Lecture Notes in Computer Science. 〈10.1007/978-3-319-24258-3_16〉. 〈hal-01329129〉

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