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2015 | OriginalPaper | Chapter

Comparing Two CbKST Approaches for Adapting Learning Paths in Serious Games

Authors : Javier Melero, Naïma El-Kechaï, Jean-Marc Labat

Published in: Design for Teaching and Learning in a Networked World

Publisher: Springer International Publishing

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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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Metadata
Title
Comparing Two CbKST Approaches for Adapting Learning Paths in Serious Games
Authors
Javier Melero
Naïma El-Kechaï
Jean-Marc Labat
Copyright Year
2015
Book
Design for Teaching and Learning in a Networked World

Print ISBN: 978-3-319-24257-6

Electronic ISBN: 978-3-319-24258-3

Copyright Year: 2015

DOI
https://doi.org/10.1007/978-3-319-24258-3_16

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