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Comparing Two CbKST Approaches for Adapting Learning Paths in Serious Games

  • Javier MeleroEmail author
  • Naïma El-Kechaï
  • Jean-Marc Labat
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9307)

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.

Keywords

Serious games Competence-based Knowledge Space Theory Domain model Adaptation 

Notes

Acknowledgements

This work was supported in part by the Region Ile de France and by the French Ministry for the Economy, Industry and Employment (FUI). We would like to thank them for their support in the “PlaySerious” project. The authors would like to thank John Wisdom and Bertrand Marne for their very helpful support.

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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Javier Melero
    • 1
    Email author
  • Naïma El-Kechaï
    • 1
  • Jean-Marc Labat
    • 1
  1. 1.LIP6, Université Pierre et Marie CurieParisFrance

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