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Learning Analytics for a Puzzle Game to Discover the Puzzle-Solving Tactics of Players

  • Mehrnoosh Vahdat
  • Maira B. Carvalho
  • Mathias Funk
  • Matthias Rauterberg
  • Jun Hu
  • Davide Anguita
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9891)

Abstract

Games can be used as effective learning tools, proved to enhance players’ performance in a wide variety of cognitive tasks. In this context, Learning Analytics (LA) can be used to improve game quality and to support the achievement of learning goals. In this paper, we investigate the use of LA in digital puzzle games, which are commonly used for educational purposes. We describe our approach to explore the way players learn game skills and solve problems in an open-source puzzle game called Lix. We performed an initial study with 15 participants, in which we applied Process Mining and cluster analysis in a three-step analysis approach. This approach can be used as a basis for recommending interventions so as to facilitate the puzzle-solving process of players.

Keywords

Learning Analytics Educational Data Mining Serious games Puzzle games Technology enhanced learning Cluster analysis Process mining 

Notes

Acknowledgments

This work was supported in part by the Erasmus Mundus Joint Doctorate in Interactive and Cognitive Environments, funded by the EACEA Agency of the European Commission under EMJD ICE FPA n 2010-0012.

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Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  • Mehrnoosh Vahdat
    • 1
    • 3
  • Maira B. Carvalho
    • 1
    • 3
  • Mathias Funk
    • 1
  • Matthias Rauterberg
    • 1
  • Jun Hu
    • 1
  • Davide Anguita
    • 2
  1. 1.Department of Industrial DesignEindhoven University of TechnologyEindhovenThe Netherlands
  2. 2.DIBRIS - Università degli Studi di GenovaGenoaItaly
  3. 3.DITEN - Università degli Studi di GenovaGenoaItaly

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