Learning Analytics Through Serious Games: Data Mining Algorithms for Performance Measurement and Improvement Purposes

Authors

  • Abdelali Slimani Computer science, systems and telecommunication Laboratory (LIST), Faculty of sciences and technologies, University Abdelmalek Essaadi, Tangier, Morocco
  • Fatiha Elouaai Computer science, systems and telecommunication Laboratory (LIST), Faculty of sciences and technologies, University Abdelmalek Essaadi, Tangier, Morocco
  • Lotfi Elaachak Computer science, systems and telecommunication Laboratory (LIST), Faculty of sciences and technologies, University Abdelmalek Essaadi, Tangier, Morocco
  • Othman Bakkali Yedri Computer science, systems and telecommunication Laboratory (LIST), Faculty of sciences and technologies, University Abdelmalek Essaadi, Tangier, Morocco
  • Mohammed Bouhorma Computer science, systems and telecommunication Laboratory (LIST), Faculty of sciences and technologies, University Abdelmalek Essaadi, Tangier, Morocco
  • Mateu Sbert Institut d’Informàtica i Aplicacions, Universitat de Girona, Spain School of Computer Science and Technology, Tianjin University

DOI:

https://doi.org/10.3991/ijet.v13i01.7518

Keywords:

learning analytics, serious game, debriefing, teaching, immunological techniques

Abstract


learning analytics is an emerging discipline focused on the measurement, collection, analysis and reporting of learner interaction data through the E-learning contents. Serious game provides a potential source for relevant educational user data; it can propose an interactive environment for training and offer an effective learning process. This paper presents methods and approaches of educational data mining such as EM and K-Means to discuss the learning analytics through serious games, and then we provide an analysis of the player experience data collected from the educational game “ELISA” used to teach students of biology the immunological technique for determination of ANTI-HIV antibodies. Finally, we propose critically evaluation of our results including the limitations of our study and making suggestions for future research that links learning analytics and serious gaming.

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Published

2018-01-22

How to Cite

Slimani, A., Elouaai, F., Elaachak, L., Bakkali Yedri, O., Bouhorma, M., & Sbert, M. (2018). Learning Analytics Through Serious Games: Data Mining Algorithms for Performance Measurement and Improvement Purposes. International Journal of Emerging Technologies in Learning (iJET), 13(01), pp. 46–64. https://doi.org/10.3991/ijet.v13i01.7518

Issue

Vol. 13 No. 01 (2018)

Section

Papers

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