Learning Analytics Through Serious Games: Data Mining Algorithms for Performance Measurement and Improvement Purposes ARTICLE
Abdelali Slimani, Fatiha Elouaai, Lotfi Elaachak, Othman Bakkali Yedri, Mohammed Bouhorma, Computer science, systems and telecommunication Laboratory (LIST), Faculty of sciences and technologies, University Abdelmalek Essaadi, Tangier, Morocco ; Mateu Sbert, Institut d\u2019Informtica i Aplicacions, Universitat de Girona, Spain School of Computer Science and Technology, Tianjin University
iJET Volume 13, Number 1, ISSN 1863-0383 Publisher: International Association of Online Engineering, Kassel, Germany
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 \u201cELISA\u201d 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.
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(1), 46-64. Kassel, Germany: International Association of Online Engineering. Retrieved February 21, 2018 from https://www.learntechlib.org/p/182231/.
© 2018 International Association of Online Engineering