文章基本信息

标题：Learning Analytics Through Serious Games: Data Mining Algorithms for Performance Measurement and Improvement Purposes
其他标题：Learning Analytics Through Serious Games: Data Mining Algorithms for Performance Measurement and Improvement Purposes
本地全文：下载
作者：Abdelali Slimani ; Fatiha Elouaai ; Lotfi Elaachak 等
期刊名称：International Journal of Emerging Technologies in Learning (iJET)
印刷版ISSN：1863-0383
出版年度：2018
卷号：13
期号：1
页码：46-64
语种：English
出版社：Kassel University Press
摘要：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.
关键词：learning analytics;serious game; debriefing; teaching; immunological techniques