文章基本信息

标题：Predicting Assignment Submissions in a Multiclass Classification Problem
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作者：Bogdan Drăgulescu ; Marian Bucos ; Radu Vasiu 等
期刊名称：TEM Journal
印刷版ISSN：2217-8309
电子版ISSN：2217-8333
出版年度：2015
卷号：4
期号：3
页码：244-254
语种：English
出版社：UIKTEN
摘要：Predicting student failure is an important task that can empower educators to counteract the factors that affect student performance. In this paper, a part of the bigger problem of predicting student failure is addressed:predicting the students that do not complete their assignment tasks. For solving this problem,real data collected by our university’s educational platform was used. Because the problem consisted of predicting one of three possible classes (multi-class classification),the appropriate algorithms and methods were selected. Several experiments were carried out to find the best approach for this prediction problem and the used data set. An approach of time segmentation is proposed in order to facilitate the prediction from early on. Methods that address the problems of high dimensionality and imbalanced data were also evaluated. The outcome of each approach is shown and compared in order to select the best performing classification algorithm for the problem at hand.
关键词：Multi-class classification;machine learning;e-learning;learning analytics;Moodle.