Predicting Student Performance in Higher Education

Hana Bydzovská, L. Popelínský
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引用次数: 23

Abstract

In this work, we focus on predicting student performance using educational data. Students have to choose elective and voluntary courses for successful graduation. Searching for suitable and interesting courses is time-consuming and the main aim is to recommend students such courses. Two beneficial approaches are thoroughly discussed in this paper. The results were achieved by analysis of study-related data and structural attributes computed from the social network. To validate the proposed method based on data mining and social network analysis, we evaluate data extracted from the information system of Masaryk University. However, the method is quite general and can be used at other universities.
预测学生在高等教育中的表现
在这项工作中,我们专注于使用教育数据预测学生的表现。为了顺利毕业,学生必须选择选修课程和志愿课程。寻找合适的和有趣的课程是费时的,主要目的是为学生推荐这样的课程。本文对两种有益的方法进行了深入的讨论。该结果是通过分析研究相关数据和从社会网络中计算出的结构属性获得的。为了验证基于数据挖掘和社会网络分析的方法,我们对从马萨里克大学信息系统中提取的数据进行了评估。然而,这种方法是非常普遍的,可以在其他大学使用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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