利用数据挖掘技术预测新大学生的学习成绩

Muslihah Wook, Y. H. Yahaya, Norshahriah Wahab, M. Isa, N. Awang, Hoo Yann Seong
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引用次数: 72

摘要

对学生学习成绩的预测能力在高校教育体系中是非常重要的。近年来,一些研究人员提出了高等教育数据挖掘技术。在本文中,我们比较了两种数据挖掘技术:人工神经网络(ANN)和聚类与决策树相结合的分类技术,用于预测和分类学生的学习成绩。本研究使用的数据集为马来西亚国防大学(NDUM)科学与国防技术学院计算机科学系学生数据。
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Predicting NDUM Student's Academic Performance Using Data Mining Techniques
The ability to predict the students’ academic performance is very important in institution educational system. Recently some researchers have been proposed data mining techniques for higher education. In this paper, we compare two data mining techniques which are: Artificial Neural Network (ANN) and the combination of clustering and decision tree classification techniques for predicting and classifying students’ academic performance. The data set used in this research is the student data of Computer Science Department, Faculty of Science and Defence Technology, National Defence University of Malaysia (NDUM).
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