文章基本信息

标题：Data Mining Techniques in EDM for Predicting the Performance of Students
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作者：Ajay Kumar Pal ; Saurabh Pal
期刊名称：International Journal of Computer and Information Technology
印刷版ISSN：2279-0764
出版年度：2013
卷号：2
期号：6
页码：1110
出版社：International Journal of Computer and Information Technology
摘要：In recent, growth of higher education has increased rapidly. Many new institutions, colleges and universities are being established by both the private and government sectors for the growth of education and welfare of the students. Each institution aims at producing higher and exemplary education rates by employing various teaching and grooming methods. But still there are cases of unemployment that exists among the medium and low risk students. This paper describes the use of data mining techniques to improve the efficiency of academic performance in the educational institutions. Various data mining techniques such as decision tree, association rule, nearest neighbors, neural networks, genetic algorithms, exploratory factor analysis and stepwise regression can be applied to the higher education process, which in turn helps to improve student's performance. This type of approach gives high confidence to students in their studies. This method helps to identify the students who need special advising or counseling by the teacher which gives high quality of education.
关键词：component; Data Mining; KDD; EDM; Association ; Rule