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...

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Bibliographic Details
Main Authors: Wook, M., Yahaya, Y.H., Wahab, N., Isa, M.R.M., Awang, N.F., Hoo Yann Seong
Format: Conference Proceeding
Language:English
Subjects:
Application software
artificial neural network
Artificial neural networks
Classification tree analysis
clustering
Computer science
Computer science education
Data mining
decision tree
Decision trees
Educational technology
Instruction sets
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Summary: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).
DOI:10.1109/ICCEE.2009.168