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
Published in2009 Second International Conference on Computer and Electrical Engineering Vol. 2; pp. 357 - 361
Main Authors Wook, M., Yahaya, Y.H., Wahab, N., Isa, M.R.M., Awang, N.F., Hoo Yann Seong
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.12.2009
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).
ISBN:9781424453658
1424453658
DOI:10.1109/ICCEE.2009.168