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Ranking of influencing factors in predicting students' academic performance.


Citation

Affendey, Lilly Suriani and Mohd Paris, Ikmal Hisyam and Mustapha, Norwati and Sulaiman, Md. Nasir and Muda, Zaiton (2010) Ranking of influencing factors in predicting students' academic performance. Information Technology Journal, 9 (4). pp. 832-837. ISSN 1812-5638

Abstract

The aim of this study was to rank influencing factors that contribute to the prediction of students’ academic performance. It is useful in identifying weak students who are likely to perform poorly in their studies. In this study, we used WEKA open source data mining tool to analyze attributes for predicting a higher learning institution’s bachelor of computer science students’ academic performance. The data set comprised of 2427 number of student records and 396 attributes of students registered between year 2000 and 2006. Preprocessing includes attribute importance analysis. We applied the data set to different classifiers (Bayes, trees or function) and obtained the accuracy of predicting the students’ performance into either first-second-upper class or second-lower-third class. A cross-validation with 10 folds was used to evaluate the prediction accuracy. Our results showed the ranking of courses that has significant impact on predicting the students’ overall academic results. In addition, we perform experiments comparing the performance of different classifiers and the result showed that Naïve Bayes, AODE and RBFNetwork classifiers scored the highest percentage of prediction accuracy of 95.29%.


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Additional Metadata

Item Type: Article
Subject: Educational tests and measurement.
Subject: College students - Rating of.
Subject: Competency based educational tests.
Divisions: Faculty of Computer Science and Information Technology
Publisher: Asian Network for Scientific Information (ANSINET)
Keywords: Predicting academic performance; Academic performance; Data mining; Attributes ranking.
Depositing User: Nida Hidayati Ghazali
Date Deposited: 25 Jun 2013 03:51
Last Modified: 03 Nov 2015 06:45
URI: http://psasir.upm.edu.my/id/eprint/16423
Statistic Details: View Download Statistic

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