An Analysis on Student Academic Performance by Using Decision Tree Models

Jastini Mohd. Jamil*, Nurul Farahin Mohd Pauzi and Izwan Nizal Mohd. Shahara Nee
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Jastini Mohd. Jamil*: School of Quantitative Sciences, College of Arts and Sciences, Universiti Utara Malaysia, 06010 UUM Sintok, Kedah, Malaysia
Nurul Farahin Mohd Pauzi: School of Quantitative Sciences, College of Arts and Sciences, Universiti Utara Malaysia, 06010 UUM Sintok, Kedah, Malaysia
Izwan Nizal Mohd. Shahara Nee: School of Quantitative Sciences, College of Arts and Sciences, Universiti Utara Malaysia, 06010 UUM Sintok, Kedah, Malaysia

The Journal of Social Sciences Research, 2018, 615-620 Special Issue: 6

Abstract: Large volume of educational data has led to more challenging in predicting student’s performance. In Malaysia currently, study about the performance of students in Malaysia institutions is very little being addressed. The previous studies are still insufficient to identify what factors contribute to student’s achievements and lack of investigations on exploring pattern of student’s behaviour that affecting their academic performance within Malaysia context. Therefore, predicting student’s academic performance by using decision trees is proposed to improve student’s achievements more effectively. The main objective of this paper is to provide an overview on predicting student’s academic performance using by using data mining techniques. This paper also focuses on identifying the pattern of student’s behaviour and the most important attributes that impact to the student’s achievement. By using educational data mining techniques, the students, lecturers and academic institution are able to have a better understanding on the student’s achievement.

Keywords: Academic performance; Data mining; Decision tree. (search for similar items in EconPapers)
Date: 2018
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