Abstract—There are several statistical tools being used for information extraction and knowledge discovery from the students’ performance analysis. This paper presents data mining approach applied to discover students’ performance patterns in mathematics, English, and programming courses taught in an undergraduate engineering degree program. The interesting patterns emerging from this analysis promise to offer some helpful and constructive guidance to educational administrators and decision makers in higher education sector for the improvement and revision of teaching methodology, restructuring of curriculum, and modifying the prerequisites requirements of various courses.
Index Terms—Association rules, KDD, educational data mining, mathematics and programming
The authors are with the Al Ghurair University, Dubai, UAE (Tel.: +971 (4) 420 0223; fax: +971 (4) 420 0226 (e-mail: anwar@agu.ac.ae).
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Cite: M. A. Anwar, Naseer Ahmed, and Wajahatullah Khan, "Analysis of Students’ Grades in Mathematics, English, and Programming Courses: A KDD Approach,"
International Journal of Future Computer and Communication vol. 1, no. 2, pp. 111-115, 2012.
