Asian Journal of Information Technology

Year: 2017
Volume: 16
Issue: 2
Page No. 218 - 226

Assessing the Impact of Class Attendance on Student’s Academic Performance using Data Mining

Authors : Olufunke Oladipupo, Olawande Daramola, Jelili Oyelade and Ibukun Afolabi

Abstract: Many institutions of learning encourage students to have good lecture attendance records. The belief is that an above average attendance rate will enhance student’s academic performance. However, very few studies have attempted to answer questions that relate to: the actual impact of good attendance record on student’s academic performance; the extent in quantitative terms of the effect of good attendance record on student’s academic performance. This study reports the findings from an experimental analysis of student’s attendance record and corresponding academic performance results using association rule mining. Based on the extracted patterns in rules from the five course assessed, it was discovered that the impact of class attendance on academic performance is very low. A student with >70 % attendance score can still fall into any grade between “A-F”. This indicates that class attendance is not the major factor that determines student academic performance but other key factors such as the student participation in the class, personal study and group study. The result of this case study and the recommendations is expected to provide useful information for the managements of higher institutions of learning on appropriate perspective to adopt on class attendance policies and good motivation for distance and online learning programmes.

How to cite this article:

Olufunke Oladipupo, Olawande Daramola, Jelili Oyelade and Ibukun Afolabi, 2017. Assessing the Impact of Class Attendance on Student’s Academic Performance using Data Mining. Asian Journal of Information Technology, 16: 218-226.

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