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Title

Predicting Students Performance Using Classification Techniques

Author

Ahmed Alsanad and Toqa Aiman Mukheimer

Citation

Vol. 22  No. 9  pp. 673-679

Abstract

This research paper aims to use data mining methodologies to predict student’s performance to figure out factors influenced students’ success to help the university to success more effectively in an efficient way. In this paper, we will go through the literature to review the most recent contributions to this topic. Then, we propose a model that focuses on predicting students’ performance using classification techniques by applying different algorithms and compare them to find which one is more suitable in our case. In the end, the reader becomes aware of the importance of studying students’ academic performance through understanding the previous studies that have helped educational institutions to improve and enhance their professionalism in education and increase their students’ performance success rate in an efficient way.

Keywords

Data Mining, Classification, Educational Mining, Student Academic Performance, Predictive Model, Descriptive Model.

URL

http://paper.ijcsns.org/07_book/202209/20220988.pdf