Predicting University Student Performance Using Machine Learning Techniques
Student: Ayodeji Anthony Alese (Project, 2025)
Department of Computer and Information Science
Bamidele Olumilua University of Edu. Science and Tech. Ikere Ekiti, Ekiti State
Abstract
This research looks forward to developing a model with the ability to make effective analysis and prediction on the performance of students in regard to their advanced knowledge, using modern machine learning techniques. Through modern machine learning algorithms-supervised and unsupervised-finding insight into students' academic and behavioral data, the paper tends to be helpful for educational institutions as regards early intervention with better time-saving support for at-risk students by optimizing learning outcomes.
Keywords
For the full publication, please contact the author directly at: sanchezalese@gmail.com
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Institutions
- Abdul-Gusau Polytechnic, Talata-Mafara, Zamfara State 3
- Abia State Polytechnic, Aba, Abia State 24
- Abia State University, Uturu, Abia State 71
- Abraham Adesanya Polytechnic, Ijebu-Igbo, Ogun State 3
- Abubakar Tafawa Balewa University, Bauchi, Bauchi State 15
- Abubakar Tatari Ali Polytechnic, Bauchi State. (affiliated To Atbu Bauchi) 1
- Achievers University, Owo, Ondo State 6
- Adamawa State University, Mubi, Adamawa State 8
- Adekunle Ajasin University, Akungba-Akoko, Ondo State 26
- Adeleke University, Ede, Osun State 1