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
- HASSAN USMAN KATSINA POLYTECHNIC (NCE), KATSINA, KATSINA STATE 4
- Hassan Usman Katsina Polytechnic, Katsina, Katsina State 5
- Heritage Polytechnic, Ikot Udota, Akwa Ibom State 46
- Hussaini Adamu Federal Polytechnic, Kazaure, Jigawa State 8
- Ibrahim Badamasi Babangida University, Lapai, Niger State 24
- Igbinedion University, Okada, Benin City, Edo State 2
- Ignatius Ajuru University of Education, Port Harcourt, Rivers State 8
- Imo State Polytechnic, Umuagwo, Owerri, Imo State 3
- Imo State University, Owerri, Imo State 45
- Institute of Management and Technology, Enugu, Enugu State 11