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
- University of Port Harcourt Teaching Hospital, Port Harcourt , River State 6
- University of Port-Harcourt, Rivers State 220
- University of Uyo, Akwa Ibom State 214
- Usmanu Danfodio University, Sokoto, Sokoto State 248
- Veritas University, Bwari, FCT, Abuja 2
- Waziri Umaru Federal Polytechnic, Birnin Kebbi, Kebbi State 4
- Western Delta University, Oghara, Delta State 5
- Yaba College of Technology, Yaba, Lagos State 16
- Yobe State University, Damaturu, Yobe State 3
- Yusuf Maitama Sule University, Kano, Kano State 3