Key takeaways
- Aina Daniel Ayodele, a postgraduate scholar in the Department of Computer Science at the College of Computing, recently defended his Master's thesis, entitled “Leveraging Machine Learning for Early Detection of At-Risk Students Using Psycho-social Data." His research addresses the significant issue of student dropout rates, a substantial concern in today's educational landscape.
- Ayodele's study emphasizes the necessity of focusing on more than just academic performance when identifying students at risk of dropping out.
- According to his research, conventional detection methods may overlook critical indicators, hence the need to consider psycho-social factors alongside academic records for a m...
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