Identifying and Understanding Student Dropouts Using Metaheuristic Optimized Classifiers and Explainable Artificial Intelligence Techniques

This study addresses the pressing issue of student dropout in higher education institutions and explores the potential of artificial intelligence (AI) to mitigate this challenge. Student dropout is a complex phenomenon influenced by diverse factors, including internal and external, student character...

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Detaylı Bibliyografya
Asıl Yazarlar:	Radic Goran, Luka Jovanovic, Nebojsa Bacanin, Milos S. Stankovic, Vladimir Simic, Milos Antonijevic, Miodrag Zivkovic
Materyal Türü:	Artigo
Dil:	Inglês
Baskı/Yayın Bilgisi:	IEEE 2024-01-01
Seri Bilgileri:	IEEE Access
Konular:	Higher education dropout explainable artificial intelligence metaheuristics XGBoost AdaBoost optimization
Online Erişim:	https://ieeexplore.ieee.org/document/10640075/
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Identifying and Understanding Student Dropouts Using Metaheuristic Optimized Classifiers and Explainable Artificial Intelligence Techniques

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