A Robust Hybrid CNN–LSTM Model for Predicting Student Academic Performance

The rapid increase in educational data from diverse sources such as learning management systems and assessment records necessitates the application of advanced analytical techniques to identify at-risk students and address persistent issues like dropout rates and academic underperformance. However,...

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Bibliographic Details
Main Authors: Kuburat Oyeranti Adefemi, Murimo Bethel Mutanga
Format: Article
Language:English
Published: MDPI AG 2025-05-01
Series:Digital
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Online Access:https://www.mdpi.com/2673-6470/5/2/16
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