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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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-05-01
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| Series: | Digital |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2673-6470/5/2/16 |
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