A Comprehensive Comparative Analysis of Deep Learning Models for Student Performance Prediction in Virtual Learning Environments: Leveraging the OULA Dataset and Advanced Resampling Techniques

A Comprehensive Comparative Analysis of Deep Learning Models for Student Performance Prediction in Virtual Learning Environments: Leveraging the OULA Dataset and Advanced Resampling Techniques

Predicting student performance in Virtual Learning Environments (VLEs) has become increasingly important with the growth of online education. Early identification of at-risk students allows timely interventions to improve academic outcomes. This study evaluates the performance of several Deep Learni...

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Bibliographic Details
Main Authors: Bayan A. Alnasyan, Mohammed Basheri, Madini O. Alassafi
Format: Article
Language:English
Published: IEEE 2025-01-01
Series:IEEE Access
Subjects:
Deep learning
student performance
prediction
resampling methods
Online Access:https://ieeexplore.ieee.org/document/10979810/
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