A Multi-Faceted Deep Learning Approach for Student Engagement Insights and Adaptive Content Recommendations

A Multi-Faceted Deep Learning Approach for Student Engagement Insights and Adaptive Content Recommendations

In an era where technology shapes education, effectively engaging students remains a cri- tical challenge. Student engagement significantly impacts academic performance, yet traditional assessment methods fail to capture its multidimensional nature. This study proposes a novel Engagement Level Class...

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Bibliographic Details
Main Authors: Rabeeya Saleem, Muhammad Aslam
Format: Article
Language:English
Published: IEEE 2025-01-01
Series:IEEE Access
Subjects:
Engagement level classification framework (ELCF)
personalized content recommendation
deep learning models
real-time behavioral analysis
educational technology
Online Access:https://ieeexplore.ieee.org/document/10966906/
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https://ieeexplore.ieee.org/document/10966906/

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