Papers › Students Engagement Level Detection in Online e-Learning Using Hybrid EfficientNetB7...
Students Engagement Level Detection in Online e-Learning Using Hybrid EfficientNetB7 Together With TCN, LSTM, and Bi-LSTM
Tasneem Selim, Islam Elkabani, Mohamed A. Abdou
Students engagement level detection in online e-learning has become a crucial problem due to the rapid advance of digitalization in education. In this paper, a novel Videos Recorded for Egyptian Students Engagement in E-learning (VRESEE) dataset is introduced for students engagement level detection in online e-learning. This dataset is based on an experiment conducted on a group of Egyptian college students by video recording them during online e-learning sessions. Each recorded video is labeled with a value from 0 to 3 representing the level of engagement of each student during the online session. Moreover, three new hybrid end-to-end deep learning models have been proposed for detecting student’s engagement level in an online e-learning video. These models are evaluated using the VRESEE dataset and also using a public Dataset for the Affective States in E-Environment (DAiSEE). The first proposed hybrid model uses EfficientNet B7 together with Temporal Convolution Network (TCN) and achieved an accuracy of 64.67% on DAiSEE and 81.14% on VRESEE. The second model uses a hybrid EfficientNet B7 along with Long Short Term Memory (LSTM) and reached an accuracy of 67.48% on DAiSEE and 93.99% on VRESEE. Finally, the third hybrid model uses EfficientNet B7 along with a Bidirectional LSTM and achieved an accuracy of 66.39% on DAiSEE and 94.47% on VRESEE. The results of the first, second and third proposed models outperform the results of currently existing models by 1.08%, 3.89%, and 2.8% respectively in students engagement level detection.
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Tasks
Results from the paper archive 2025-07-28
| Task | Dataset | Model | Metric | Value | Rank at snapshot | Leaderboard | Report |
|---|---|---|---|---|---|---|---|
| Student Engagement Level Detection (Four Class Video Classification) | DAiSEE | Hybrid EfficientNet B7 + Bi-LSTM | 4-class test accuracy | 67.48% | #1 of 3 | Archive leaderboard | report |
| Student Engagement Level Detection (Four Class Video Classification) | DAiSEE | Hybrid EfficientNet B7 + LSTM | 4-class test accuracy | 66.39% | #2 of 3 | Archive leaderboard | report |
| Student Engagement Level Detection (Four Class Video Classification) | DAiSEE | Hybrid EfficientNet B7 + TCN | 4-class test accuracy | 64.67% | #3 of 3 | Archive leaderboard | report |
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