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Application of Deep Learning on Student Engagement in e-learning environments.
Prakhar Bhardwaj1, P K Gupta1, Harsh Panwar1
1Department of Computer Science and Engineering, Jaypee University of Information Technology, Waknaghat, Solan, HP, 173 234, India.
Computers & Electrical Engineering : an International Journal
|December 26, 2022
Summary
This study introduces deep learning algorithms to monitor student emotions and engagement in real-time during online classes. The Mean Engagement Score (MES) helps improve digital learning experiences for better educational outcomes.
Area of Science:
- Artificial Intelligence
- Educational Technology
- Computer Vision
Background:
- The COVID-19 pandemic accelerated the adoption of e-learning and remote digital education.
- Maintaining student engagement in online classes is crucial for effective learning.
- Traditional classroom engagement metrics are difficult to translate to digital environments.
Purpose of the Study:
- To develop novel deep learning algorithms for real-time monitoring of student emotions and engagement during online classes.
- To introduce a Mean Engagement Score (MES) for quantifying student participation.
- To provide educational institutions with tools for enhancing digital learning methods.
Main Methods:
- Real-time emotion recognition using facial landmark detection.
- Analysis of facial expressions to identify emotions like happiness, sadness, anger, fear, disgust, and surprise.
- Computation of the Mean Engagement Score (MES) integrating facial analysis and student survey data.
Main Results:
- The proposed algorithms can monitor a range of student emotions in real-time.
- The Mean Engagement Score (MES) provides a quantitative measure of student engagement.
- The system offers an automated approach to assess and potentially improve online learning interactions.
Conclusions:
- Deep learning-based emotion and engagement monitoring can significantly enhance online education.
- The MES offers a novel metric for evaluating the effectiveness of digital learning platforms.
- This technology can help educational institutions create more interactive and engaging remote learning experiences.
Keywords:
COVID-19Deep learningDigital learningEmotion recognitionEngage DetectionEngagement detectionMore Related Videos
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