What type of study is this?

September 10, 2025ComputersOpen Access

Multimodal Detection of Emotional and Cognitive States in E-Learning Through Deep Fusion of Visual and Textual Data with NLP

View Full Paper

Ask AI

Bookmark

Authors

This system integrates visual and textual data for detecting cognitive and emotional states, suggesting new interventions.

Results show a precision of 88.5% for fatigue detection and 91.5% for sentiment analysis, indicating strong performance.
Using CNN-LSTM and LSTM models, alongside sentiment analysis, enhances the ability to identify learner disengagement.
The system aggregates cues from facial emotions, fatigue signs, and sentiment, facilitating individualized interventions.
Findings highlight the feasibility of integrated approaches for emotionally intelligent learning systems in real-time.

maazouzi et al. (2025) studied this question.

View Full Paper

Ask AI

Bookmark