💻 computer science
A Multimodal Fusion Framework for Student Engagement Detection Using Facial, Behavioral, and Textual Features
This study proposes a multimodal fusion framework that integrates facial, behavioral, and textual features to detect student engagement, demonstrating that a late fusion strategy achieves high accuracy (0.864) and outperforms single-modality models in classifying engagement levels.
Original paper licensed under CC BY 4.0 (https://creativecommons.org/licenses/by/4.0/). This is an AI-generated explanation of the paper below. It is not written or endorsed by the authors. For technical accuracy, refer to the original paper. Read full disclaimer
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