A three-stage pipeline uses few-shot VLM action parsing, sliding-window segmentation, and LLM sequence classification with peer context to measure student engagement from classroom videos.
Skeleton-based action segmentation with multi-stage spatial- temporal graph convolutional neural networks.IEEE Trans- actions on Emerging Topics in Computing, 12:202–212, 1
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Context Matters: Peer-Aware Student Behavioral Engagement Measurement via VLM Action Parsing and LLM Sequence Classification
A three-stage pipeline uses few-shot VLM action parsing, sliding-window segmentation, and LLM sequence classification with peer context to measure student engagement from classroom videos.