ArticleScientific data2025
A Video Dataset for Classroom Group Engagement Recognition.
Article in Scientific data, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
2 citing papers in PubMed.
- Assessing multidimensional student engagement in studio-based design learning: a traceable multimodal framework for teacher-led inquiry.Frontiers in psychology · 2026Article
- Rehearsal-Free Continual Learning for Emerging Unsafe Behavior Recognition in Construction Industry.Sensors (Basel, Switzerland) · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
Abstract
Student group engagement helps share knowledge and build a more complete understanding. Recognition of group engagement in the classroom helps us understand students' learning state and optimize teaching and study processes. While existing research predominantly focuses on individual engagement recognition through controlled lab-based computer interactions, this paradigm was fundamentally misaligned with authentic classroom dynamics. To address this issue, this research focuses on student group engagement recognition in classroom environments using visual cues. We propose OUC Classroom Group Engagement Dataset (OUC-CGE), the first benchmark dedicated to group engagement analysis in authentic classroom settings using pure visual signals. Several classical models are tested on OUC-CGE, and through technical-pedagogical dual validation strategy, OUC-CGE exhibits good consistency and discriminability with existing datasets. By transcending the individualistic paradigm, this work establishes group engagement as a computable pedagogical construct, offering teachers diagnostic insights into group engagement trajectories while preserving the ecological complexity of authentic classrooms. The OUC-CGE dataset and models are publicly released to catalyze research in socially-embedded educational artificial intelligence.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.