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To investigate the detection of students' behavioral engagement (On-Task vs.Off-Task), we propose a two-phase approach in this study. In Phase 1,contextual logs (URLs) are utilized to assess active usage of the contentplatform. If there is active use, the appearance information is utilized inPhase 2 to infer behavioral engagement. Incorporating the contextualinformation improved the overall F1-scores from 0.77 to 0.82. Ourcross-classroom and cross-platform experiments showed the proposed generic andmulti-modal behavioral engagement models' applicability to a different set ofstudents or different subject areas.

Detecting Behavioral Engagement of Students in the Wild Based on Contextual and Visual Data