A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf
.
Unobtrusive and Multimodal Approach for Behavioral Engagement Detection of Students
[article]
2019
arXiv
pre-print
We propose a multimodal approach for detection of students' behavioral engagement states (i.e., On-Task vs. Off-Task), based on three unobtrusive modalities: Appearance, Context-Performance, and Mouse. Final behavioral engagement states are achieved by fusing modality-specific classifiers at the decision level. Various experiments were conducted on a student dataset collected in an authentic classroom.
arXiv:1901.05835v1
fatcat:73njb4q24vd4zlbhesyjxsbziq