2000 character limit reached
Unobtrusive and Multimodal Approach for Behavioral Engagement Detection of Students (1901.05835v1)
Published 16 Jan 2019 in cs.HC, cs.LG, and stat.ML
Abstract: 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.
Sponsor
Paper Prompts
Sign up for free to create and run prompts on this paper using GPT-5.
Top Community Prompts
Collections
Sign up for free to add this paper to one or more collections.