  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.
