3 papers
cs.HC2019
Unobtrusive and Multimodal Approach for Behavioral Engagement Detection of Students
Nese Alyuz, Eda Okur, Utku Genc +3
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-Pe…
cs.CY2019
Detecting Behavioral Engagement of Students in the Wild Based on Contextual and Visual Data
Eda Okur, Nese Alyuz, Sinem Aslan +3
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 utiliz…
cs.HC2019
The Importance of Socio-Cultural Differences for Annotating and Detecting the Affective States of Students
Eda Okur, Sinem Aslan, Nese Alyuz +2
The development of real-time affect detection models often depends upon obtaining annotated data for supervised learning by employing human experts to label the student data. One o…