Computer Science
ATL-BP: A Student Engagement Dataset and Model for Affect Transfer Learning for Behavior Prediction
Document Type
Article
Abstract
We propose a video-based transfer learning approach for predicting problem outcomes of students working with an intelligent tutoring system (ITS) by analyzing their faces and gestures. The ability to predict such outcomes enables tutoring systems to adjust interventions and ultimately yield improved student learning. We collected and released a labeled dataset of 2,749 problem-solving interaction samples of 54 students working with an intelligent online math tutor. Our transfer-learning challenge was then to design a representation in the source domain of images obtained from the Internet for facial expression analysis, and transfer this learned representation for human behavior prediction in the domain of webcam videos of students in a classroom environment. We developed a novel facial affect representation and a user-personalized training scheme that unlocks the potential of this representation. We designed several variants of a recurrent neural network that models the temporal structure of video sequences. Our final model, named ATL-BP for Affect Transfer Learning for Behavior Prediction, achieves a relative increase in the mean F-score of 50% over the state-of-the-art method on this new dataset. We also propose an additional set of annotations to predict students' engagement while solving a specific problem, and present models that can predict such engagement.
Publication Title
IEEE Transactions on Biometrics, Behavior, and Identity Science
Publication Date
2023
Volume
5
Issue
3
First Page
411
Last Page
424
DOI
10.1109/TBIOM.2022.3210479
Keywords
behavior prediction, engagement prediction, intelligent tutoring system, Transfer learning, video classification
Repository Citation
Ruiz, Nataniel; Yu, Hao; Allessio, Danielle A.; Jalal, Mona; Joshi, Ajjen; Murray, Tom; Magee, John J.; Delgado, Kevin Manuel; Ablavsky, Vitaly; Sclaroff, Stan; Arroyo, Ivon; Woolf, Beverly P.; Bargal, Sarah Adel; and Betke, Margrit, "ATL-BP: A Student Engagement Dataset and Model for Affect Transfer Learning for Behavior Prediction" (2023). Computer Science. 9.
https://commons.clarku.edu/faculty_computer_sciences/9
APA Citation
Ruiz, N., Yu, H., Allessio, D. A., Jalal, M., Joshi, A., Murray, T., ... & Betke, M. (2022). ATL-BP: a student engagement dataset and model for affect transfer learning for behavior prediction. IEEE Transactions on Biometrics, Behavior, and Identity Science.
