Affect-aware tutors: recognising and responding to student affect
International Journal of Learning Technology
3D corpus of spontaneous complex mental states
ACII'11 Proceedings of the 4th international conference on Affective computing and intelligent interaction - Volume Part I
Modeling how students learn to program
Proceedings of the 43rd ACM technical symposium on Computer Science Education
What do students learn about programming from game, music video, and storytelling projects?
Proceedings of the 43rd ACM technical symposium on Computer Science Education
Multimodal analysis of the implicit affective channel in computer-mediated textual communication
Proceedings of the 14th ACM international conference on Multimodal interaction
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Emotion, or affect, plays a central role in learning. In particular, promoting positive emotions throughout the learning process is important for students' motivation to pursue computer science and for retaining computer science students. Positive emotions, such as engagement or enjoyment, may be fostered by timely individualized help. Especially promising are interventions if the student is having difficulty completing a task. Recognizing when a student is facing a complex task may better inform teachers or adaptive learning environments about the students' affective states, which in turn can inform instructional adaptations. We approach this research goal by analyzing a data set of student facial videos from computer-mediated human tutorial sessions in Java programming. Students and tutors interacted with a synchronized web-based development environment. The tutorial sessions were divided into six lessons each with subtasks, and featured corresponding learning objectives for the students. In post-hoc analysis, we identified "difficult" tasks by comparing the frequencies of student-tutor interaction and task behaviors such as running the program and the time to complete tasks. Nonverbal behaviors, such as gesturing or postural shifting, were then compared with task difficulty. Understanding such nonverbal behavior can inform individualized interventions, which may keep students engaged and foster greater learning gains.