Automatic detection of learner's affect from conversational cues
User Modeling and User-Adapted Interaction
Coarse-grained detection of student frustration in an introductory programming course
ICER '09 Proceedings of the fifth international workshop on Computing education research workshop
Affect-aware tutors: recognising and responding to student affect
International Journal of Learning Technology
International Journal of Human-Computer Studies
User models for adaptive hypermedia and adaptive educational systems
The adaptive web
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Affect-based computing is one of the important research areas in Intelligent Tutoring Systems (ITS). Previous approaches have dealt with affective state analysis based on the data from hardware sensors like eye-tracker, pressure sensitive chairs. However, automatically identifying the affective states only from the student log data is still an important research question. In this proposal, we identify students' affective states by examining patterns in the ITS student log data that contains information about student response, time taken to answer and so on.