Abstract
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.
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Rajendran, R. (2011). Automatic Identification of Affective States Using Student Log Data in ITS. In: Biswas, G., Bull, S., Kay, J., Mitrovic, A. (eds) Artificial Intelligence in Education. AIED 2011. Lecture Notes in Computer Science(), vol 6738. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-21869-9_118
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DOI: https://doi.org/10.1007/978-3-642-21869-9_118
Publisher Name: Springer, Berlin, Heidelberg
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