Research in affective computing and educational technology has shown the potential of affective interventions to increase student's self-concept and motivation while learning. Our project aims to investigate whether the use of affective interventions in a meta-cognitive tutor can help students achieve deeper modeling of dynamic systems by being persistent in their use of meta-cognitive strategies during and after tutoring. This article is an experience report on how we designed and implemented the affective intervention. (The meta-tutor is described in a separate paper.) We briefly describe the theories of affect underlying the design and how the agent's affective behavior is defined and implemented. Finally, the evaluation of a detector-driven categorization of student behavior, that guides the agent's affective interventions, against a categorization performed by human coders, is presented. © 2013 Springer-Verlag Berlin Heidelberg.
CITATION STYLE
Girard, S., Chavez-Echeagaray, M. E., Gonzalez-Sanchez, J., Hidalgo-Pontet, Y., Zhang, L., Burleson, W., & Vanlehn, K. (2013). Defining the behavior of an affective learning companion in the affective meta-tutor project. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 7926 LNAI, pp. 21–30). Springer Verlag. https://doi.org/10.1007/978-3-642-39112-5_3
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