Empirically building and evaluating a probabilistic model of user affect
User Modeling and User-Adapted Interaction
Affect-aware tutors: recognising and responding to student affect
International Journal of Learning Technology
Multimethod assessment of affective experience and expression during deep learning
International Journal of Learning Technology
Modelling affect expression and recognition in an interactive learning environment
International Journal of Learning Technology
Measuring instant emotions during a self-assessment test: the use of FaceReader
Proceedings of the 7th International Conference on Methods and Techniques in Behavioral Research
A model based method for automatic facial expression recognition
ECML'05 Proceedings of the 16th European conference on Machine Learning
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This paper extends upon traditional emotional measurement frameworks used by ITSs in which emotions are analyzed as single, discrete psychological experiences by examining co-occurring emotions (COEs) (e.g., Conati) through a novel methodological approach. In this paper we examined the occurrence of students' embodiment of basic single discrete emotions (SDEs) and COEs (in addition to neutral) using an automatic facial expression recognition program, FaceReader 4.0. This analysis focuses on the sub goal setting task of learners' (N = 50) interaction with MetaTutor, during which a pedagogical agent assisted students to set three relevant sub goals for their learning session. Results indicated that neutral and sadness were the SDEs experienced most by students and also the most represented emotions in COE pairs. COEs represented nearly a quarter of students' embodied emotions.