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Visualizing Emotional Experiences in Computer-supported One-to-One Tutoring: Based Analysis of Data of Automatic Facial Expression Recognition

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DOI: 10.23977/icamcs2019.07

Author(s)

Qi Fangrou, Chen Zihan, Chen Bo, Lu Jijian

Corresponding Author

Lu Jijian

ABSTRACT

Automatic facial expression recognition (AFER) is able to record big data based on seven kinds of each teacher or student expressions during computer-supported one-to-one tutoring processes. In our analysis of classroom videos, we combined four kinds of expressions (disgust, anger, sad and fear) to be one simple kind of disturbance, and two kinds of expressions (happy and surprise) to pleasure, which we thought could be easier for visualizing emotional experiences. As a result, we utilized a simpler three-dimensional analysis framework for the student’ emotional experience in classroom, comprising pleasure, neutrality, and disturbance, was constructed by us. This framework was used in visualizing teacher’s and student’s different emotional experiences in computer-supported one-to-one tutoring with large data from AFER, which occurred in five tutoring courses in mathematics.

KEYWORDS

Emotional experience, One-to-one tutoring, Computer-supported, Visualization, Big data

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