Emotional patterns in a simulated virtual classroom supported with an affective recommendation system

Abstract

The purpose of this study is to explore the effects of an affective recommendation system on the developmental trajectories of prospective teachers' emotional patterns, integrated with a Simulated Virtual Classroom (SVC) platform called SimlnClass. SVC exposes teachers to a range of student discourses in the form of unexpected stimuli. Fifteen prospective teachers participated in a study consisting of two practicum sessions in the SVC. Participants did not receive any affective recommendation after the first session but did receive it after the second session. Additional data were collected during both sessions in the SVC, including the physiological responses, such as electroencephalogram (EEG), galvanic skin response (GSR), and facial expressions. L metric and Lag sequential analysis were employed in determining teachers' transitional emotional patterns. The results showed that participants did not maintain disgust after receiving affective recommendations, although they maintained sadness. This result indicates that the given affective recommendation has an inherent effect on negative emotions that are felt less intensely. Different or longer-term interventions may be needed for more intense and long-lasting negative discrete emotions such as sadness. Also, participants transitioned to happiness and sadness instead of maintaining their neutral status after receiving an affective recommendation. This result demonstrates that affective recommendations encourage participants to use the cognitive reappraisal necessary for emotion regulation. When the participants' emotional patterns are examined on the basis of student discourse, the results are more complex and the emotional patterns differ according to the function of the discourse triggered by virtual students.