Investigation of the interaction of teacher candidates' executive function skills with emotions in computer simulation environment

Abstract

The study investigates the interaction between executive functions and affect transitions in a computer simulation-based teaching task. Pre-service teachers from a state university participated and data were collected using EEG, EDA and facial expression analysis. The collected data were analyzed using event-related oscillations, sequential pattern mining and Wilcoxon Signed Ranks tests. The results show that pre-service teachers tend to use correct interventions when they are happy, but incorrect interventions when they are surprised or angry. Executive functions, especially working memory, perform better under negative emotions than under neutral conditions. The results highlight the importance of understanding emotional influences on teaching interventions.