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

In this study, it is aimed to investigate the interaction between executive functions and affect transitions in a computer simulation-based teaching set of tasks. Executive function is one of the essential competencies for teachers, covering comprehension and supervision of cognitive processes. Participants were selected from a state university. EEG, EDA, and facial expressions data were used for emotion recognition in the research. Data were analyzed through event-related oscillations, sequential pattern mining, and non-parametric analysis. The research results show that pre-service teachers permanently experience being happy, surprised, fearful, and neutral in their teaching tasks. From time to time, there is a transition from neutrality to experiencing surprise and fear. Another study result is that pre-service teachers tend to apply the correct intervention method when they experience happiness. However, they tended to use the wrong intervention method when faced with a situation where they had to maintain the rule while experiencing surprise. This situation was similar to contempt and anger. Pre-service teachers tended to apply the correct intervention method if they experienced contempt when encountering a stimulus that needed to re-apply the intervention method they found. However, if they were angry, they applied the wrong intervention method. In addition, when the executive function skills of the participants were examined according to their emotional states, it was found that working memory performance and updating performance were better in negative valance than in neutral.