AI-Supported Simulation-Based Learning: Learners’ Emotional Experiences and Self-Regulation in Challenging Situations

Abstract

This study explores learners’ emotional experiences and self-regulation and how they overcome stressful situations in a simulation-based learning environment (SBLE). We also examine what kinds of situations an AI tutor could be used to facilitate simulation-based learning. We will first present the theoretical background of the research dealing with self-regulated learning, followed by positive and negative emotions and situations in simulation-based learning. The research questions of the study are as follows: (1) What kinds of emotions do learners experience in simulation-based learning situations? (2) Through what kinds of SRL operations do learners aim to overcome challenging situations during simulation-based learning? and (3) In what kinds of situations could an AI tutor be used to facilitate simulation-based learning? To collect data, a 1-week experiment was conducted in August 2021. The data was collected using online observations, video recordings, and delayed stimulated recall interviews. The interview data was analyzed through a deductive thematic analysis process. The results of the study show that learners experienced various positive and negative emotions and emotions are deeply connected with learning. We need to do more research to describe these connections in more detail. According to the results, an AI tutor can provide help for decision-making and visualizing critical points and help learners ask questions to check vital points in the system.