Demystifying the Relations of Motivation and Emotions in Game-Based Learning: Insights from Co-Occurrence Network Analysis

Abstract

Accumulating evidence indicates that game-based learning is emotionally engaging. However, little is known about the nature of emotions in game-based learning. We extended previous game-based learning research by examining epistemic emotions and their relations to motivational constructs. One-hundred-thirty-one (n=131) 15–18-year-old students played the Antidote COVID-19 game for 25 minutes. Data were collected on their epistemic emotions, flow experience, situational interest, and satisfaction that were measured after the game-playing session. Learners reported significantly higher intensity levels of positive epistemic emotions (excitement, surprise, and curiosity) than negative ones (boredom, anxiety, frustration, and confusion). The co-occurrence network analyses provided new insights into the relationships between motivational and emotional states, where high-intensity flow experience, situational interest, and satisfaction co-occurred the most often with positive epistemic emotions. Results also revealed that a high-intensity flow can be experienced without high levels of situational interest in the topic. That is, gameplay can engage learners even though the learning topic does not interest them. This highlights the importance of intrinsically integrating the learning content with core game mechanics, ensuring the processing of the learning content. The study demonstrated that epistemic emotions, flow experience, satisfaction, and situational interest reveal different qualities of game-based learning. The results suggest that at least flow, situational interest, and epistemic emotions should be measured to understand different dimensions of engagement in game-based learning. Overall, the study advances prior research by clarifying relationships between epistemic emotions and motivational constructs.