How Emotions Change during Learning with an Intelligent Tutoring System
Date:
Abstract: Emotional experiences have a significant impact on learning about complex topics. Yet, challenges exist because emotions are typically operationalized as end products, excluding if, how, and when emotions change during learning and their relation to metacognition and performance with advanced learning technologies such as intelligent tutoring systems (ITSs). In this paper, we addressed these challenges by capturing and analyzing 117 college students’ concurrent and self-reported emotions at 3 time points during learning with MetaTutor, an ITS. Analyses revealed negative relationships between increases in boredom, metacognitive monitoring accuracy, and performance. We also found that if confusion persisted over time during learning, it was detrimental to performance. These findings provide implications for designing affect-sensitive ITSs which foster emotion-regulation and metacognitive monitoring based on changes in emotions during learning to optimize performance.
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