Affective Sequences and Student Actions Within Reasoning Mind

artificial intelligence in education(2020)

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摘要
Now that the modeling of affective states is beginning to mature, understanding affect dynamics has become an increasingly realistic endeavor. However, the results from empirical studies have not always matched those of theoretical models, which raises questions as to why. In this study, we explore the relationship between affective sequences that have been previously explored in the literature and the activities students may engage in when interacting with Reasoning Mind, a blended learning system for elementary mathematics. The strongest correlations are found for students who shift from engaged concentration to frustration, making fewer actions in the system. While confusion is generally associated with positive patterns, and frustration and boredom have unexpectedly similar implications for student activity.
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关键词
student actions,mind
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