Sujith M. Gowda

Affective States and State Tests: Investigating How Affect Throughout the School Year Predicts End of Year Learning Outcomes

In this paper, we investigate the correspondence between student affect in a web-based tutoring platform throughout the school year and learning outcomes at the end of the year, on a high-stakes mathematics exam.

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Towards an Understanding of Affect and Knowledge from Student Interaction with an Intelligent Tutoring System

Csikszentmihalyi’s Flow theory states that a balance between challenge and skill leads to high engagement, overwhelming challenge leads to anxiety or frustration, and insufficient challenge leads to boredom. In this paper, we test this theory within the context of student interaction with an intelligent tutoring system. Automated detectors of student affect and knowledge were developed, validated, and applied to a large data set.

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