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2006

A Dynamic Mixture Model to Detect Student Motivation and Proficiency

10 years 4 months ago
A Dynamic Mixture Model to Detect Student Motivation and Proficiency
Unmotivated students do not reap the full rewards of using a computer-based intelligent tutoring system. Detection of improper behavior is thus an important component of an online student model. To meet this challenge, we present a dynamic mixture model based on Item Response Theory. This model, which simultaneously estimates a student's proficiency and changing motivation level, was tested with data of high school students using a geometry tutoring system. By accounting for student motivation, the dynamic mixture model can more accurately estimate proficiency and the probability of a correct response. The model's generality is an added benefit, making it applicable to many intelligent tutoring systems as well as other domains.
Jeffrey Johns, Beverly Park Woolf
Added 30 Oct 2010
Updated 30 Oct 2010
Type Conference
Year 2006
Where AAAI
Authors Jeffrey Johns, Beverly Park Woolf
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