The fine-grained impact of gaming (?) on learning
ITS'10 Proceedings of the 10th international conference on Intelligent Tutoring Systems - Volume Part I
A bayes net toolkit for student modeling in intelligent tutoring systems
ITS'06 Proceedings of the 8th international conference on Intelligent Tutoring Systems
Adapting to when students game an intelligent tutoring system
ITS'06 Proceedings of the 8th international conference on Intelligent Tutoring Systems
Scaffolding vs. hints in the assistment system
ITS'06 Proceedings of the 8th international conference on Intelligent Tutoring Systems
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This paper examines the problem of modeling when students are engaged in “gaming the system.” We propose and partially validate an approach that uses a hidden Markov model, as is used in knowledge tracing, to estimate whether the student is gaming on the basis of observable actions By doing so, we provide a common modeling approach that is applicable to gaming, or other constructs such as off task behavior We find that our initial approach gave promising results, with parameter estimates that are plausible, and also exposed some weaknesses in our initial attempt Specifically, that relying solely on response time is probably insufficient to construct a strong model of gaming.