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Abstract Title: Fun and Gaming with Andes
Abstract: We present results from an analysis of students' shallow behaviors,
i.e., gaming, during their interaction with an Intelligent Tutoring System.  We have developed a method for detecting gaming based on timings of student actions.  We use this method to analyze student log data taken from six college classes that used the Andes tutor system for homework and test preparation.   Our findings show that contrary to other research, student features are a better predictor of gaming than problem features.  We also find that students engaged in gaming for a significant fraction of their work.
Abstract Type: Contributed Poster

Contributed Poster

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Author/Organizer Information

Primary Contact: Brett van de Sande
Arizona State University
and Co-Presenter(s)
Kasia Muldner, Winslow Burleson, and Kurt VanLehn, Arizona State University.