Abstract
We present results from an analysis of students' shallow behaviors, i.e., gaming, during their interaction with an Intelligent Tutoring System (ITS). The analysis is based on six college classes using the Andes ITS for homework and test preparation. Our findings show that student features are a better predictor of gaming than problem features, and that individual differences between students impact where and how students game. © Springer-Verlag Berlin Heidelberg 2010.
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CITATION STYLE
Muldner, K., Burleson, W., Van De Sande, B., & Vanlehn, K. (2010). An analysis of gaming behaviors in an intelligent tutoring system. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 6094 LNCS, pp. 184–193). https://doi.org/10.1007/978-3-642-13388-6_23
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