Off-task behavior in the cognitive tutor classroom: when students "game the system"
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Inferring learning and attitudes from a Bayesian Network of log file data
Proceedings of the 2005 conference on Artificial Intelligence in Education: Supporting Learning through Intelligent and Socially Informed Technology
Effects of Dissuading Unnecessary Help Requests While Providing Proactive Help
Proceedings of the 2005 conference on Artificial Intelligence in Education: Supporting Learning through Intelligent and Socially Informed Technology
Affect and Usage Choices in Simulation Problem-Solving Environments
Proceedings of the 2007 conference on Artificial Intelligence in Education: Building Technology Rich Learning Contexts That Work
Repairing Disengagement With Non-Invasive Interventions
Proceedings of the 2007 conference on Artificial Intelligence in Education: Building Technology Rich Learning Contexts That Work
Can Help Seeking Be Tutored? Searching for the Secret Sauce of Metacognitive Tutoring
Proceedings of the 2007 conference on Artificial Intelligence in Education: Building Technology Rich Learning Contexts That Work
Adapting to when students game an intelligent tutoring system
ITS'06 Proceedings of the 8th international conference on Intelligent Tutoring Systems
Prevention of off-task gaming behavior in intelligent tutoring systems
ITS'06 Proceedings of the 8th international conference on Intelligent Tutoring Systems
Off-topic essay detection using short prompt texts
IUNLPBEA '10 Proceedings of the NAACL HLT 2010 Fifth Workshop on Innovative Use of NLP for Building Educational Applications
Designing affective computing learning companions with teachers as design partners.
Proceedings of the 3rd international workshop on Affective interaction in natural environments
An analysis of students' gaming behaviors in an intelligent tutoring system: predictors and impacts
User Modeling and User-Adapted Interaction
Detecting gaming the system in constraint-based tutors
UMAP'10 Proceedings of the 18th international conference on User Modeling, Adaptation, and Personalization
An analysis of gaming behaviors in an intelligent tutoring system
ITS'10 Proceedings of the 10th international conference on Intelligent Tutoring Systems - Volume Part I
Squeezing out gaming behavior in a dialog-based ITS
ITS'10 Proceedings of the 10th international conference on Intelligent Tutoring Systems - Volume Part I
WTF? detecting students who are conducting inquiry without thinking fastidiously
UMAP'12 Proceedings of the 20th international conference on User Modeling, Adaptation, and Personalization
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Gaming the system, attempting to succeed in an interactive learning environment by exploiting properties of the system rather than by learning the material (for example, by systematically guessing or abusing hints), is prevalent across many types of educational software. Past research on why students choose to game has focused on student individual differences. Many student individual differences, including attitudes towards mathematics, have been shown to be associated with gaming, but generally with low correlation. In this paper, we investigate how individual differences between learning environments can increase or decrease the probability of gaming. We enumerate ways intelligent tutor lessons vary from each other, and use data mining to discover hypotheses about how differences in software design and content influence the choice to game the system. We discover a set of tutor features that explain 56% of the variance in gaming, over five times the degree of variance explained in any prior study of student individual differences and gaming. These results provide an important step towards developing prescriptions for designing intelligent tutor software that students game significantly less.