Off-task behavior in the cognitive tutor classroom: when students "game the system"
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Modeling and understanding students' off-task behavior in intelligent tutoring systems
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Developing a generalizable detector of when students game the system
User Modeling and User-Adapted Interaction
The Behavior of Tutoring Systems
International Journal of Artificial Intelligence in Education
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
Classifying learner engagement through integration of multiple data sources
AAAI'06 Proceedings of the 21st national conference on Artificial intelligence - Volume 1
A dynamic mixture model to detect student motivation and proficiency
AAAI'06 Proceedings of the 21st national conference on Artificial intelligence - Volume 1
Detection and analysis of off-task gaming behavior 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
Model-based clustering analysis of student data
ICHIT'11 Proceedings of the 5th international conference on Convergence and hybrid information technology
Detecting the moment of learning
ITS'10 Proceedings of the 10th international conference on Intelligent Tutoring Systems - Volume Part I
The fine-grained impact of gaming (?) on learning
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
Gaze tutor: A gaze-reactive intelligent tutoring system
International Journal of Human-Computer Studies
Does the length of time off-task matter?
Proceedings of the 2nd International Conference on Learning Analytics and Knowledge
Detecting learning moment-by-moment
International Journal of Artificial Intelligence in Education - Special issue on Best of ITS 2010
International Journal of Artificial Intelligence in Education - Special issue on Best of ITS 2010
Proceedings of the Third International Conference on Learning Analytics and Knowledge
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Both gaming the system (taking advantage of the system's feedback and help to succeed in the tutor without learning the material) and being off-task (engaging in behavior that does not involve the system or the learning task) have been previously shown to be associated with poorer learning. In this paper we investigate two hypotheses about the mechanisms that lead to this reduced learning: (a) less learning within individual steps (immediate harmful impact) and (b) overall learning loss due to fewer opportunities to practice (aggregate harmful impact). We show that gaming tends to have immediate harmful impact while off-task tends to have aggregated harmful impact on learning.