Original Paper

User Modeling and User-Adapted Interaction

, Volume 18, Issue 3, pp 287-314

First online:

Developing a generalizable detector of when students game the system

  • Ryan S. J. d. BakerAffiliated withHuman-Computer Interaction Institute, Carnegie Mellon University Email author 
  • , Albert T. CorbettAffiliated withHuman-Computer Interaction Institute, Carnegie Mellon University
  • , Ido RollAffiliated withHuman-Computer Interaction Institute, Carnegie Mellon University
  • , Kenneth R. KoedingerAffiliated withHuman-Computer Interaction Institute, Carnegie Mellon University

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Abstract

Some students, when working in interactive learning environments, attempt to “game the system”, attempting to succeed in the environment by exploiting properties of the system rather than by learning the material and trying to use that knowledge to answer correctly. In this paper, we present a system that can accurately detect whether a student is gaming the system, within a Cognitive Tutor mathematics curricula. Our detector also distinguishes between two distinct types of gaming which are associated with different learning outcomes. We explore this detector’s generalizability, and find that it transfers successfully to both new students and new tutor lessons.

Keywords

Gaming the system Latent response models Cognitive tutors Behavior detection Machine learning Generalizable models Student modeling Interactive learning environments