A major issue in Intelligent Tutoring Systems is off-task student behavior, especially performance-based gaming, where students systematically exploit tutor behavior in order to advance through a curriculum quickly and easily, with as little active thought directed at the educational content as possible. The goal of this research was to explore the phenomena of off-task gaming behavior within the Assistments system, as well as to develop a passive visual indicator to deter and prevent off-task gaming behavior without active intervention via graphical feedback to the student and teachers. Traditional active intervention approaches were also constructed for comparison purposes, and machine-learned gaming-detection models were developed as a potential invocation and evaluation mechanism. Passive graphical interventions have been well received by teachers, and results are suggestive that they are effective at reducing off-task gaming behavior
