Gamification of Joint Student/System Control over Problem Selection in a Linear Equation Tutor

Yanjin Long, Vincent Aleven

Integrating gamification features in ITSs has become a popular theme in ITSs research. This work focuses on gamification of shared student/system control over problem selection in a linear equation tutor, where the system adaptively selects the problem type while the students select the individual problems. In a 2×2+1+1 classroom experiment with 267 middle school students, we studied the effect, on learning and enjoyment, of two ways of gamifying shared problem selection: performance-based rewards and the possibility to redo completed problems, both common design patterns in games. We also included two ecological control conditions: a standard ITS and a popular algebra game, DragonBox 12+. A novel finding was that of the students who had the freedom to re-practice problems, those who were not given rewards performed significantly better on the post-tests than their counterparts who received rewards. Also, we found that the students who used the tutors learned significantly more than students who used DragonBox 12+. In fact, the latter students did not improve significantly from pre- to post-tests on solving linear equations. Thus, in this study the ITS was more effective than a commercial educational game, even one with great popular acclaim. The results suggest that encouraging re-practice of previously solved problems through rewards is detrimental to student learning, compared to solving new problems. It also produces design recommendations for incorporating gamification features in ITSs.

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