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.
The final publication is available at Springer via https://doi.org/10.1007/978-3-319-07221-0_47.