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Among the approaches used to make serious games and learning environments enjoyable, two important ones are 1) adapting task difficulty to match user performance, which leverages the theories of zone of proximal development and flow and 2) providing a high degree of control and choice, which uses constructs from self-determination theory. However, it is not clear whether the two approaches lead to similar results or whether focusing on performance may lead to suboptimal enjoyment. This is relevant since, in addition to being performance-oriented, serious games and learning environments also need to be enjoyable to be effective. To address this issue, we evaluated two kinds of difficulty adaptation in a simple memory training game: one adaptation based solely on difficulty-performance matching and the other based solely on providing a high degree of control/choice. Our results suggest that neither approach is optimal: players enjoyed themselves the most in the control/choice mode, but performed the best in the difficulty-performance matching mode. Player behavior in the game suggests that a trade-off between maximizing performance and maximizing enjoyment could be achieved by a combination of the two approaches. However, long-term studies would be required to determine whether such a combination could indeed be effective.
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