A fun-accuracy trade-off in game-based learning

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Abstract

The present paper illustrates that the game-based implementation of a learning task - here to train basic math skills - entails benefits with strings attached. We developed a game for learning math with its core element based on the number line estimation task. In this task, participants have to indicate the position of a target number on a number-line, which is thought to train basic numerical skills. Participants completed both the game on a mobile device and a conventional paper-pencil version of the task. They indicated to have significantly more fun using the game-based environment. However, they also made considerably higher estimation errors in the game compared to the paper-pencil version. In this case, more fun in a math-learning task was ultimately bought at the expense of lower reliability, namely lowered accuracy of estimations in the learning game. This fun-accuracy trade-off between adding elements for enjoyment and clarity of content is discussed together with the consequences for game-design.

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APA

Greipl, S., Ninaus, M., Bauer, D., Kiili, K., & Moeller, K. (2019). A fun-accuracy trade-off in game-based learning. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 11385 LNCS, pp. 167–177). Springer Verlag. https://doi.org/10.1007/978-3-030-11548-7_16

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