• Journal of Korea Game Society
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• v.17 no.6
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• pp.77-88
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• 2017

The purpose of this study is to compare existing player type theories using data clustering. For the study, 235 result data of the gamified class in second semester of A university at 2016 used. This study applied K-means and Silhouette to decide the appropriate number of clusters. The player types applied in this study are Bartle's 2-D and 3-D player types, Ferro's five types, and BrainHex. According to the results, Bartle's 2D player type was found to be the best in perspective of data clustering. This study also analyzed the distribution of characteristics for each player types. The results of this study are expected to have an impact on player analysis, which is used in the application of gamification or in the development process.

• Journal of Korea Game Society
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• v.17 no.4
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• pp.25-36
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• 2017

The purpose of this study is to verify the difference in academic achievement among Bartle's player types in an educational gamification environment. For the research, we conducted a questionnaire survey of 250 students who took courses at the K - university in $2^{nd}$ semester, 2016. A total of 235 people participated a survey. The Overall score data and player type questionnaire results were combined and statistical analysis was used to validate the difference in academic achievement. According to the results, there was a significant difference in academic achievement by each type of players. The result of this study may be used to design a gamified curriculum considering the characteristics of learner's player types.