Abstract
Gamification has gained scientific attention as a motivational tool for behavior change in various contexts. When designing gamification, several scholars emphasize the importance of tailoring content to the needs of different users, e.g. by using the gamification user types HEXAD typology. From a theoretical point of view, researchers suggest correlations between HEXAD types and certain game elements, but empirical validation of these assumptions is still lacking. Previous studies show limitations either in terms of sample size or comprehensiveness of analysis. Therefore, this study aims to empirically identify game element preferences of different HEXAD types and to validate both the English and a corresponding German version of the HEXAD scale in a quantitative study design with 1,073 participants. The validation shows that the HEXAD scale is a valuable tool for identifying HEXAD types, with some improvements needed for a better model fit. Correlation analysis shows highly significant correlations between HEXAD types and specific game elements. While Philanthropists are motivated by gifting, administrative roles, and knowledge sharing, Free Spirits prefer creativity tools, exploratory tasks, and learning. Both Achievers and Players like challenges, leaderboards, levels, and competition, but Players are additionally attracted by extrinsic elements such as achievements, points, and rewards. Socializers like social elements, i.e., teams, social discovery, and social networks. Finally, Disruptors like anarchic gameplay and innovation platforms. In general, the results suggest that the HEXAD typology provides helpful and validated guidance for tailored gamification, and our findings should successfully drive future gamification design to maximize the desired behavioral outcome.
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Krath, J., von Korflesch, H.F.O. (2021). Player Types and Game Element Preferences: Investigating the Relationship with the Gamification User Types HEXAD Scale. In: Fang, X. (eds) HCI in Games: Experience Design and Game Mechanics. HCII 2021. Lecture Notes in Computer Science(), vol 12789. Springer, Cham. https://doi.org/10.1007/978-3-030-77277-2_18
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