HexArcade: Predicting Hexad User Types By Using Gameful Applications

Maximilian Altmeyer; Gustavo F. Tondello; Antonio Krüger; Lennart E. Nacke

In: Proceedings of the Annual Symposium on Computer-Human Interaction in Play. ACM SIGCHI Annual Symposium On Computer-Human Interaction in Play (CHI Play-2020), November 2-4, Ottawa, ON, Canada, ACM, New York, 11/2020.


Personalization is essential for gameful systems. Past research showed that the Hexad user types model is particularly suitable for personalizing user experiences. The validated Hexad user types questionnaire is an effective tool for scientific purposes. However, it is less suitable in practice for personalizing gameful applications, because filling out a questionnaire potentially affects a person's gameful experience and immersion within an interactive system negatively. Furthermore, studies investigating correlations between Hexad user types and preferences for gamification elements were survey-based (i.e.,not based on user behaviour). In this paper, we improve upon both these aspects. In a user study (N=147), we show that gameful applications can be used to predict Hexad user types and that the interaction behaviour with gamification elements corresponds to a users' Hexad type. Ultimately, participants perceived our gameful applications as more enjoyable and immersive than filling out the Hexad questionnaire.

Weitere Links

chiplay20a-sub7712-cam-i15.pdf (pdf, 2 MB )

Deutsches Forschungszentrum für Künstliche Intelligenz
German Research Center for Artificial Intelligence