Player Type Models: Towards Empirical Validation

Marc Busch, Elke Mattheiss, Rita Orji, Peter Fröhlich, Michael Lankes, Manfred Tscheligi

Research output: Chapter in Book/Report/Conference proceedingsConference contributionpeer-review

23 Citations (Scopus)


Player type models – such as the BrainHex model – are popular approaches for personalizing digital games towards individual preferences of players. Although several player type models have been developed and are currently used in game design projects, there is still a lack of data on their validity. To close this research gap we currently investigate the psychometric properties (factor structure, reliability, stability) and predictive validity (if player type scores can predict player experience) of the player type model BrainHex in an ongoing project. Results of two online studies (n1=592, n2=243) show that the psychometric properties of the BrainHex model could be improved. We suggest to improve the according questionnaire and sketch how the predictive validity could be investigated in future studies.
Original languageEnglish
Title of host publicationCHI EA 2016
Subtitle of host publication#chi4good - Extended Abstracts, 34th Annual CHI Conference on Human Factors in Computing Systems
PublisherACM Press
Number of pages7
ISBN (Electronic)9781450340823
Publication statusPublished - 7 May 2016
EventACM Conference on Human Factors in Computing Systems (CHI 2016) - San Jose, United States
Duration: 7 May 201612 May 2016

Publication series

NameConference on Human Factors in Computing Systems - Proceedings


ConferenceACM Conference on Human Factors in Computing Systems (CHI 2016)
CountryUnited States
CitySan Jose
Internet address


  • Games
  • Personalization
  • Player type models

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