Abstract
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 language | English |
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Title of host publication | CHI EA 2016 |
Subtitle of host publication | #chi4good - Extended Abstracts, 34th Annual CHI Conference on Human Factors in Computing Systems |
Publisher | ACM Press |
Pages | 1835-1841 |
Number of pages | 7 |
ISBN (Electronic) | 9781450340823 |
DOIs | |
Publication status | Published - 7 May 2016 |
Event | ACM Conference on Human Factors in Computing Systems (CHI 2016) - San Jose, United States Duration: 7 May 2016 → 12 May 2016 https://chi2016.acm.org |
Publication series
Name | Conference on Human Factors in Computing Systems - Proceedings |
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Volume | 07-12-May-2016 |
Conference
Conference | ACM Conference on Human Factors in Computing Systems (CHI 2016) |
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Country/Territory | United States |
City | San Jose |
Period | 07.05.2016 → 12.05.2016 |
Internet address |
Keywords
- Games
- Personalization
- Player type models