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.
Originalsprache | Englisch |
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Titel | CHI EA '16 Proceedings of the 2016 CHI Conference Extended Abstracts on Human Factors in Computing Systems |
Seiten | 1835-1841 |
Seitenumfang | 7 |
DOIs | |
Publikationsstatus | Veröffentlicht - 2016 |
Veranstaltung | CHI 2016 - Conference on Human Factors in Computing Systems - Dauer: 7 Mai 2016 → 12 Mai 2016 |
Konferenz
Konferenz | CHI 2016 - Conference on Human Factors in Computing Systems |
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Zeitraum | 7/05/16 → 12/05/16 |
Research Field
- Ehemaliges Research Field - Technology Experience
Schlagwörter
- Player type models; games; personalization