The effects of player type on performance: A gamification case study. (February 2019)

• Record Type: Journal Article
• Authors: Lopez, Christian E.; Tucker, Conrad S.
• Is Part Of: Computers in human behavior. Volume 91(2019)
• Page Start: 333
• Page End: 345
• Publication Date: 2019-02
• Subjects: Gamification -- Player types -- Hexad scale -- Performance -- Game elements; Interactive computer systems -- Periodicals; Man-machine systems -- Periodicals; 004.019
• DOI: 10.1016/j.chb.2018.10.005
• Languages: English
• ISSNs: 0747-5632

Abstract

Abstract: The objective of this work was to explore the effects that an individual's Hexad player type has on their performance in gamified applications. Previous studies sought to explore the relationship between player types of individuals and their preference of game elements. However, these studies have been theoretical in nature, never exposing participants to actual gamified applications or analyzing their real-time performance. Consequently, the biases inherent in humans may impact the validity of these studies since humans are rarely mindful of their behavior and preferences before they are faced with the stimuli (e.g., game elements). Moreover, the effects of game elements on an individual's motivation and performance may differ when implemented in an application. With existing theory-based studies on player types, a designer may spend valuable resources tailoring an application according to an individual's player type and his/her perceived preferences and yet, not see any positive effects on performance. In light of these gaps, a case study with a randomized controlled experiment is presented in which individuals' player type, their perception of game elements, and their performance, are assessed. The results indicate that player type correlates with individuals' perception of game elements and performance in the gamified application. These findings support the importance of exploring the relationship between player type and individuals' performance in gamified applications. Moreover, only after controlling for player type, the results reveal that participants who interacted with the gamified application performed better than those who interacted with the non-gamified application. These results highlight the importance of considering individuals' player type and the need for tailoring applications. Given these findings, this work provides guidelines to help tailor gamified applications, based on an individual's player type. Highlights: Gamification improves performance when controlling for player types. Player type correlates to individuals' performance in gamified applications. Individuals' preferences do not fully explain their performance in gamification. Reward elements do not ensure increase performance or motivation in gamification. Tailoring gamification based on player types is a first step towards personalization.