The Gamer Types of Seniors and Gamification Strategies Toward Physical Activity

Kuo, Chia Ming; Chen, Hsi-Jen

doi:10.1007/978-3-030-22015-0_14

Cited by 4 publications

(2 citation statements)

References 22 publications

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“…The number of studies which investigate player types are quite limited in the literature, however there are several studies that uses player types as an individual difference (dos Santos, Bittencourt, & Vassileva, 2018;Gelder, & Kovenock, 2017;Gil, Cantador, & Marczewski, 2015;Kuo & Chen, 2019;Park & Kim, 2017). The common deficiency of these studies is ignoring the contextual and cultural suitability of generic player typologies and using clear-cut player types in their research processes.…”

Section: Discussionmentioning

confidence: 99%

Digital Player Typologies in Gamification and Game-Based Learning: A Meta-Synthesis

Sezgin¹

2020

BUEFAD

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Educational practices based on individual differences have become more significant as a result of technological advances. Learners today, demand learning processes which contain visual stimuli, ease of use, fast thinking and movement and playful activities. The two of such learning approaches are gamification and game-based learning. This research is a concept-centric meta-synthesis study examining player types as an individual difference in playful learning environments. In this research, the studies which analysed the typology of players, are examined in terms of methods used, game environments and contextual aspects The definitions and classifications given in 11 researches were reviewed in detail and analysed in terms of their findings and conclusions. Content analysis revealed the common points and 9 different thematic components in relation to general player typology were identified. According to study, it is concluded that, player typologies can be used as an individual difference criterion in the game-based educational processes. However, it is also recognized that player typologies identified by different researchers may not be eligible for all settings and practices. Given that game-based approaches are highly affected from cultural context, cultural characteristics of community of learners should be taken into consideration if these approaches to be employed in learning environments.

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Section: Discussionmentioning

confidence: 99%

Digital Player Typologies in Gamification and Game-Based Learning: A Meta-Synthesis

Sezgin¹

2020

BUEFAD

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“…Studies have been conducted to explore older adults' preferences for gamification elements in terms of personality traits, motivation, age, and gender. Koivisto [32] categorized the player types and personality traits of older users to identify gamification strategies preferred by the same player types in order to design more targeted gamification elements for them. Kappen et al [26,33] investigated the use of gamification elements in physical activity (PA) techniques for older adults and designed gamified PA programs to provide personalized exercise applications for older adults.…”

Section: Related Workmentioning

confidence: 99%

Designing Personalized Persuasive Game Elements for Older Adults in Health Apps

2022

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The use of gamification elements in health apps has been shown to promote healthy behaviors. However, one-size-fits-all gamification strategy does not have the best persuasive effect. Therefore, the aim of this paper was to determine how to select personalized game elements for older adults and use them in health education app design. Firstly, based on the DMC model, the Kano model was used to identify the demand attributes of game mechanisms, and three gamification mechanisms (winning, feedback and reward) preferred by the elderly were selected. Secondly, the corresponding gamification elements were selected by the focus group method, and nine virtual products were generated. Thirdly, the virtual products were rated and conjointly analyzed to obtain the relative importance of gamification mechanisms and the utility values of gamification elements, and a comparative analysis was conducted on four characteristics of older adults: age, gender, personal income, and education. The results obtained the best combination of gamification elements chosen by the elderly under different classifications. Finally, design guidelines on persuasive gamification elements were developed based on the characteristics of older adults, and a modified gamification model was proposed. The results of this study provide suggestions and guidelines for the design of persuasive gamification in health education apps, which will help improve the satisfaction of older adults with health apps.

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