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Cited by 403

The DOI matches its Crossref record; 108 of the 108 references it cites were found in a registry or an index.

Tailored gamification: A review of literature

Open access
Klock, Ana Carolina Tomé, Gasparini, Isabela, Pimenta, Marcelo Soares, Hamari, Juho·2020·International Journal of Human-Computer Studies

Abstract

Gamification is increasingly becoming a pertinent aspect of any UI and UX design. However, a canonical dearth in research and application of gamification has been related to the role of individual differences in susceptibility to gamification and its varied designs. To address this gap, this study reviews the extant corpus of research on tailored gamification (42 studies). The findings of the review indicate that most studies on the field are mostly focused on user modeling for a future personalization, adaptation, or recommendation of game elements. This user model usually contains the users’ preferences of play (i.e., player types), and is mostly applied in educational settings. The main contributions of this paper are a standardized terminology of the game elements used in tailored gamification, the discussion on the most suitable game elements for each users’ characteristic, and a research agenda including dynamic modeling, exploring multiple characteristics simultaneously, and understanding the effects of other aspects of the interaction on user experience.

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Metadata

Authors
Klock, A. C. T., Gasparini, I., Pimenta, M. S., & Hamari, J.
Venue
International Journal of Human-Computer Studies
Publisher
Elsevier BV
Published
2020-12
Volume
144
Pages
102495
ISSN
1071-5819 (ISSN-L)
OpenAlex
W3034650940
Cited by
403
References
108
FWCI
71.95
Type
journal article
Language
en
Open access
hybrid

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CoChat. (2026). Citation check: Tailored gamification: A review of literature. https://app.cochat.ai/papers/10.1016/j.ijhcs.2020.102495
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Klock, A. C. T., Gasparini, I., Pimenta, M. S., & Hamari, J. (2020). Tailored gamification: A review of literature. International Journal of Human-Computer Studies. https://doi.org/10.1016/j.ijhcs.2020.102495

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.