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HexArcade: Predicting Hexad User Types By Using Gameful Applications

Authors:

Maximilian Altmeyer,

Gustavo F. Tondello,

Antonio Krüger,

Lennart E. NackeAuthors Info & Claims

CHI PLAY '20: Proceedings of the Annual Symposium on Computer-Human Interaction in Play

Pages 219 - 230

https://doi.org/10.1145/3410404.3414232

Published: 03 November 2020 Publication History

Abstract

Personalization is essential for gameful systems. Past research showed that the Hexad user types model is particularly suitable for personalizing user experiences. The validated Hexad user types questionnaire is an effective tool for scientific purposes. However, it is less suitable in practice for personalizing gameful applications, because filling out a questionnaire potentially affects a person's gameful experience and immersion within an interactive system negatively. Furthermore, studies investigating correlations between Hexad user types and preferences for gamification elements were survey-based (i.e.,not based on user behaviour). In this paper, we improve upon both these aspects. In a user study (N=147), we show that gameful applications can be used to predict Hexad user types and that the interaction behaviour with gamification elements corresponds to a users' Hexad type. Ultimately, participants perceived our gameful applications as more enjoyable and immersive than filling out the Hexad questionnaire.

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Index Terms

HexArcade: Predicting Hexad User Types By Using Gameful Applications
1. Human-centered computing
  1. Human computer interaction (HCI)
    1. Empirical studies in HCI

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Published In

cover image ACM Conferences

CHI PLAY '20: Proceedings of the Annual Symposium on Computer-Human Interaction in Play

November 2020

621 pages

ISBN:9781450380744

DOI:10.1145/3410404

General Chairs:
Pejman Mirza-Babaei
Ontario Tech University, Canada
,
Victoria McArthur
Carlton University, Canada
,
Program Chairs:
Vero Vanden Abeele
KU Leuven, Belgium
,
Max Birk
Eindhoven University of Technology, Netherlands

Copyright © 2020 Owner/Author.

This work is licensed under a Creative Commons Attribution International 4.0 License.

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Published: 03 November 2020

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Cited By

de Carvalho Barros Bezerra GOliveira WGuimarães Santos AHamari J(2024)Exploring the Use of Unplugged Gamification on Programming Learners’ ExperienceACM Transactions on Computing Education10.1145/368616524:3(1-25)Online publication date: 27-Sep-2024
https://dl.acm.org/doi/10.1145/3686165
Tyack AMekler E(2024)Self-Determination Theory and HCI Games Research: Unfulfilled Promises and Unquestioned ParadigmsACM Transactions on Computer-Human Interaction10.1145/3673230Online publication date: 15-Jun-2024
https://doi.org/10.1145/3673230
Ooge JDe Braekeleer JVerbert K(2024)Nudging Adolescents Towards Recommended Maths Exercises with Gameful RewardsArtificial Intelligence in Education10.1007/978-3-031-64299-9_28(328-335)Online publication date: 2-Jul-2024
https://doi.org/10.1007/978-3-031-64299-9_28
Santos AOliveira WHamari JJoaquim SIsotani S(2023)The Consistency of Gamification User Types: A Study on the Change of Preferences over TimeProceedings of the ACM on Human-Computer Interaction10.1145/36110687:CHI PLAY(1253-1281)Online publication date: 4-Oct-2023
https://dl.acm.org/doi/10.1145/3611068
Krath JAltmeyer MTondello GNacke L(2023)Hexad-12: Developing and Validating a Short Version of the Gamification User Types Hexad ScaleProceedings of the 2023 CHI Conference on Human Factors in Computing Systems10.1145/3544548.3580968(1-18)Online publication date: 19-Apr-2023
https://dl.acm.org/doi/10.1145/3544548.3580968
Chan GArya AOrji RZhao ZWhitehead A(2023)Increasing motivation in social exercise games: personalising gamification elements to player typeBehaviour & Information Technology10.1080/0144929X.2023.2255293(1-31)Online publication date: 13-Sep-2023
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Palomino PRodrigues LLuz AToda ANacke LIsotani S(2023)Predicting user types with symbolic images: An empirical validation based on two card-sorting studiesEntertainment Computing10.1016/j.entcom.2023.10059647(100596)Online publication date: Aug-2023
https://doi.org/10.1016/j.entcom.2023.100596
Hadi Mogavi RDeng CHoffman JHaq EGujar SBucchiarone AHui P(2023)Your Favorite Gameplay Speaks Volumes About You: Predicting User Behavior and Hexad TypeHCI in Games10.1007/978-3-031-35979-8_17(210-228)Online publication date: 23-Jul-2023
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Rodríguez IPuig ARodríguez À(2022)Towards Adaptive Gamification: A Method Using Dynamic Player Profile and a Case StudyApplied Sciences10.3390/app1201048612:1(486)Online publication date: 4-Jan-2022
https://doi.org/10.3390/app12010486
Alalgawi DSadkhan S(2022)Adapt Gamification to Learners' Preferences2022 Fifth College of Science International Conference of Recent Trends in Information Technology (CSCTIT)10.1109/CSCTIT56299.2022.10145630(260-264)Online publication date: 15-Nov-2022
https://doi.org/10.1109/CSCTIT56299.2022.10145630
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