Sarkar, Anurag, Williams, Michael, Deterding, Christoph Sebastian orcid.org/0000-0003-0033-2104 et al. (1 more author) (2017) Engagement Effects of Player Rating System-Based Matchmaking for Level Ordering in Human Computation Games. In: Canossa, Alessandro, Sicart, Miguel, Harteveld, Casper, Zhu, Jichen and Deterding, Sebastian, (eds.) Proceedings of the 12th International Conference on the Foundations of Digital Games, FDG 2017. International Conference on the Foundations of Digital Games 2017, 14-17 Aug 2017 ACM Proceedings . ACM , USA
Abstract
Human computation games lack established ways of balancing the difficulty of tasks or levels served to players, potentially contributing to their low engagement rates. Traditional player rating systems have been suggested as a potential solution: using them to rate both players and tasks could estimate player skill and task difficulty and fuel player-task matchmaking. However, neither the effect of difficulty balancing on engagement in human computation games nor the use of player rating systems for this purpose has been empirically tested. We therefore examined the engagement effects of using the Glicko-2 player rating system to order tasks in the human computation game Paradox. An online experiment (n=294) found that both matchmaking-based and pure difficulty-based ordering of tasks led to significantly more attempted and completed levels than random ordering. Additionally, both matchmaking and random ordering led to significantly more di cult tasks being completed than pure difficulty-based ordering. We conclude that poor balancing contributes to poor engagement in human computation games, and that player rating system-based difficulty rating may be a viable and efficient way of improving both.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | This is an author-produced version of the published paper. Uploaded in accordance with the publisher’s self-archiving policy. Further copying may not be permitted; contact the publisher for details |
Keywords: | human computation games,matchmaking,player rating systems,difficulty balancing,Glicko-2,level ordering,Player rating systems,Level ordering,Human computation games,Matchmaking,Difficulty balancing |
Dates: |
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Institution: | The University of York |
Academic Units: | The University of York > Faculty of Arts and Humanities (York) > Theatre, Film, TV and Interactive Media (York) |
Funding Information: | Funder Grant number EPSRC EP/M023265/1 |
Depositing User: | Pure (York) |
Date Deposited: | 04 Jul 2017 13:30 |
Last Modified: | 16 Oct 2024 10:52 |
Published Version: | https://doi.org/10.1145/3102071.3102093 |
Status: | Published |
Publisher: | ACM |
Series Name: | ACM Proceedings |
Identification Number: | 10.1145/3102071.3102093 |
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Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:118622 |