research-article

Towards Quantifying Player's Involvement in 3D Games Based-on Player Types

Authors:

Deborah Richards,

Michael Hitchens,

Michael J. JacobsonAuthors Info & Claims

IE2014: Proceedings of the 2014 Conference on Interactive Entertainment

Pages 1 - 10

https://doi.org/10.1145/2677758.2677763

Published: 02 December 2014 Publication History

Abstract

With the varied use of games, the need to measure player's involvement has become prominent. Several studies aimed to quantify users' involvement. However, none of these studies presented a robust framework to measure the player's involvement in games nor considered player types as a factor. In this paper, a framework to quantify automatically the players' involvement in games is presented. This framework consists of three levels and each level includes criteria to evaluate three aspects of 3D games: (1) application level, (2) usage level, and (3) content level. Additionally, the framework's criteria considers player types proposed by Bartle. To validate the results of the framework, player involvement was estimated manually on a case-by-case basis by three experienced evaluators. The manual estimation was then compared with the automatically generated-quantified result produced by the framework. The comparison revealed a significant match.

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Cited By

Richards DBilgin ARanjbartabar HMakhija A(2018)Towards Realtime Adaptation: Uncovering User Models from Experimental DataKnowledge Management and Acquisition for Intelligent Systems10.1007/978-3-319-97289-3_4(46-60)Online publication date: 27-Jul-2018
https://doi.org/10.1007/978-3-319-97289-3_4
de Haan JRichards DDignum F(2017)Aiding learning efficiency in virtual worlds2017 23rd International Conference on Virtual System & Multimedia (VSMM)10.1109/VSMM.2017.8346286(1-8)Online publication date: Oct-2017
https://doi.org/10.1109/VSMM.2017.8346286

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Towards Quantifying Player's Involvement in 3D Games Based-on Player Types

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cover image ACM Other conferences

IE2014: Proceedings of the 2014 Conference on Interactive Entertainment

December 2014

259 pages

ISBN:9781450327909

DOI:10.1145/2677758

Editors:
Karen Blackmore
University of Newcastle
,
Keith Nesbitt
University of Newcastle
,
Shamus P. Smith
University of Newcastle

Copyright © 2014 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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Published: 02 December 2014

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December 2 - 3, 2014

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Cited By

Richards DBilgin ARanjbartabar HMakhija A(2018)Towards Realtime Adaptation: Uncovering User Models from Experimental DataKnowledge Management and Acquisition for Intelligent Systems10.1007/978-3-319-97289-3_4(46-60)Online publication date: 27-Jul-2018
https://doi.org/10.1007/978-3-319-97289-3_4
de Haan JRichards DDignum F(2017)Aiding learning efficiency in virtual worlds2017 23rd International Conference on Virtual System & Multimedia (VSMM)10.1109/VSMM.2017.8346286(1-8)Online publication date: Oct-2017
https://doi.org/10.1109/VSMM.2017.8346286

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