Evaluating User Experience in Games: Concepts and Methods - Lirmm

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42 J. Takatalo et al. (e.g., usability) in order to analyze design goals at particular game levels, game features, or user groups. The touch-screen can be used at home as well as in the laboratory and the time period evaluated can range from minutes to days, depending on the scope of the study. 3.4 Contributions and Future Challenges Numerous concepts have been proposed to describe and explain the UX in games. Clearly, there is no one concept alone, but rather a wide and multidimensional array of psychologically relevant subcomponents that can capture the experiential richness provided by digital games. PIFF 2 provides one way of integrating such subcomponents into a single framework. Although it is based on the wider concepts of presence, involvement, and flow, PIFF 2 aims at understanding the subcomponents of “being there” and “optimal experience,” for example, when playing games. Theoretically, PIFF 2 is founded on previous studies conducted in the field of game research, while it takes into consideration the basic psychology and the game content, that is, fundamental game components (i.e., the mechanics, the narrative, and the interface). Methodologically, it is based on a large multivariate data set that is psychometrically analyzed in order to establish a reliable and valid set of subcomponents. These analyses have provided 15 subcomponents for analyzing the UX in games. These subcomponents disclose the content, quality, meaning, value, intensity, and extensity of the UX. It was shown here how PIFF 2 can be utilized to analyze the UX in a group and individual contexts. Because in PIFF 2 gamers are considered to be in a game world instead of merely using a game, this framework enables consideration of a broad range of psychological phenomena occurring in games. This is beneficial for basic research in games. As it was shown in the two cases presented, PIFF 2 metrics can be incorporated into different phases of the game development cycle. In the concept and prototyping phases, a multidimensional framework will be helpful in determining the desired psychological attributes for the UX. Designers can use the psychological information as inspiration and support for their own thoughts when creating new and added value for their games. In the production phase, quality assurance professionals and those evaluating beta versions of the games appreciate validated and reliable tools when evaluating the UX alongside game usability. Although EVEQ-GP seems to work well in the research settings, future work will involve condensing it into a more convenient tool to be used in various experimental settings. It will then be used to collect multicultural data to support the current framework. The use of the individual PIFF 2 subcomponents for the study of specific game design problems will also be considered in more detail. This will include studying the relationships between different PIFF 2 subcomponents and the game components. In future, we will deepen the social and story-related subcomponents of the PIFF 2 in order to deal with socially rich game contents, such as massively multiplayer online role-playing games. The current multidimensional structure of PIFF 2 provides a firm foundation for these future goals.
3 Presence, Involvement, and Flow in Digital Games 43 Acknowledgments We thank prof. Takashi Kawai, Antti Hulsi, Heikki Särkelä, Jeppe Komulainen, Miikka Lehtonen, Maija Pekkola, Jaakko Sipari, and Jari Lipsanen for help in collecting and analyzing the data and sharing thoughts. This work has been supported by the User Centered Information Technology graduate school, Oskar Öflund’s Foundation and the Kone Foundation. Appendix 1: The Final PFA of the Presence and Involvement Measurement Model Total variance explained Factor Total Initial Eigen values Percentage of variance Cumulative percentage Total Extraction sums of squared loadings Rotation Percentage of variance Cumulative percentage Total Role engagement 19,650 23,674 23,674 19,125 23,042 23,042 9,382 Attention 6,189 7,456 31,130 5,657 6,816 29,858 8,310 Interest 3,394 4,089 35,220 2,811 3,387 33,245 4,235 Importance 2,715 3,271 38,491 2,204 2,656 35,900 10,179 Co-presence 2,025 2,439 40,930 1,496 1,803 37,703 11,823 Interaction 1,803 2,172 43,103 1,193 1,438 39,141 5,613 Arousal 1,782 2,148 45,250 1,147 1,382 40,523 4,498 Physical presence 1,485 1,789 47,040 954 1,150 41,673 11,537 Extraction method: Principal axis factoring. Appendix 2: The Final PFA of the Flow Measurement Model Total variance explained Factor Total Initial Eigen values Percentage of variance Cumulative percentage Total Extraction sums of squared loadings Rotation Percentage of variance Cumulative percentage Total Valence 13,279 23,713 23,713 12,762 22,788 22,768 7,543 Impressiveness 4,055 7,241 30,955 3,458 6,175 28,963 4,573 Competence 2,540 4,535 35,490 2,020 3,608 32,571 7,453 Challenge 2,013 3,594 39,084 1,445 2,581 35,152 3,272 Enjoyment 1,898 3,371 42,454 1,261 2,252 37,404 4,848 Playfulness 1,695 3,027 45,481 1,140 2,036 39,440 6,707 Control 1,627 2,906 48,387 1,041 1,860 41,298 4,628 Extraction method: Principal axis factoring.
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Human-Computer Interaction Series E
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Regina Bernhaupt Editor Evaluating
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For Philippe
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viii Foreword Chapter 3, Presence I
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x Foreword personality which evolve
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Contents Part I Introduction to Eva
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Contributors Regina Bernhaupt IRIT,
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Contributors xvii Manfred Tscheligi
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Index A Advanced interaction games,
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