Evaluating User Experience in Games: Concepts and Methods - Lirmm

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32 J. Takatalo et al. overlap between flow and presence supports the findings of presence being a prerequisite of flow (Novak et al. 2000). Losing self-consciousness and merging action and awareness have been difficult for respondents to recognize in previous studies (Rettie 2001). The actual state of flow is often characterized as ease of doing, enjoyment and positive valence (pleasure), and the absence of boredom and anxiety (Csikszentmihalyi 1975). Previously, flow has been related to playfulness (e.g., cognitive spontaneity) (Webster and Martocchio 1992) and the sense of control (Ghani and Deshpande 1994, Novak et al. 2000). In addition to these, a wide variety of other emotional feelings has been reported in games, such as, pleasantness, strength, and impressiveness of the experience, amazement, and excitement (Lazzaro 2004, Schubert et al. 2001). Although all the above PIFF subcomponents have a strong theoretical foundation, we have studied them psychometrically in a large empirical data set. 3.2 PIFF: Methodological Background PIFF is based on the quantitative data gathered with the Experimental Virtual Environment Experience Questionnaire-Game Pitkä (i.e., long) (EVEQ-GP). EVEQ-GP is composed of approximately 180 items presented in previous studies concerning the sense of presence (Kim and Biocca 1997, Lessiter et al. 2001, Lombard et al. 2000, Schubert et al. 2001, Usoh et al. 2000, Witmer and Singer 1998), involvement (McQuarrie and Munson 1992), and flow prerequisites and correlates (Della Fave and Massimini 1988, Fontaine 1992, Ghani and Deshpande 1994, Mehrabian and Russell 1974, Novak et al. 2000, Webster and Martocchio 1992). All the items were translated into Finnish and transformed either into a sevenpoint Likert-scale (1 = Strongly Disagree to 7 = Strongly Agree) or into seven-point semantic differentials. The items were modified so that they were assessing experiences received from one game playing session. EVEQ-GP is administered to an individual gamer after a playing session. The gamers who fill in the questionnaire are encouraged to reflect on their subjective experiences of the game they just played. The method enables the participants to report, within the boundaries of the 180 items, how they experienced that particular game. In the field of behavioral sciences, the use of questionnaires has proved to be a valid way of assessing various mental phenomena (Rust and Golombok 1999). The first version of the PIFF was based on two smaller data sets (n = 68 and n = 164). Of the 180 EVEQ-GP items, 146 were used to form 23 subcomponents measuring the UX in games (Takatalo et al. 2004). Thereafter, a heterogeneous data from 2182 Finnish gamers who filled in the questionnaire were collected. Data from laboratory experiments and an Internet survey are included in the data set. The data include approximately 320 different games, various displays (HMD, TV, and CRT), and contexts of play (online, offline, home, and laboratory), giving a broad scope to the UX in games. This data enabled more advanced statistical analyses of the PIFF subcomponents. As a result of these analyses, a refined version of the framework, i.e., PIFF 2 was developed.
3 Presence, Involvement, and Flow in Digital Games 33 physical presence social presence involvement cognitive evaluation emotional outcomes interaction exploration action real being there enclosed attention time distortion spatial arousal drama co-presence social richness interest importance challenge required abilities skill meets demands clear goals ease of doing innovative playful independence control anxiety pleasure valence boredom impressiveness amazement excitement pleasantness enjoyment interaction physical presence attention role engagement co-presence arousal interest importance challenge competence playfulness control valence impressiveness enjoyment Fig. 3.2 The two measurement models that form the PIFF 2 .Ontheleft, measured latent variables in five boxes, in the middle, 139 measured questionnaire items (observed variables) represented in 34 boxes. On the right, 15 factor-analytically (PFA) extracted subcomponents of UX in games Methodologically, PIFF 2 is grounded on two separate multivariate measurement models (Tarkkonen and Vehkalahti 2005), which assessed presence and involvement as well as flow (Fig. 3.2). In psychometrics, measurement models include latent variables (i.e., those difficult to measure straightforwardly), which are measured with observed variables such as questionnaire items. These observed variables are analyzed with multivariate methods to form subcomponents (i.e., measurement scales). These subcomponents thus formed can then be used to assess latent variables. We used principal axis factor analysis (PFA) with an oblique direct Oblimin rotation (delta = 0) independently in both measurement models to compress a large number of questionnaire items into the subcomponents. Of the 180 EVEQ-GP items,
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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
Page 11 and 12: x Foreword personality which evolve
Page 14 and 15: Contents Part I Introduction to Eva
Page 16 and 17: Contributors Regina Bernhaupt IRIT,
Page 18: Contributors xvii Manfred Tscheligi
Page 21 and 22: xx About the Authors Emily Brown is
Page 23 and 24: xxii About the Authors a post-docto
Page 25 and 26: xxiv About the Authors Christina Ko
Page 27 and 28: xxvi About the Authors MIT Media La
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82 E. Brown from the code. This is
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84 E. Brown At this point, there is
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86 E. Brown Game developers have be
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Chapter 6 Investigating Experiences
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6 Investigating Experiences and Att
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Chapter 8 User Experience Design fo
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150 K. Poels et al. in games. This
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Chapter 10 Evaluating User Experien
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Chapter 11 Evaluating Exertion Game
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Index A Advanced interaction games,
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