Evaluating User Experience in Games: Concepts and Methods - Lirmm

More documents

Recommendations

Info

238 C. Koeffel et al. (see following section), no particular work on how to evaluate user experience through the application of heuristics has been introduced. 13.4 History of Heuristics for Video Games In the following, a brief overview of the history of heuristics for video games will be presented, starting with Malone who was the first one to introduce the idea of using heuristics to evaluate games (Malone 1980, 1982). His heuristics mainly focused on educational games, not possessing the graphical, acoustic and computational possibilities that current video games offer. Malone categorised his heuristics into challenge, fantasy and curiosity. Although Malone has introduced his heuristics as early as 1980, this method was adopted by a wider audience with Jakob Nielsen’s 10 heuristics introduced in 1994 (Nielsen 1994). Since then, these 10 heuristics are the mostly referenced set of heuristics and frequently used for different kinds of applications. Originally, they have been developed for traditional interfaces, nevertheless they are also (to a certain extent) applicable to several other areas such as pervasive games or video games. Federoff assessed the applicability of these heuristics to the area of video games (Federoff 2002). She discovered that they were usable and developed a set of 40 heuristics which were partially based on Nielsen’s heuristics. For a better overview and easier assignment of single problems to heuristics, she categorised them into game interface, game mechanics and game play. We think that the heuristics published by Federoff appear slightly superficial and sometimes do not cover the entire extent of facets offered by video games, especially when considering the capabilities of state-of-the-art video games. Furthermore, they appear to concentrate on role-playing games and are therefore not applicable to all possible game genres. In 2004 Desurvire et al. released a new set of verified heuristics, the HEP (heuristic evaluation of playability), which were based on the heuristics introduced by Federoff (Desurvire et al. 2004). In contrast to Federoff’s approach, these heuristics were categorised into four sections: game story, game play, game mechanics and game usability. Through further evaluations, these heuristics have proven to be effective. We think that the heuristics by Desurvire et al. do not consider the important impact of challenge on the user’s experience. Nevertheless, the categorisation of heuristics for video games into game play, game story, game mechanics and game usability has been taken into account when formulating our framework. Two years after Desurvire et al. designed their heuristics, Röcker and Haar tested the adaptability of these heuristics to the area of pervasive games (Röcker and Haar 2006). It was their basic assumption that no aspects related to the game platform were to be found in the heuristics for game play and game story. Furthermore, they expected this information to be contained in the categories game mechanics and game usability, which were deemed to be platform dependent. For this reason, these heuristics had to be reconsidered. The results of a study connected to their investigations revealed that the heuristics concerning the game mechanics are the same for all types of
13 Using Heuristics to Evaluate the Overall User Experience 239 games. Besides the evaluation of pervasive games, the evaluation of mobile games has also been of interest to researchers. In 2006, Nokia released a framework for the evaluation of the playability of mobile games (Koivisto and Korhonen 2006). Their framework is split into modules containing heuristics for game play, game usability and mobility. The modules do not have to be evaluated at the same time, and at least the modules concerning game play and game usability should be able to be applied to other kinds of games, not only mobile games. Another approach towards the evaluation of groupware has been published in Pinelle and Gutwin (2007). They developed the Table-Collaboration Usability Analysis (T-CUA) which is based on the Collaboration Usability Analysis (CUA). It is especially designed to evaluate collaborative groupware and concentrates on issues in connection with teamwork. In April 2007, Schaffer released a white paper introducing a new version of heuristics for video games (Schaffer 2007). According to him, the heuristics introduced so far were too vague, difficult to realise, more suitable to postmortem reviews and not applicable during the design process. He provides a set of detailed heuristics with graphical examples for each heuristic which eases the evaluation significantly, especially when it is not conducted by an expert in the field of computer games. Pinelle et al. introduced a set of heuristics based on game reviews in 2008 (Pinelle et al. 2008). For their work, five researchers reviewed 108 game reviews of the GameSpot 9 website and categorised the issues found into 10 final heuristics. According to Pinelle et al., this approach offers the possibility to evaluate a game’s usability without reviewing unnecessary technical issues and issues related to entertainment. Based on the idea of heuristics for pervasive games by Röcker and Haar (2006), Jegers has introduced a study investigating the special characteristics and issues of pervasive games (Jegers 2008). He criticises the approach of Röcker and Haar as being too focused on Smart Home technology and the evaluation as being too theoretical. Therefore, Jegers has developed a pervasive game and conducted an iterative evaluation using different methods. When comparing his findings to Desurvire’s HEP (Desurvire et al. 2004) and to traditional usability issues, he found out that there are several problems that are not covered by the aforementioned principles. Therefore, he suggests further methodological research in this area. 13.5 User Experience of Games Within recent years, the term “user experience” has become a buzzword within the community focusing on HCI. According to Hassenzahl and Tractinsky (2006), this is the counter-reaction to the more dominant task and work-related usability paradigm. Still, this is not a completely new concept. The American philosopher and psychologist John Dewey described experiences to be “not mere feelings; they 9 http://www.GameSpot.com
Page 2 and 3:
Human-Computer Interaction Series E
Page 4 and 5:
Regina Bernhaupt Editor Evaluating
Page 6:
For Philippe
Page 9 and 10:
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
Page 29:
xxviii About the Authors Theft Auto
Page 33 and 34:
Chapter 1 User Experience Evaluatio
Page 35 and 36:
1 User Experience Evaluation in Ent
Page 37:
1 User Experience Evaluation in Ent
Page 41 and 42:
Chapter 2 Enabling Social Play: A F
Page 43 and 44:
2 Enabling Social Play 13 It is als
Page 45 and 46:
2 Enabling Social Play 15 observati
Page 47 and 48:
2 Enabling Social Play 17 for playe
Page 49 and 50:
2 Enabling Social Play 19 to provid
Page 51 and 52:
2 Enabling Social Play 21 Colwell J
Page 53 and 54:
Chapter 3 Presence, Involvement, an
Page 55 and 56:
3 Presence, Involvement, and Flow i
Page 57 and 58:
Page 59 and 60:
Page 61 and 62:
Page 63 and 64:
Page 65 and 66:
Page 67 and 68:
Page 69 and 70:
Page 71 and 72:
Page 73 and 74:
Page 75 and 76:
Page 77 and 78:
Chapter 4 Assessing the Core Elemen
Page 79 and 80:
4 Assessing the Core Elements of th
Page 81 and 82:
Page 83 and 84:
Page 85 and 86:
Page 87 and 88:
Page 89 and 90:
Page 91 and 92:
Page 93 and 94:
Page 95 and 96:
Page 97 and 98:
Page 99 and 100:
Page 101:
Page 104 and 105:
74 E. Brown (2005). Björk and Holo
Page 106 and 107:
76 E. Brown 5.2.3 How We Work Toget
Page 108 and 109:
78 E. Brown could be simulated on p
Page 110 and 111:
80 E. Brown 5.3.2 Pre-production At
Page 112 and 113:
82 E. Brown from the code. This is
Page 114 and 115:
84 E. Brown At this point, there is
Page 116 and 117:
86 E. Brown Game developers have be
Page 119 and 120:
Chapter 6 Investigating Experiences
Page 121 and 122:
6 Investigating Experiences and Att
Page 123 and 124:
Page 125 and 126:
Page 127 and 128:
Page 129 and 130:
Page 131 and 132:
Page 133 and 134:
Page 135:
Page 138 and 139:
108 G. McAllister and G.R. White Th
Page 140 and 141:
110 G. McAllister and G.R. White su
Page 142 and 143:
112 G. McAllister and G.R. White of
Page 144 and 145:
114 G. McAllister and G.R. White te
Page 146 and 147:
116 G. McAllister and G.R. White qu
Page 148 and 149:
Page 150 and 151:
120 G. McAllister and G.R. White 7.
Page 152 and 153:
Page 154 and 155:
124 G. McAllister and G.R. White an
Page 156 and 157:
126 G. McAllister and G.R. White Al
Page 158 and 159:
128 G. McAllister and G.R. White Ne
Page 161 and 162:
Chapter 8 User Experience Design fo
Page 163 and 164:
8 User Experience Design for Inexpe
Page 165 and 166:
Page 167 and 168:
Page 169 and 170:
Page 171 and 172:
Page 173 and 174:
Page 175 and 176:
Page 177:
Page 180 and 181:
150 K. Poels et al. in games. This
Page 182 and 183:
152 K. Poels et al. their game char
Page 184 and 185:
154 K. Poels et al. If we apply thi
Page 186 and 187:
156 K. Poels et al. Participants ge
Page 188 and 189:
158 K. Poels et al. 9.3.2 Exploring
Page 190 and 191:
160 K. Poels et al. If our train is
Page 192 and 193:
162 K. Poels et al. would be intere
Page 195 and 196:
Chapter 10 Evaluating User Experien
Page 197 and 198:
10 Evaluating User Experience Facto
Page 199 and 200:
Page 201 and 202:
Page 203 and 204:
Page 205 and 206:
Page 207 and 208:
Page 209 and 210:
Page 211 and 212:
Page 213:
Page 217 and 218: Chapter 11 Evaluating Exertion Game
Page 219 and 220: 11 Evaluating Exertion Games 189 pr
Page 221 and 222: 11 Evaluating Exertion Games 191 th
Page 223 and 224: 11 Evaluating Exertion Games 193 to
Page 225 and 226: 11 Evaluating Exertion Games 195 co
Page 227 and 228: 11 Evaluating Exertion Games 197 11
Page 229 and 230: 11 Evaluating Exertion Games 199 an
Page 231 and 232: 11 Evaluating Exertion Games 201 11
Page 233 and 234: 11 Evaluating Exertion Games 203 to
Page 235 and 236: 11 Evaluating Exertion Games 205 Ac
Page 237: 11 Evaluating Exertion Games 207 Pa
Page 240 and 241: 210 M. Brown et al. challenges that
Page 242 and 243: 212 M. Brown et al. was also happen
Page 244 and 245: 214 M. Brown et al. Another importa
Page 246 and 247: 216 M. Brown et al. Albinsson and Z
Page 248 and 249: 218 M. Brown et al. asked to report
Page 250 and 251: 220 M. Brown et al. Table 12.2 Mean
Page 252 and 253: 222 M. Brown et al. Table 12.7 Cont
Page 254 and 255: 224 M. Brown et al. Table 12.9 Cont
Page 256 and 257: 226 M. Brown et al. Count 450 400 3
Page 258 and 259: 228 M. Brown et al. feedback. Thus,
Page 260 and 261: 230 M. Brown et al. Desurvivre H, C
Page 263 and 264: Chapter 13 Using Heuristics to Eval
Page 265 and 266: 13 Using Heuristics to Evaluate the
Page 267: 13 Using Heuristics to Evaluate the
Page 287 and 288: Index A Advanced interaction games,
show all

Evaluating User Experience in Games: Concepts and Methods - Lirmm

Create successful ePaper yourself

Delete template?

Save as template?