Evaluating User Experience in Games: Concepts and Methods - Lirmm

More documents

Recommendations

Info

36 J. Takatalo et al. 3.3 PIFF 2 in Practice We have demonstrated here the multidimensional and psychological nature of the UX in games. The rest of the chapter presents two distinct practical examples of how to utilize the mapping of PIFF 2 subcomponents in different phases of the game development life cycle. First, all the subcomponents are used to compare groups of expert gamers in two different games. Psychological profile provided by the PIFF 2 is compared against METASCORE R○ and user ratings provided by the Metacritic.com (Metacritic.com 2009). However, sometimes more detailed information about a specific game feature is needed as quickly and efficiently as possible. Using only selected PIFF 2 subcomponents in a more qualitative manner would then be a better choice. Our second case deals with an individual-level analysis of experienced game difficulty and learning of skills during the first hour of play. Analysis of game mechanics and qualitative interview are integrated into this case. However, the use of complete subscales with several participants guarantees more extensive and reliable results. 3.3.1 Between Groups: PIFF 2 in Two Different Games A standard way of using PIFF 2 is to gather post-game experiences with an EVEQ- GP questionnaire. This would be most beneficial, for example, in the production phase when all content can be represented, but there is still time and possibility to introduce changes before releasing the game. If used as a post-launch study, a PIFF 2 analysis can provide useful information and facilitate evaluation of the released product. Here, we conduct such a post-launch analysis to two first-person shooters (FPS) and compare PIFF 2 profiles with the METASCORE R○ and the user ratings of these games. Both these numeric values are provided by the Metacritic.com (Metacritic.com 2009). METASCORE R○ is based on a weighted average of various scores assigned by expert critics to that game. The user ratings are means of all the ratings given to a game by the users. Metacritic.com provides the amount of users that have rated a particular game. This comparison will demonstrate the added value of the psychological and multidimensional analysis of the UX based on gamers’ own reflections from the game. The data included 109 expert male gamers, who played either Valve’s Half- Life 2 (HL2; n = 62) or Counter Strike: Source (CS; n = 47), both run by the same Source R○ game engine. This makes the interface in studied games exactly the same. After they finish playing either HL2 or CS, each gamer filled in the EVEQ- GP in our Internet survey. HL2 is described as “it opens the door to a world where the player’s presence affects everything around him, from the physical environment to the behaviors even the emotions of both friends and enemies. The player again picks up the crowbar of research scientist Gordon Freeman, who finds himself on an alien-infested Earth being picked to the bone, its resources depleted, its populace dwindling” (Half-Life 2 2004). In CS, gamers can “engage in an incredibly realistic
3 Presence, Involvement, and Flow in Digital Games 37 brand of terrorist warfare in this wildly popular team-based game” (Counter-Strike: Source 2004). In addition, “CS modifies the multiplayer aspects of ‘Half-Life’ to bring it a more team-oriented game play. CS provides the player with an experience that a trained counter-terrorist unit or terrorist unit experiences” (Metacritic.com 2009). Thus, there were differences in game mechanics and narrative between HL2 and CS. HL2 has received a METASCORE R○ of 96/100 based on 81 reviews and CS 88/100 based on nine reviews. A METASCORE R○ between 90 and 100 is considered as a “Universal Acclaim” and between 75 and 89 a “Generally favorable reviews” (Metacritic.com 2009). The users rated HL2 9,3/10 (3487 votes) and CS 9,2/10 (7532 votes) (situation in March 22, 2009). Although the background of the players rating the games was not standardized in any ways (e.g., skill, gender), this variation between scores and ratings gives an interesting starting point for the inspection of the PIFF 2 profiles. Two distinct between-subjects multivariate analyses of variance (MANOVA) were conducted for both presence and involvement as well as flow subcomponents. Significant differences in MANOVA’s were further studied in univariate analyses. The UX determinants are included in bold face. Figure 3.3 shows that the levels of both presence and involvement differed between the games (Wilk’s Lambda = 0.70, F(8,100) = 5.46, p
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 65: 3 Presence, Involvement, and Flow i
Page 77 and 78: Chapter 4 Assessing the Core Elemen
Page 79 and 80: 4 Assessing the Core Elements of th
Page 101: 4 Assessing the Core Elements of th
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 and 268:
Page 269 and 270:
Page 271 and 272:
Page 273 and 274:
Page 275 and 276:
Page 277 and 278:
Page 279 and 280:
Page 281 and 282:
Page 283 and 284:
Page 285 and 286:
Page 287 and 288:
Index A Advanced interaction games,
show all

Evaluating User Experience in Games: Concepts and Methods - Lirmm

You also want an ePaper? Increase the reach of your titles

Delete template?

Save as template?