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Personality and Individual Differences 40 (2006) 609–619

The relationship between computer-game preference, gender, and mental-rotation ability Claudia Quaiser-Pohl a


, Christian Geiser b, Wolfgang Lehmann


FB I-Psychology, University of Trier, D-54286 Trier, Germany b University of Geneva, Switzerland c Otto-von-Guericke-University of Magdeburg, Germany

Received 14 December 2004; received in revised form 16 June 2005; accepted 2 July 2005 Available online 10 October 2005

Abstract This study examined how computer-game preference relates to mental-rotation test (MRT) performance and to gender differences. Subjects were 861 German secondary-school children (mean age = 14.67; range 10–20 years). Latent class analysis with the data of a computer-game preference scale revealed three types of players: ‘‘non-players’’, ‘‘action-and-simulation game players’’ and ‘‘logic-and-skill-training game players’’. Large gender differences were found with respect to class assignment. More females than males were found in the ‘‘logic-and-skill-training game player’’ class (82.9%) and in the class of ‘‘non-players’’ (81.9%). Males in contrast were overrepresented (81.7%) in the class of ‘‘action-and-simulation game players’’. As expected, males on average outperformed females in mental-rotation test performance (d = 0.63). Furthermore, ANOVA results indicated mean differences in mental-rotation ability between action-andsimulation players and non-players (partial g2 = .01) as well as age differences (partial g2 = .04). With boys, non-players on average had lower MRT scores than action-and-simulation game players. For females, computer-game preference was unrelated to MRT performance. Results are discussed within a nature–nurtureinteractionist framework of gender differences in spatial abilities. Ó 2005 Elsevier Ltd. All rights reserved. Keywords: Spatial ability; Mental-rotation; Computer-games; Gender differences


Corresponding author. Tel.: +49 651 201 2063; fax: +49 651 201 2961. E-mail address: [email protected] (C. Quaiser-Pohl).

0191-8869/$ - see front matter Ó 2005 Elsevier Ltd. All rights reserved. doi:10.1016/j.paid.2005.07.015


C. Quaiser-Pohl et al. / Personality and Individual Differences 40 (2006) 609–619

1. Introduction Gender differences in spatial abilities are well established (Harris, 1981; McGee, 1979). They depend upon many factors like the subdimension of spatial ability (e.g., mental-rotation or visualization), the speed requirement of the test or the test instruction. One of the largest and most reliable gender differences in favour of males can be found in mental-rotation. Here the effect sizes d range from .56 to over 1.10 (e.g., Halpern, 2000; Linn & Peterson, 1985; Voyer, Voyer, & Bryden, 1995). However, the causes of these differences still remain unclear. Explanations have usually been cast in terms of the nature–nurture controversy (McGee, 1979). On the nature side of the issue biological factors such as genetics, brain lateralization or sex hormones are hypothesized to influence the sex differences (Baron-Cohen, 2003; Hampson, 1990; Kimura, 1992; McGee, 1979). While on the nurture side, socialization and early life experience such as sex-typed play (Denier & Serbin, 1983; Serbin & Connor, 1979), spatial activities (Baenninger & Newcombe, 1989, 1995; Olson & Eliot, 1986), outdoor games involving balls (Bjorklund & Brown, 1998), motivation, self-concept, efficacy, and control have been proposed as explanations for the gender differences (Eccles, 1987). Many studies revealed that experience has a clear effect on spatial abilities. On the one hand, numerous training studies (e.g., Alington, Leaf, & Monaghan, 1992; Connor, Serbin, & Schackman, 1977; Kyllonen, Lohmans, & Snow, 1984; McGee, 1979; Platt & Cohen, 1981; Richardson, 1994) have shown that spatial-test performance can be improved through practice. On the other hand, an improvement of spatial-test performance can also be induced by a training of geometrical skills (Kirby & Boulter, 1999). Furthermore, schooling has a large effect on spatial abilities. For instance, the number of mathematics courses taken is related to spatial-test performance (Burnett & Lane, 1980; Casey, Colon, & Goris, 1992). An investigation using the summer vs. school year design has shown that for kindergarten and first-grade children, growth in spatial ability is more rapid during the school year than during the summer (Baenninger & Newcombe, 1995). Lately, the study of the role of training and experience for individual differences in spatial-test performance has been expanded to computer-related experiences including computer-games (McClurg & Chaille´, 1987; Subrahmanyam & Greenfield, 1994). Playing the computer-game ÔBlockoutÕ, for example, which requires mental-rotation of geometric figures (De Lisi & Cammarano, 1996) and playing the computer game ÔTetrisÕ, which requires rapid rotation and placement of seven differently-shaped blocks, improved spatial-test performance (Ogakaki & Frensch, 1994). Many computer applications (e.g., computer-aided design and drawing) and video games (such as Tetris) require spatial processes such as mental rotation and spatial visualization. In research conducted by Norman (1994), the spatial skill level was found to be the most significant predictor of success in the ability to interact with, and take advantage of the computer interface in performing database manipulation. Technology usage, however, has been masculinized through computer-games and images in the media (Ware & Stuck, 1985). Computers are seen to be ÔboysÕ toys and males indicate that they play computer-games more frequently than females (Alington et al., 1992; Goldstein, 1994; Peters, Chisholm, & Laeng, 1995). Females, on the other hand, seem to have higher levels of computer anxiety (Brosnan & Davidson, 1994). In a cross-cultural study (Sorby, Leopold, & Go´rska, 1999),

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however, for American and Polish engineering students no gender differences were found regarding the play with video and computer-games. Several studies revealed that benefits for spatial abilities can be obtained from video or computer-game playing (De Lisi & Cammarano, 1996; Dorval & Pepin, 1986; Forsyth & Lancy, 1987; Law, Pellegrino, & Hunt, 1993; Ogakaki & Frensch, 1994; Subrahmanyam & Greenfield, 1994). In contrast, however, some studies have observed limited effects of video game practice on spatial task performance (Gagnon, 1985; Peters et al., 1995). Ogakaki and Frensch (1994) concluded that the finding of differences on spatial tasks after video-game practice may depend on the types of spatial abilities that are needed and on the match between the abilities involved in the video game and the abilities that are tested. With regard to the relationship between computergame experience and mental-rotation ability this means that mental-rotation can be better improved through some computer-games than through others. This study first examined gender differences in MRT performance and in computer-game experience. It also investigated the relationship between computer-game preference and mental-rotation test performance with regard to gender differences in mental-rotation. 1.1. Hypotheses It was hypothesized, that girls and boys would differ in their computer-game preference and it was expected that males would outperform females in MRT performance. It was predicted that individuals who had more computer-game experience would achieve a higher score on MRT than those with less computer-game experience. Finally, we expected that some computer-games would be more strongly correlated with high to mental-rotation ability than others.

2. Method 2.1. Participants The sample investigated here was a subsample taken from a larger investigation on spatial abilities (Geiser, Lehmann, & Eid, in press). This subsample consisted of N = 861 pupils (505 females) from the German Bundesland Sachsen-Anhalt. Mean age of participants was 14.67 years (SD = 2.35; range: 10–20 years). N = 530 subjects (61.6%) went to high school (German Gymnasium; grade range: 7–13), while the rest were secondary school students (German Sekundarschule; grade range: 5–10). 2.2. Measures Mental-rotation performance was measured by a German language version of the redrawn Vandenberg and Kuse (1978) Mental Rotations Test (MRT) by Peters et al. (1995, 1995). The MRT consists of 24 items which are administered in two sets of 12 items, respectively. Each item consists of five three-dimensional block figures (see Fig. 1). The block figure on the left (target) has to be compared to four similar constructions on the right hand side. In each item, two of the four figures on the right are rotated versions of the target (correct alternatives), whereas the other two


C. Quaiser-Pohl et al. / Personality and Individual Differences 40 (2006) 609–619

Fig. 1. Example of an MRT item.

are distractor figures. The task is to detect the two correct alternatives that can be rotated to congruence with the target figure in each item. Credit for an item is given only if both correct figures are found so that subjects can reach a maximum score of 24. Good reliability values were found for this MRT version (Cronbachs a = .87; Split-Half reliability = .80; N = 1695; see Geiser et al., in press). Computer-game experience was assessed by a self-report questionnaire. In this questionnaire, subjects were asked to rate how often they used to play different types of computer-games. The computer-games were divided into 8 categories: adventure games, action games, sport games, fantasy role-playing games, logic games, skill-training games, simulation games, and drivingsimulator games. In addition, for each category, two examples of typical games belonging to the respective category were presented (e.g., ‘‘Quake’’ and ‘‘Doom’’ were given as examples for action games). The frequency of playing computer-games of each category had to be rated on a 4-point scale (‘‘never’’, ‘‘rarely’’, ‘‘often’’, ‘‘very often’’). In addition, the questionnaire included a single item worded ‘‘I never play computer-games at all’’ which subjects could check or not. The 8-item scale (without the single item) showed satisfying internal consistency in the present research (Cronbachs a = .78). 2.3. Procedure The measures were administered in spring of 2002. Participants were tested in their classrooms during the regular school day either by one of their teachers or by a research assistant from the University of Magdeburg. This was true for all classes except one class of secondary school students (N = 18; 2.1%) who were tested during a visit at the University of Magdeburg. The MRT was always administered first and we allowed 3 minutes to complete each MRT subscale. Between the two subscales there was a break of 2 minutes. Pupils received no reward for their participation except feedback about their test results. From 24 subjects (2.8%), no MRT data was available for the statistical analysis. This was the case either because these participants came too late to school on the day of testing or they were excluded because they obviously had not understood the test instructions. However, all 861 subjects filled out the computer-game questionnaire. 2.4. Statistical analysis In order to identify different types of computer-game players, we analyzed the 8 items of the computer-game questionnaire with latent class analysis (LCA; see, e.g., Clogg, 1995; Eid, Langeheine, & Diener, 2003; Langeheine & Rost, 1988). In the LCA framework, inter-individual

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differences concerning item responses are explained by the existence of several subgroups (latent classes) with distinct response patterns. The number and the properties of these subgroups are not known a priori but determined in the analysis. Information criteria (IC) can be used to determine the adequate number of latent classes. These indices consider how well a model fits the observed data while favouring more parsimonious models (with fewer classes) over models with a large number of classes. In a series of models with an increasing number of classes, the model with the smallest information criterion value is selected. After an appropriate model has been found, each subject can be assigned to the latent class for which his or her assignment probability is maximum. The resulting class membership variable can be used for further statistical analysis. In the present study, we used the computer program WINMIRA 1.37 (Von Davier, 2001) which uses the EM algorithm and Maximum Likelihood estimation to fit LCA models with an increasing number of classes to the data. The models were compared using the Bayes information criterion (BIC). In order to keep the number of estimated parameters within a reasonable range, we collapsed the four response categories of the 8 items into two categories. That is, the categories ‘‘never’’ and ‘‘rarely’’ were collapsed into the category ‘‘0’’ while ‘‘often’’ and ‘‘very often’’ were collapsed into the category ‘‘1’’.

3. Results 3.1. Mental-rotations test Participants reached a mean MRT score of 9.91 (SD = 4.79). Males scored significantly higher than females [Mmales = 11.69, SDmales = 5.00; Mfemales = 8.67, SDfemales = 4.21; t(654.73) = 9.16; p < .001; effect size d = 0.63] but also showed greater performance variance [Levene test: F(1, 835) = 11.12; p = .001]. 3.2. Computer-game experience In the LCA, we selected the solution with 3 latent classes as it showed the lowest BIC value.1 This model seemed to be reasonable given that the mean class assignment probabilities were high (class 1: .93, class 2: .90, class 3: .76), indicating that 3 types of computer-game players can be distinguished reliably. Furthermore, the model was clear an easy to interpret. The latent class profiles of this solution are depicted in Fig. 2. The lines in Fig. 2 show the conditional response probabilities in each of the 3 latent classes. High response probabilities for certain computer games indicate that these games are played more often in the respective class while lower probabilities indicate that these games are played less often. As can be seen in Fig. 2, pupils assigned to latent class 1 (45.5%) have very low response probability values for all types of computer games (all probabilities are below .11 in class 1). That means, that a relatively large group of students rarely or never plays any of the 8 types of computer-games. Therefore, in the following, we denote members of class 1 as ‘‘non-players’’.


The BIC values for the 2, 3 and 4 class solutions are 7160.45, 7103.82 and 7110.53, respectively.

C. Quaiser-Pohl et al. / Personality and Individual Differences 40 (2006) 609–619 0.9 0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.1 0

Class 1 (45.5%) Class 2 (36.8%)

Lo gi c tra in in Si g m D u riv la in tio g n si m ul at or Sk ill

Sp or t pl ay in g ro le

Ac tio n

Class 3 (17.7%)

Fa nt as y

Ad ve nt ur e

Response Probability


Type of Computer Game

Fig. 2. Latent class profiles for the 3-class solution.

Table 1 Cross-tabulation of latent class membership and gender Latent class membership

Females Males

Class 1 (non-players)

Class 2 (action-andsimulation game players)

Class 3 (logic-and-skilltraining game players)

321 (81.9%) 71 (18.1%)

58 (18.3%) 259 (81.7%)

126 (82.9%) 26 (17.1%)

In contrast, participants assigned to the second largest subgroup (class 2, 36.8%) generally report playing computer-games more often than members of class 1 (the response probability values are higher for all items). However, class 2 members prefer playing action, sport and simulation games (probability values above .50 for these items), while they report playing the other types of games less often. Therefore, we named members of class 2 ‘‘action-and-simulation game players’’. Finally, subjects assigned to class 3 (17.7%) show a quite different pattern. This subgroup has a clear preference for logic as well as skill-training games (response probabilities > .70 for these games) while the remaining games are rarely played in this class. We interpreted class 3 as a group of ‘‘logic-and-skill-training game players’’. In the next step, we investigated the relationship between computer-game experience, gender and mental-rotation performance. Therefore, we assigned each individual to the latent class for which her or his assignment probability was maximum.2 The cross-tabulation of class membership and gender (see Table 1) revealed a strong association between computer-game preference and gender [Pearson v2(2) = 336.98; p < .001; Contingency coefficient C = .53]. In particular, girls were overrepresented in the group of non-players (81.9% of all class 1 members were females)


Assignment probabilities for individuals must not be confused with response probabilities within each latent class. While assignment probabilities are computed for each individual in order to assign each subject to his/her most likely class, the response probabilities for a set of items are equal for all subjects belonging to the same latent class.

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Mean MRT Score

13 12 11 Females Males

10 9 8 7 6 Non-players Action-and- Logic-andsimulation skill training

Fig. 3. Mean MRT scores of the different computer-game classes for females and males. Error bars indicate ± 1 standard error of the means.

while they were strongly underrepresented in the class of action-and-simulation game players (only 18.3% females in class 2). In contrast, more females (82.9%) than males were found in the class of logic-and-skill-training game players. However, in sum, 63.6% of all females were assigned to the class of non-players, while only 19.9% of all males were found in this group. In addition, 17.3% of the girls but only 2.5% of the boys in our sample checked the Item ‘‘I never play computer-games at all’’ [Pearson v2(1) = 45.51; p < .001; Phi = .23]. In order to test whether computer-game experience could predict mental rotation performance over and above gender, we performed an analysis of variance (ANOVA). In the ANOVA, latent class membership and sex were entered as independent variables and MRT score as dependent variable. In order to control for age differences, age was entered as a covariate. Altogether, the model explained 13.2% of the MRT variance (corrected R2). In particular, the results yielded a significant main effect for latent class membership [F(2, 830) = 3.74; p = .02]. However, this effect was relatively small (partial g2 = .01). A Bonferroni-adjusted post hoc test revealed that class 1 members (non-players) had slightly lower mean MRT scores than class 2 members (action-andsimulation game players; Mean difference3 = 1.10; SE = 0.45; p = .045). The other pairwise comparisons yielded no significant differences (ps > .13). The main effect of gender remained significant [F(1, 830) = 40.08; p < .001; partial g2 = .05]. Furthermore, age had a significant effect on MRT performance [F(1, 830) = 30.88; p < .001; partial g2 = .04], indicating that on average, older students showed a higher MRT performance. Although the interaction between latent class membership and sex failed to reach significance [F(2, 830) = 2.82; p = .06; partial g2 = .01], it can be seen in Fig. 3 that males who were assigned to either class 2 (action-and-simulation game players) or class 3 (logic-and-skill-training game players) had higher mean MRT scores than males who were assigned to the subgroup of non-players (class 1). This association, however, was not found for females. For females, computer game preference was unrelated to MRT performance (the MRT means of females were almost equal in each latent class). 3

Based on marginal means estimated by SPSS.


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4. Discussion The findings of the present study are interesting for a number of reasons. First, they confirm the results of other studies which showed that boys are more used to playing computer-games than girls (Alington et al., 1992; Goldstein, 1994). So, as far as the frequency of computer-game playing is concerned, computer technology still seems to be a male domain and computers still ‘‘boys toys’’ (e.g., Ware & Stuck, 1985). Moreover, our results show that boys and girls prefer different computer-games. While most of the boys were classified as ‘‘action-and-simulation game players’’, the majority of the girls were ‘‘non-players’’. If girls play computer-games at all, they seem to favour logic games and skill-training games over other computer-games. This is also in line with the gender stereotype according to which males prefer action and adventure films and games while girls do not like this genre. But these results could also have to do with the age group we have studied, which was relatively old (mean age: 14.67). With regard to the fast development in computer technology during the last decade one could assume that the habit of using computers and playing computer-games may have changed rapidly, as well as the gender differences in this domain. Therefore, in future studies it would be interesting to examine whether the gender differences in computer-game experience are the same with younger children. Second, as expected, boys outperformed girls in MRT performance, and being action-andsimulation game player had a small positive effect on MRT performance. So far, the results are consistent with other findings on the relationship between computer-game experience and mental-rotation test performance (e.g., De Lisi & Cammarano, 1996; Ogakaki & Frensch, 1994; Subrahmanyam & Greenfield, 1994). It could be argued that this effect is too small to have any practical consequences. One must keep in mind, however, that the effect size reported is a partial effect size. That is, it is already corrected for the influences of gender and age. Interestingly, in our data the relationship between computer-game experience and MR performance could only be found for boys. For girlsÕ mental-rotation ability, however, it does not seem to matter whether they play computer-games or not. This finding is contrary to the results of several other studies. Usually, experience like increased exposure to spatial activities has proved to be equally beneficial for both, males and females (Baenninger & Newcombe, 1989). In other studies females even gained more from computer experience or computer-game training than males (e.g., Connor et al., 1977; Quaiser-Pohl & Lehmann, 2002). It seems, however, that the frequency of playing computer-games is too low for the whole group of girls to have an effect. Remember that, in our sample, 81.9% of all subjects assigned to the latent class of non-players were female and that 63.6% of all females were found in this group. With regard to the fact that the estimation of computer-game frequency was a relative one—i.e., subjects did not estimate the hours per week they spend playing computer games—we could further assume that if most of the boys play certain kinds of computer-games because of a hedonistic motivation they do this much more often than girls. Therefore, they profit more from this experience than most of the girls and this improves their spatial abilities to some extent. However, with non-experimental data, one must be careful with interpreting the results in terms of cause and effect between computer-game experience and spatial ability indicating that a higher frequency of computer-game usage leads to better spatial abilities. It could also be the other way round, which means that their good spatial ability, i.e., mental-rotation abilities, is the reason why boys like to play special kinds of computer-games. This would be in line with the work of Casey

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and her colleagues (Casey, 1996; Casey et al., 1992; Casey, Nutall, & Pezaris, 1999) who showed that for girls with a special genetic predisposition for extraordinary spatial abilities the probability is higher that they take more mathematics courses and visit special schools which again improves their spatial abilities. Like Casey and her colleagues we interpret our results within a nature–nurture-interactionist framework of gender differences in spatial abilities. Computer-game experience and preference seems to serve as a mediator between gender and mental-rotation test performance. Looking for the third variable behind this relationship, research on spatial abilities indicates that an individual hormonal status may influences both, spatial ability and computer-game experience (e.g., Gouchie & Kimura, 1991; Hampson, 1990). It may be that the hormonal status and history of some individuals predisposes them to both enjoy playing certain computer-games and having well-developed spatial abilities. Other individuals—because of their hormonal status and history—do not like playing computer-games and have less well developed spatial abilities. Finally, what does all this mean for the gender differences in mental rotation? Results again show that biology and experience are intertwined in a manner that is difficult to separate (Halpern & Tan, 2001). Still more research is needed to find out how much nature and nurture contribute to the development of spatial abilities and how both ‘‘work together’’. It seems that individualsÕ admission of playing certain types of computer games is a useful predictor of spatial abilities. Consideration of the relatively low effect sizes lead us to conclude that we may not have asked the right question yet. In future studies instead of comparing groups of computer-games like adventure, action and logic games, it may be better to look at the special characteristics of the different computer-games, even within one of the groups and relate them to the particular properties of the spatial task that is tested (Ogakaki & Frensch, 1994). This approach might help us to further elucidate the complex relationship between computer-game preference, gender and spatial ability and lead to a better understanding of how playing computer-games might contribute to improve spatial ability. References Alington, D. E., Leaf, R. C., & Monaghan, J. R. (1992). Effects of stimulus color, pattern, and practice on sex differences in mental rotations task performance. Journal of Psychology, 126, 539–553. Baenninger, M., & Newcombe, N. (1989). The role of experience in spatial test performance: a meta-analysis. Sex Roles, 20, 327–344. Baenninger, M., & Newcombe, N. (1995). Environmental input to the development of sex-related differences in spatial and mathematical ability. Learning and Individual Differences, 7, 363–379. Baron-Cohen, S. (2003). The essential difference. Men, women and the extreme male brain. Allan Lane: Penguin Books. Bjorklund, D. F., & Brown, R. D. (1998). Physical play and cognitive development: integrating activity, cognition, and education. Child Development, 69, 604–606. Brosnan, M., & Davidson, M. (1994). Computerphobia—is it a particularly female phenomenon? The Psychologist, 7, 73–78. Burnett, S. A., & Lane, D. M. (1980). Effects of academic instruction on spatial visualization. Intelligence, 4, 233–242. Casey, M. B. (1996). Understanding individual differences in spatial ability within females: a nature/nurture interactionist framework. Developmental Review, 16, 241–260. Casey, M. B., Colon, D., & Goris, Y. (1992). Family handedness as a predictor of mental rotation ability among minority girls in a math-science training program. Brain and Cognition, 18, 88–96. Casey, M. B., Nutall, R. L., & Pezaris, E. (1999). Evidence in support of a model that predicts how biological and environmental factors interact to influence spatial skills. Developmental Psychology, 35, 1217–1247.


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