spatial navigation in large-scale virtual environments: gender differences in survey tasks

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Computers in

Computers in Human Behavior 24 (2008) 1643–1667

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Human Behavior

Spatial navigation in large-scale virtualenvironments: Gender differences in survey tasks

Lorys Castelli *, Luca Latini Corazzini, Giuliano Carlo Geminiani

Department of Psychology and Center for Cognitive Science, University of Turin, Via Po 14, 10123 Turin, Italy

Available online 10 August 2007

Abstract

Most of the studies on gender differences in spatial abilities have focused on traditional paper andpencil cognitive tests, while these differences have been less investigated in navigational tasks carriedout in complex virtual environments (VEs). The aim of the present study has been to evaluate genderdifferences in route and survey knowledge by means of specific tasks (route-learning, pointing, land-mark-placing) carried out in two separate VEs. In addition the male and female participants weresubjected to a battery of spatial abilities tests and specific self-report questionnaires. The resultsshowed a significant difference favouring males in the survey tasks, as well as in the spatial abilitiestests; on the contrary, no gender differences were found in the route task. Moreover, a different pat-tern of correlations among the measures were found in the male and female sub-groups.� 2007 Elsevier Ltd. All rights reserved.

Keywords: Gender differences; Spatial navigation; Computer-simulated virtual environments; Route/surveyknowledge

1. Introduction

1.1. Gender differences on spatial navigation: comparing methods

As demonstrated by Sandstrom, Kaufman, and Huettel (1998) most of the studies onspatial ability have not provided for navigational tasks. By navigational tasks, we meantests which imply the real or ‘‘virtual’’ movement of subjects within large-scale

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doi:10.1016/j.chb.2007.06.005

* Corresponding author. Tel.: +39 011 6703065.E-mail address: [email protected] (L. Castelli).

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1644 L. Castelli et al. / Computers in Human Behavior 24 (2008) 1643–1667

environments, geometrically defined and with landmarks. In such environments the sub-jects do not have the possibility to comprehend all the spatial information from a singlepoint of view.

In order to evaluate possible differences over and above ‘‘simple’’ spatial abilities, sev-eral authors have used bi-dimensional maps (Galea & Kimura, 1993; Holding & Holding,1989). In a study conducted by Galea and Kimura, the subjects were asked to take a newroute on a 2D map of a city (Galea & Kimura, 1993). The male participants made fewermistakes in learning the route than the female ones and took less time to do the test. Inaddition, while the females recalled more landmarks than the males, the latter demon-strated more knowledge of the geometric properties of the map.

Despite the fact that the various elements in 2D can easily be controlled and manipu-lated, it is not clear how far the differences noted in finding streets using 2D maps are rep-resentative of the differences found in real navigation. The subjects are only able tocomprehend all the environmental information from a single point of view, thus lackingone of the key characteristics of spatial navigation. In addition, as demonstrated by Mof-fat, Hampsom, and Hatzipantelis (1998) and Sandstrom et al. (1998), the subjects see andunderstand an abstract representation of the environment, rather than moving inside it.Such structural differences leave open the possibility that spatial abilities subtended tolearning through 2D maps and those subtended to real navigation do not completely over-lap. This said, 2D maps have the advantage to make easier the acquisition of surveyknowledge with respect to sequencial navigation, since maps provide a single view on acomplete environment. A study by Golledge, Doughery, and Bell (1995) comparedroute-based to survey-based acquisition of spatial knowledge by means of two differentspatial learning conditions, map-based vs. navigational-based. The results of the studyshowed some evidence of the advantage of map-based with respect to route-based learningin understanding spatial relations within an environment. On the basis of this finding theauthors suggested that exposure to maps positively adds to the understandings we acquirefrom travelling through an environment. In addition, as far as gender differences were con-cerned, the present study did not evidence a difference between male and female across alltasks, but only in certain specific spatial task in which female outperformed male.

In recent years some studies have investigated gender differences in spatial navigationtasks through virtual reality methodology (VR), by constructing virtual environments(VEs).

In the wake of studies conducted on rats, some authors have investigated these differ-ences using computerised versions of uncomplex environments similar to the Morris watermaze (MWM) or the radial arm maze (RAM). In the standard version of these tasks theanimals have to look for a hidden platform in a large pool of water (MWM) or find rewardsin the form of food (RAM) (Roof, 1993; Roof, Zhang, Glasier, & Stein, 1993; Williams &Meck, 1991). What consistently emerges from such studies is an advantage in favour ofmale rats, who demonstrate, for example, greater speed in acquiring knowledge of newenvironments. Male rats appear to rely more on the geometric information present in theenvironment, while information regarding landmarks also seems to be of particular impor-tance to female rats (Williams, Barnett, & Meck, 1990; Williams & Meck, 1991).

Also in studies on man, carried out using methodology similar to MWM, we again findan advantage in favour of males (Astur, Ortiz, & Sutherland, 1998; Sandstrom et al.,1998). Sandstrom and his team tested 48 subjects, 24 male and 24 female, in a MWM-typeVE (Sandstrom et al., 1998). In the training phase the subjects were asked to find a hidden

L. Castelli et al. / Computers in Human Behavior 24 (2008) 1643–1667 1645

target, starting each time from different starting points. The labyrinth used provided bothgeometric information (trapezoidal room) and landmark information (four different land-marks placed in the labyrinth). The testing phase was sub-divided into four sub-phases. Inthe ‘‘stable landmark environment’’, in which the geometric information was varied,meaning the shape of the room, while keeping the position of the landmarks unchanged,the performance of the females substantially overlapped the males’. On the contrary, in thetwo conditions in which information from the landmarks could not be used to find the tar-get (an environment without landmarks and an environment with the landmarks posi-tioned at random compared to the training phase) the performance of the males turnedout to be better than the females’. The males tend to use both geometric and landmarkinformation, while the females selectively use landmark information to find their way innew environments. Consequently varying the position of landmarks in an environmenthas more effects on the performance of females than on males.

Similarly, Astur and his team used a computerised version of the MWT to measurethese types of differences in navigational abilities (Astur et al., 1998). The male and femaleparticipants were instructed to navigate towards a hidden platform. The males carried outthe task better, taking less time to find the hidden platform. They also spent more timeswimming in the quadrant of the swimming-pool where the platform was placed. Despitethe fact that the male participants declared having had more experience of video gamesthan the female, these differences did not statistically account for the different perfor-mances between the two sexes which emerged from the MWM.

Such studies reveal how virtual environments like the MWM represent a useful instru-ment in the study of navigational abilities. However, such VEs do not appear to besufficiently complex. Environments such as the MWM may appear not to be very eco-logical compared to more complex virtual environments and therefore more similar to realones.

A study which has analyzed these types of differences in a more complex virtual envi-ronment was conducted by Moffat et al. (1998). The navigational environment consisted ofa labyrinth with perpendicular intersections and without landmarks. The participants wereasked to find a way out in two different labyrinths having a similar level of difficulty. Fivedifferent trials were carried out in each of the two experimental labyrinths. The timeneeded to complete each trial, the route taken and the number of mistakes made wererecorded. The results showed how the performance of the males was globally more thor-ough and quicker than the females: the males took significantly less time and made fewermistakes in completing the different trials. The authors also excluded the possibility thatthe major experience of video games reported by the males in the self-report questionnairesmight account for the differences found in the navigational trials. For both sets of mea-surements made during the navigational trials, the difference found remained substantiallyunchanged when the experience of video games was imposed as a covariant. As expected,the males scored significantly higher in the spatial cognitive tests. There were also signif-icant correlations between the scores obtained in the cognitive tests and the trials carriedout in the labyrinth, thereby confirming the results of other studies (Darken & Silbert,1996; Waller, 2000). Another recent study investigated spatial knowledge, in a batteryof tasks including wayfinding, estimated of direction and distance and a map placementtask, by means of a complex VE (Tlauka, Brolese, Pomeroy, & Hobbs, 2005); the resultsshowed significant differences favoring males in the majority of the tasks carried out in thevirtual shopping centre.


To sum up, the desktop VEs may be considered valid and effective instruments in thestudy of spatial navigation abilities since they allow a systematic modification of the envi-ronmental features and a systematic recording of behaviour (Peruch, Vercher, & Gauthier,1995; Ruddle, Payne, & Jones, 1997; Tlauka & Wilson, 1994; Waller, 2000).

1.2. Factors involved in gender differences in spatial navigation

A recent work by Saucier and Green tried to establish whether the differences frequentlyobserved between males and females in navigational tasks were somehow linked to the useof different strategies of the two sexes or to different basic abilities (Saucier & Green,2002). Starting from published data (Dabbs, Chang, Strong, & Milun, 1998; Lawton,1994), of a greater focussing on the geometric properties of the environment by the menagainst a greater reliability on landmarks inside the environment by the women, theauthors controlled the experimental conditions by varying the navigational instructionsgiven to the subjects. One half of the experimental sample was asked to take certain routes,towards unknown destinations, following landmark-based instructions, while the otherhalf were given Euclidean-based instructions (north–south–east–west) to reach the samedestinations. The results indicated that the females who followed the Euclidean-basedinstructions made significantly more mistakes than both the females who followed thelandmark-based instructions, and the males who followed the landmark and the Euclid-ean-based instructions. The same result pattern emerged after analyzing the time takento complete the routes, with the females who followed the Euclidean-based instructionsbeing significantly slower than the other three subject groups.

The same experiment was subsequently repeated by the authors using a 2D matrix asthe ‘‘navigational environment’’, that is to say, a new environment unfamiliar to the par-ticipants, in place of the real environment of the previous experiment. This was done tokeep the familiarity with the environment variable under greater control. The results over-lap with those in the first experiment: the males appear to do better when they use Euclid-ean information, while the females turn out to be more suited to landmark-basedinstructions. Such differences have been interpreted by the authors as confirmation thatthese observed differences reflect dimorphic ability in using these two types of spatialinformation.

A further interesting observation emerging from the Saucier study (Saucier & Green,2002) is the significant correlation between a mental rotation test and the number of mis-takes made by the subjects who had followed the Euclidean instructions. The correlationdoes not appear to be significant for the subjects who had navigated with landmark-basedinstructions; this correlation accounts for more than 50% of the variance of the Euclidean-based trial. It may be hypothesised that most of the mistakes made by the females in the‘‘Euclidean’’ trial partly derive from their reduced ability to maintain bearings with respectto the four cardinal points, attributable to their reduced ability in the mental rotation test.

A further factor that seems to play some role in navigational tasks is ‘‘spatial anxiety’’(Coluccia & Louse, 2004). Lawton developed the ‘‘Spatial Anxiety Scale’’ (SAS) in orderto measure the levels of anxiety that subjects experience in situations that require spatialnavigation (Lawton, 1994). As Schmitz has shown, emotional factors must be consideredas one of the mediators in the learning and development of navigational competences(Schmitz, 1997). To date, few studies have analyzed the potential effect of such a phenom-enon on spatial learning in new environments. In the study of Saucier et al. there emerged


a greater level of anxiety in the females than in the males (Saucier & Green, 2002). Thelevel of anxiety found in girls was significantly higher than in boys in the study carriedout on young people by Schmitz (1997). She also demonstrated the presence of significantcorrelations between anxiety levels and some navigational measurements, such as the timeand number of mistakes in the first experimental trial. Correlations between spatial anx-iety, greater in females, and performance in spatial/navigational tasks have been demon-strated by other studies (Bryant, 1982; Lawton, 1994; Lawton, 1996).

Lawton showed that the males appear more inclined to navigate in environments byrelying on absolute geographic co-ordinates (orientation strategy), while environmentalfeatures, landmarks, especially those situated near decisional points, assume particular rel-evance for the females (route strategy) (Lawton, 1994). In the same study there was a supe-rior performance by the males in the mental rotation test and in a test on spatialperception, while the females obtained significantly higher scores in the SAS (Lawton,1994). Another interesting observation is the significant correlation between spatial anxi-ety and the orientation strategy subscale, while there was no relationship with the routestrategy subscale.

A study conducted by Waller (2000) tried to measure, using multivariant analysis, therelationship between the various factors involved in spatial navigation in virtual realityenvironments: the classic paper and pencil spatial tests, spatial representations acquiredin real environments, the gender, experience and the attitude towards using the computer,competence in the use of interfaces involved in VE experiments and the ability to acquireand transfer knowledge from a VE to a real one. In the model tested by the author spatialabilities in cognitive tests and ability in using interfaces turned out to be the most powerfulpredictors of the spatial performances in VE. According to the author, the gender, eventhough representing a significant predictor of the ability to acquire knowledge from aVE, would not become one primarily, but through its association with other factors, suchas the visual–spatial abilities and ability in the use of interfaces.

The results of these studies demonstrate that spatial navigation is a complex abilityinvolving different heterogeneous factors.

1.3. Spatial navigation theories

Different classifications of the various components and stages involved in the acquisi-tion of spatial knowledge have followed one another through the years.

As Schmitz demonstrated (Schmitz, 1997), the first theories in the field of spatial knowl-edge followed a sequence of stages, acquired during development mostly in a serial way(Hart & Moore, 1973; Piaget & Inhelder, 1967): the egocentric stage, the allocentric stage,and the geocentric stage. In the first stage spatial knowledge is strictly bound up in self,while in the allocentric stage we begin to acquire spatial knowledge independently of self,on the basis of the spatial properties of the environment. In the final stage, geocentric, spa-tial knowledge no longer linked to external reference points is formed, but with abstractand absolute co-ordinates, like the Euclidean properties.

Starting with such a classification, literature refers to two types of strategy/knowledgewhich individuals rely on in the exploration/learning of environments: route knowledgeand survey knowledge (Maguire, Frith, Burgess, Donnett, & O’Keefe, 1998; O’Keefe &Nadel, 1978; Russell & Ward, 1982; Siegel & White, 1975). According to some authors,starting with the theorisations of Siegel and White (1975), a further preliminary stage of


knowledge is represented by landmark knowledge, in other words, a stage in which thelandmarks present in an environment are simply noted and confined to memory.

In route knowledge the prospective and viewpoint adopted by the subject are centredon self and factors such as sequentialising, the variation of body position compared tothe environment and visual information directly accessible to the subject (street intersec-tions and identity of landmarks) will all acquire importance. Instead, survey knowledgeimplies the formation of a map of the environment by the observer; a ‘‘bird’s eye view’’where all the environmental information is potentially available. Route knowledge there-fore involves a sequence of instructions about how to get from one point to the next,whereas survey knowledge implies the construction of a cognitive map of the environment,a map which ‘‘integrates’’ the different routes by means of the relationships between thedifferent locations (Lawton, 1994). In addition, despite the fact that both types of knowl-edge allow adequate navigation within the environments, route knowledge, being morerigid and sequential, can more easily lead to mistakes and disorientation whenever anyof the segments of the navigational sequence are changed (Lawton, 1994). Survey knowl-edge is considered, instead, to be more elastic and flexible, allowing for diversion from pre-established routes and greater ability in adapting to obstacles and changes to the environ-ment (O’Keefe & Nadel, 1978).

In the light of these theoretical differences, much experimental evidence can be traced toa difference in the use of these two types of knowledge: the females appear to prefer a routestrategy, while the males to rely more on survey strategy. Several studies have shown howboth environmental and behavioural factors may favour the formation of one or the othertype of knowledge/representation, and have an influence on spatial navigation ability(Coluccia & Louse, 2004; Jacobs, Laurance, & Thomas, 1997; Jacobs, Thomas, Laurance,& Nadel, 1998; Maguire, Burgess, & O’Keefe, 1999; Steck & Mallot, 2000).

One of the fundamental factors in distinguishing between the two types of strategies isthe familiarity of the subject with the navigational environment. In fact, a greater knowl-edge of the environment would seem to favour the formation of survey representations(Aginsky, Harris, Rensink, & Beusmans, 1997). In reality, as Aginsky has pointed out,not all the studies agree on this point (Aginsky et al., 1997; Montello, 1998). In the modelproposed by Montello, there is not a qualitative transition sequence between differentstages but a quantitative increase in the accuracy and completeness of spatial knowledge:a quantitative rather than a qualitative shift. In this framework there is no stage at whichpure landmark or route knowledge exists and survey knowledge begin to be acquired onfirst exposure to a novel environment (Montello, 1998). Also in the study under discussionthe author suggests that the spatial navigational tasks can be solved by using a surveystrategy right from the start, without necessarily having to go through the landmarkand route stages, according to the sequence suggested by Siegel and White (1975) (land-mark, route, survey).

The familiarity variable appears to be a problem whenever the experiments are con-ducted in real environments, already familiar to the subjects, since it is not possible to con-trol the various degrees of familiarity of the subjects.

Another important aspect is the presence of local and global cues (landmarks) whichwould seem to favour the formation respectively of spatial route and survey knowledge/representations (Aginsky et al., 1997; Gale, Golledge, Pellegrino, & Doherty, 1990;O’Keefe & Nadel, 1978; Steck & Mallot, 2000). Global landmarks, being potentially vis-ible from any point within the navigational environment and so from a great distance,


become absolute points of reference, favouring orientation strategies in survey terms. Onthe contrary, local landmarks, only visible from certain points and at reduced distances,often assume the function of relative and sequential reference points, leading to inferencessuch as ‘‘ when I see the shop, I have to turn right’’. As O’Keefe and Nadel have suggested(O’Keefe & Nadel, 1978), global landmarks provide world-centred directions which deter-mine a global reference setting that does not change when the subject moves short dis-tances. The authors themselves, instead, define navigation guided by local landmarks asnavigation relying on intermediate stage sequencing outlined by the same local landmarks.For these reasons they are closely linked to route navigation (Steck & Mallot, 2000). Suchassumptions should not however be taken strictly, since some objects which function asglobal landmarks in some of the navigation phases might subsequently be used as locallandmarks (Steck & Mallot, 2000). Individual differences in the use of the different strat-egies, like other features of navigational environments, interact with each other in deter-mining the use made of the different types of landmark.

Despite the growing interest in the study of navigational skills, up to now few studieshave examined the differences between males and females in relation to the distinctionbetween route and survey representations with the possibility of experimental controloffered by VR. Furthermore, few studies have tried to make a thorough study of the rela-tionship between navigational and spatial abilities measured by the classic paper and pen-cil spatial tests.

1.4. Aim of the study

The aim of the study has been to evaluate gender differences in route and survey nav-igational tasks carried out in complex VEs, and their relationship with the cognitive testson basic spatial abilities and specific self-report scale. To examine route knowledge weused a route-learning task, where the subjects were asked to go back the same way theyhad come, after just one exploration, in a VE without global landmarks. A previous studyhad used a similar test of route-reversing as an indicator of route knowledge (Pick, 1993).The acquisition of survey knowledge was measured by using a pointing task and a land-mark-placing task on a 2D map of the VE; both tests are considered reliable indicators ofsurvey knowledge (Waller, 2000). Two important factors favouring spatial survey knowl-edge were examined: familiarity and global landmarks; a prolonged phase of familiarisa-tion with the VE was in fact envisaged, and this was also characterised by the presence ofglobal landmarks. We hypothesised that the males would perform better than the femalesin the survey tasks.

2. Methods

2.1. Subjects

The experimental sample consisted of 40 right-handed subjects, 20 male and 20 female,who are students at Turin University. The average age (SD) was 24.5 (2.2), range 20–28,for the male sub-group, and 24.5 (2.7), range 20–30, for the female sub-group. The twosub-groups were homogeneous in terms of age and education. None of the subjects testedhad current or past neurological or psychiatric problems. All the participants had anacuteness of vision within the norm or suitably corrected by the use of lenses.


2.2. Materials and procedures

The experimental protocol envisaged three distinct phases, listed as follows:

2.3. Spatial navigation tasks in virtual environments

2.3.1. Apparatus

The three-dimensional virtual environments (labyrinths) were created by using a CAD3D architectural simulation programme. The labyrinths were displayed on a 21-in.1152 · 864 pixel high-resolution screen. The technical features of the computer used were:Intel Pentium 4, CPU 1.50 GHz, RAM 256 Mb, video card ATI Radeon 7000. The sub-jects were placed at a distance of about 50 cm. from the monitor screen. Movements insidethe environment were made using a mouse which enabled the subjects to move on threeaxes: vertical (forward/backward), horizontal (right/left) and diagonal (forward right/leftand backward right/left). Simple rotational movement (turning on oneself) without anytranslation on the three axes was also possible. Even though it is technically possible tomove backwards (backwards, backwards/right, backwards/left), during the preliminarytraining phase the subjects were told not to use this option in the experimental trials.The navigational speed was kept constant during the experimental trials. Since the fieldof view in a desktop VE eliminates most peripheral vision, continuous lines were presenton the floor in order to facilitate the view of the different alternative routes. Two visualsamples of the two VEs used are illustrated in Figs. 1 and 3; the respective maps of thetwo labyrinths are illustrated in Figs. 2 and 4.

2.3.2. Preliminary training phase

Before starting the experimentation in VEs, each subject underwent a 30-min famil-iarisation session in a virtual labyrinth similar to those used in the experimental phase.

Fig. 1. Visual sample of the labyrinth used for the Route task.

Fig. 2. Map of the labyrinth used for the Route task. The line indicates the route participants had to follow. Theseven local landmarks are also indicated.


The aim of this practice session was to minimise the incidence of individual differencesin the ability to use the experimental apparatus. Two criterions were used to consider asubject sufficiently adequate. First, the subjective feeling of being able to move in thelabyrinth without difficulties. Second, after the participants had familiarised with thelabyrinth, they were asked to follow a route with five turns and the time was recorded.Five subjects (four female/one male) were considered outliers since they carried out thistask in a longer time than the average time of the group and they were excluded fromthe study.


2.3.3. Route knowledge: route-learning task

2.3.4. Labyrinth

The navigation environment used for the present task consists of a labyrinth, with per-pendicular turns, containing seven local landmarks, in other words, reference points onlyvisible from certain positions inside the environment (see Figs. 1 and 2). The landmarksused in this VE, as well as the ones used for the survey VE, were natural or ‘‘artificial’’elements that people usually see in every day life.

2.3.5. Learning phase

The subject is invited to follow a route from a point A (start point) to a point B(end point) inside the labyrinth, following a broken line on the floor. The routeincludes six decisional points, or points at which the subject is asked to make a deci-sion about which route to take. Four of these decisional points require the subject tochoose between two alternatives, one point includes three alternatives and one pointfour alternatives. Each subject takes the route once only. The route to be taken is indi-cated by a broken line on the floor. The successful completion of the task involveslearning the route in such a way as to be able to come back by the same route anothertime.

2.3.6. Testing phaseThe subject is placed at the end point and is asked to follow the previously taken

route back until (s)he reaches the start point. The broken line present during the learn-ing phase is now removed. Each time a mistake is made the subject has to go back andstart again from the beginning, until the correct route is taken twice consecutively. Nohelp is given to the subjects. Moreover, each time a participant deviates from the learnedroute in a wrong way he was suddenly stopped, so that (s)he cannot see other paths ofthe environment, thus evitating the use of a survey strategy. The specific instructions forthis task were: ‘‘now you are placed at the end of the route that you have just taken. Thebroken line present during the learning phase is now removed. You have to come backto the start point trying to make the minor number of mistakes that you can. If youmake a mistake, you will be suddenly relocated at the end point and you can restart.’’The number of attempts and the time needed to carry out the task correctly arerecorded.

A feature of this task that should encourage the use of a route strategy is the short, lim-ited phase of learning given to the subject (just one learning trial). In addition, the absenceof global landmarks excludes the possibility of the subjects referring to absolute co-ordi-nates of space, that is, to reference points which encourage orientation in survey terms.The exclusive use of local landmarks precludes the possibility of visualising all the infor-mation available in the environment from a single perspective.

2.3.7. Survey knowledge: pointing and landmark positioning on 2D map

2.3.8. Labyrinth

In this second phase a labyrinth with a different configuration to the one in the previousphase was used in order to avoid a test–retest effect. In this case, as well as local land-marks, there were also global landmarks; in other words, reference points visible from


any point within the environment. In this test four global landmarks and three local land-marks were used (see Figs. 3 and 4).

2.3.9. Learning phase

The learning phase includes two different sub-phases, the first being a passive explora-tion followed by an active exploration phase. During the first phase, which lasts 3 min, thesubjects are invited to passively follow a pre-established route which the examiner takesinside the labyrinth. The aim of this exploration is provide a general panorama of the lab-yrinth; during this journey all the landmarks present in the environment are seen. Theactive exploration phase involves free navigation within the environment for 10 min. Eachsubject is invited to ‘‘carefully explore the environment with the view of subsequentlybeing asked to carry out some spatial tasks’’. The 10 min time was chosen after a pilotexperiment carried out on 20 subjects (10 male/10 female). These subjects declared to suf-ficiently know the labyrinth after an average time of 10 min.

2.3.10. Testing phase

Pointing. The subjects were asked to carry out three different pointing tests: placed at apoint in the labyrinth (start point), they were asked to head towards a target, pointing bymeans of an arrow situated at the centre of the screen. In carrying out this activity theywere not allowed to make any kind of movement, except for circular rotation on itsown axis. In the three individual trials, the start point was located near a global landmark,while the target was represented by local landmarks, not visible from the present position.In each of the three trials both the start point and the target were changed (see Fig. 4). Thespecific instructions for this task were: ‘‘now you are located in a specific point of the lab-yrinth that you have just explored; from here you have to head towards the landmark Xusing the arrow that you see at the centre of the screen; you cannot move but only rotateyourself.’’

Fig. 3. Visual sample of the labyrinth used for the Survey tasks.

Fig. 4. Map of the labyrinth used for the Survey tasks. The numbers 1, 2, 3 and 4 indicate the global landmarks,while the numbers 5, 6, and 7 indicate the local landmarks.


At this point the angular error was recorded, that is to say, the variation between theideal line linking the start point to the target and the direction estimated by the subject.The final score of the present trial was calculated by taking the average of the three differ-ent angular errors.

Landmark positioning on 2D maps. Finally the subjects were given a 2D map of the lab-yrinth (14 cm · 11.5 cm) showing all the geometric information of the environment (laby-rinth configuration) except for the landmarks. The task assigned to the subjects was to‘‘place card models of the environment landmarks on the map, as near as possible to theirreal position’’. The calculation of the positioning error was made by measuring the dis-tance between the real position of the landmark and the position estimated by the subject.The total score in the test was calculated by taking the average of the seven measurementsthus obtained, relative to each of the landmarks present in the VE.


We assumed that the presence of global landmarks would encourage the formation ofsurvey representations. Unlike the previous labyrinth, the subjects had salient visible infor-mation available from any position of the labyrinth (global landmarks), making orienta-tion easier in terms of absolute co-ordinates. An additional element that should havefacilitated the formation of survey knowledge was the greater familiarisation of the sub-jects with the environment, compared to the single learning trial of the route test.

2.4. Spatial ability assessment

The subjects underwent three cognitive tests on spatial abilities, given in the followingorder: the Corsi block-tapping test (the Corsi cubes test) (Spinnler & Tognoli, 1987), theBenton judgement of line orientation test, form H (JLO) (Benton, Varney, & Hamsher,1978) and a redesigned version by Peters (Peters, Laeng, Latham, Jackson, & Zaiyouna,1995) of the Vanderberg and Kuse mental rotation test, version A (MRotT) (Vanderberg& Kuse, 1978). The MrotT shapes were originally provided by Shepard and Metzler(1971). These tests were chosen because previous studies had shown differences in favourof the males in the performance (Halpern, 1992; Lawton, 1994; Orsini et al., 1986; Rah-man & Wilson, 2003). As Saucier and Green have shown, the verification of a differencebetween males and females in the MrotT allows us to consider the sample as representative(Saucier & Green, 2002).

Corsi block-tapping test. The aim of the test is to provide a measure of short-term spa-tial memory (Mbt). The test is composed by a wood apparatus with nine cubes fixed on arectangular base. Subjects were asked to reproduce a specific and increasing sequence ofcubes in the same order of the examiner.

Benton judgement of line orientation test. This test measures the visuo-perceptive abilityto correctly estimate line orientation (direction and position) compared to a referencemodel. All the 30 items includes 11 lines, numbered from 1 to 11, positioned on a rayson a white background, at a distance of 18� each other. Moreover, each item includestwo different partial lines, that corresponds to two of the lines on the rays. Participantswere asked to detect to which of the eleven lines corresponds the two partial lines.

Mental rotations test. This test measures the ability of the subjects to mentally manip-ulate designs of three-dimensional geometrical shapes, through the recognition of objectsrotated compared to the vertical axis.

2.5. Self-report questionnaires

Each subject filled in four questionnaires concerning different aspects connected to spa-tial navigation: the experience playing computer games (EPCG) designed by Moffat et al.(1998), the Santa Barbara sense of direction scale (SBSOD) designed by Hegarty, Richard-son, Montello, Lovelace, and Subbiah (2002), the way-finding strategy scale (WFS) andthe spatial anxiety scale (SAS) worked out by Lawton (1994).

Experience playing computer games. The questionnaire is made up of two items, oneabout the daily frequency of using computer/video games, the other about the frequencyof using video games which specifically involve navigation in 3D environments. The sub-jects were invited to evaluate their experience in these areas by indicating a value from 1 to7 on a Likert scale. The total score is calculated by taking an average of the two values; ahigh score represents greater experience.


Santa Barbara sense of direction scale. The questionnaire consists of 15 items on a 1–7Likert scale (1, strongly in agreement; 7, strongly in disagreement), containing statementsabout spatial and navigational abilities, navigational aptitudes and experience. Once thescores on the items containing positive statements had been inverted, the total scorewas calculated by totalling the individual scores. A high score corresponds to a greatersense of self-perceived direction.

Way-finding strategy scale. The scale is composed of 14 items containing statementsabout the different strategies used for finding the way when driving. Of the 14 items, ninerefer to survey strategies, while the remaining five refer to route strategies. The subjectswere invited to quantify on a 1–5 Likert scale (1, I never do this; 5, I always do this)the use of each of the strategies indicated, by referring to past situations in which theyfound themselves driving in a relatively familiar city. By adding together the individualscores, two final scores were obtained: one referring to route strategy and the other to ori-entation strategy (survey); in both cases a high score indicated a greater tendency to usethe strategy in question.

Spatial anxiety scale. The SAS consists of eight items containing statements about sit-uations which can cause anxiety, such as finding the way in a new city or getting lost whilegoing along a certain street. The subject has to quantify the anxiety level caused by each ofthe situations described on a 1–5 Likert scale (1, not at all; 5, a lot). The total score is cal-culated by adding together the different answers; a high score indicates that the subject hasa greater spatial anxiety level.

2.5.1. Statistical analysis

The data was analysed by means of the SPSS 9 statistics programme (statistical packagefor the social sciences). In order to compare the male and female sub-groups, we used thet-test for independent samples. The correlations between the variables were analysed bymeans of Pearson’s r correlation coefficient. Finally, univariate ANOVAs were carriedout by examining the variables as covariates. A value of p < 0.05 was considered to be sta-tistically significant.

3. Results

3.1. Spatial navigation tasks in VEs

In the route learning tests, no significant differences were found between the males andthe females in the number of attempts and in the time needed to take the same route back(Table 1). In addition there was no difference in the number of subjects who were able tocomplete this task in a single trial (13/20 male vs. 10/20 female) (chi square: 0.91; ns).

On the contrary, in the tests designed to investigate the acquisition of survey knowledgesignificant differences emerged in favour of the male sub-group (Table 1). The angularerror in the pointing tests appears to be much higher in the female sub-group(p < 0.05), as does the error in the positioning of landmarks in the 2D maps of the VE(p < 0.01). No differences were found between the error in the positioning of the localand global landmarks separately, both for the male (local error: 3.2 (3.8) vs. global error:2.1 (2.6); t(19) = 1.6, ns), and for the female (local error: 6.3 (4.4) vs. global error: 4.9 (3.9);t(19) = 1.4, ns).

Table 1Spatial navigation tasks in virtual environments: performances of male and female participants

Male Female t-test t (df) p

Route knowledge

Route learning (trials) 1.6 (1.0) 2.0 (1.4) 1.2 (38) nsRoute learning (time) 159.5 (83.1) 185.1 (77.9) 1.0 (38) ns

Survey knowledge

Pointing 15.8 (11.2) 24.6 (13.5) 2.2 (38) 0.032Landmark positioning 26 (28) 55 (35) 2.9 (38) 0.007

Mean and (SD) are shown.


In order to evaluate whether the above-stated differences between the males and thefemales in the pointing and landmark positioning tests (survey knowledge) were secondaryto the males’ greater experience with computer/video games and with their tendency toexperience less spatial anxiety, we conducted further analysis (ANOVAs) taking as covar-iates the scores obtained in the experience playing computer games and the spatial anxietyscale. A significant difference remains between males and females in the pointing test (F(1,36) = 4.846; p = 0.034) and neither of the two covariates reached the level of significance(EPCG: F(1, 36) = 0.02; p = 0.97; SAS: F(1, 36) = 1.588; p = 0.22). In a like manner, thedifference in the landmark positioning test on the map was significant (F(1, 36) = 5.813;p = 0.021), and neither of the two covariates were significant (EPCG: F(1, 36) = 0.795;p = 0.38; SAS: F(1, 36) = 2.199; p = 0.147).

Also, the results on the route task remains not significantly different between male andfemale when the SAS and EPCG scores were added as covariates in the ANOVA analysis:number of trials (F(1, 36) = 0.167; p = 0.685), time (F(1, 36) = 0.131; p = 0.720). Also forthese route measures, neither of the two covariates was significant: EPCG: F(1, 36) =0.703; p = 0.41; SAS: F(1, 36) = 0.383; p = 0.54, for the number of trials, EPCG: F(1,36) = 1.29; p = 0.26; SAS: F(1, 36 = 0.021; p = 0.88) for the time.

3.2. Post-hoc statistical power analysis

As far as the route task is concerned, the effect size is 0.328 and 0.318 (t-test d) for thenumber of trials and the time measures, respectively. As for the survey task, the effect sizeis 0.710 and 0.915 (t-test d) for the pointing and the landmark positioning measures,respectively.

The post-hoc statistical power analysis for our t-test with two groups of 20 subjectsshowed that for an hypothetical effect size of 0.2 and 0.5 (low and moderate effect size)the statistical power is not very high, 0.0946 and 0.3379, respectively, whereas for an hypo-thetical effect size of 0.8 (strong effect size) the statistical power of our t-test is quite high,0.6934.

3.3. Spatial abilities

Overall, the performance of the male subjects was significantly better than the femalesin all the tests deigned to investigate spatial abilities (see Table 2).

Table 2Spatial ability assessment: performances of male and female participants

Range min–max Male Female t-test t (df) p

Corsi 0–9 6.3 (0.9) 5.6 (1.0) 2.3 (38) 0.027JLO 0–30 27.2 (2.2) 25.2 (3.5) 2.1 (38) 0.043MRotT 0–24 15.5 (4.5) 10.1 (4.0) 4.0 (38) 0.0003

Corsi, Corsi block-tapping-test; JLO, Benton judgment of line orientation test; MRotT, Mental rotations test.Mean and (SD) are shown.


The males got higher scores in the Corsi cubes test (p < 0.05) and demonstrated greaterability in estimating line orientation compared to the reference model (JLO) (p < 0.05). Inaddition, there emerged a highly significant difference in favour of the males in the abilityto mentally rotate three-dimensional geometric forms, as measured by the MRotT(p < 0.0005).

3.4. Self-report questionnaires

The male subjects stated that they had spent a significantly greater amount of time play-ing computer/video games (EPCG) than the females, especially those games involving nav-igation in 3D environments (p < 0.005).

No statistically significant differences emerged concerning the SBSDS: the males andfemales in the sample declared having similar ability regarding ‘‘sense of direction’’. Nei-ther did significant differences emerge between the two groups concerning the WFS, nei-ther in the sub-scale regarding the use of route strategy, nor in the one concerningorientation strategy. The female sub-group declared having experienced a higher level ofanxiety in situations, potentially anxiety-provoking, involving spatial/navigational ability(SAS). Even though the significance level was not reached (p = 0.054), the scores obtainedby the females in the SAS were higher (greater spatial anxiety) than those of the males. Thedata from the self-report questionnaires is shown in Table 3.

3.5. Correlation between the tests in VEs

In the male sub-group the landmark positioning test on the 2D map correlates posi-tively and significantly both with the pointing test (p = 0.014), this also leading back tosurvey knowledge, and with the route task (p = 0.020).

Table 3Self-report questionnaires: scores of male and female participants

Male Female t-test t(df) p

Experience playing CG 8.2(4.8) 4.8(2.5) 3.4(38) 0.002SB sense of direction scale 55.9(13.0) 54.3(12.9) 0.4(38) nsWFS route 18.3(6.8) 18.9(5.3) 2.8(38) nsWFS orientation 20.9(7.0) 20.3(7.0) 2.7(38) nsSpatial anxiety 17.0(5.6) 21.0(7.1) 2.0(38) 0.054

Experience playing CG, experience playing computer games; SB sense of direction scale, Santa Barbara sense ofdirection scale; WFS, way-finding strategy scale.Mean and (SD) are shown.


With regard to the female sub-group, we found a positive correlation between the num-ber of attempts needed to successfully complete the route task and the error in positioningthe landmarks on the 2D map (p = 0.021).

In both sub-groups no significant correlation between the pointing test (angular error)and the route learning test (number of attempts) emerged. Finally, considering the entiresample a significant positive correlation was found between the landmark positioning teston the one hand, and the route learning test (p = 0.0004) and pointing test on the other(p = 0.017) (see Table 4).

3.6. Correlation between the tests in VEs and cognitive tests on spatial abilities

In the male sub-group the number of attempts needed to complete the route learningtest correlated negatively and significantly with the scores obtained in the Corsi cubes test(p = 0.012), indicating that with an increase in the score obtained by the males in the Corsi

Table 4Pearson correlations among the tasks carried out in the VEs

Route-learning Pointing Landmark pos.

M Route-learning (trials) – 0.17 0.51a

– Pointing 0.17 – 0.54a

F Landmark positioning 0.51a 0.10 –

Total Route-learning – – –Pointing 0.22 – –Landmark positioning 0.54b 0.38a –

Above the diagonal: male; below the diagonal: female.a p < 0.03.b p < 0.0005.

Table 5Pearson correlations among the tasks carried out in the VEs and the spatial ability tests

Corsi JLO MRotT

Male

Route-learning (trials) �0.55* �0.33 �0.44a

Pointing 0.12 0.16 �0.10Landmark positioning �0.18 �0.28 �0.44a

Female

Route-learning �0.38 �0.21 �0.20Pointing 0.08 �0.27 �0.10Landmark positioning 0.05 �0.31 �0.28

Total

Route-learning �0.48** �0.29 �0.35*

Pointing �0.03 �0.22 �0.26Landmark positioning �0.19 �0.39* �0.50**

Corsi, Corsi block-tapping-test; JLO, Benton judgement of line orientation test; MRotT, Mental rotations test.a 05 < p < 0.055.* p < 0.03.

** p < 0.002.


cubes test the number of attempts needed to successfully complete the route-learning testdecreases. We also have a tendency towards a significant correlation, also negative,between the mental rotations test on the one hand and two tests conducted in the labyrinthon the other, that is, the route-learning test (p = 0.053) and the landmark positioning test(p = 0.054).

With regard to the female sub-group we did not find any significant correlation betweenthe tests in the VEs and the spatial abilities test.

Taking the entire sample, we found a significant negative correlation between the route-learning test with the Corsi span (p = 0.002) and with the mental rotations test (p = 0.026):as the score obtained in these two spatial tests increases, the performance in the route testimproves, reducing the number of attempts needed to complete it. Finally, there emerges asignificant negative correlation between the landmark positioning test and the JLO(p = 0.012), and between the former and the MrotT (p = 0.001). Also in this case fewererrors in the landmark positioning test corresponds to a better performance in the cogni-tive tests in question (see Table 5).

4. Discussion

To date, most of the studies on navigational abilities carried out in VE have used verysimple setting and have analysed single component of the navigational skills, without pro-viding extensive assessments of spatial abilities.

The present study has examined the differences in acquiring route and survey knowl-edge in a large-scale complex virtual environment containing landmarks. Environmen-tal/experimental conditions were chosen which would encourage and maximise theability to form both a route and a survey representation of the environment, and thenmeasure their respective behavioural indicators in relation to their differences. In addition,going further with previous studies, the participants were extensively evaluated throughpaper and pencil tests and self-report scales. The correlation analysis between these differ-ent measures allowed to better clarify the relation between ‘‘basic’’ spatial abilities andnavigational abilities.

The most important data emerging from the study is a significant difference in favour ofthe males in the ability to acquire survey knowledge in VEs. The male participants weremore accurate than the females in the ability of pointing towards non-visible objects(pointing). In addition, the males made fewer mistakes than the females when asked toposition card reproductions of the labyrinth landmarks on a 2D map of the VE.

On the contrary, no significant differences between the males and females in the route-learning test, measured by the number of attempts and the time needed to successfully takethe same route back, were found. Nevertheless, it has to be noted that the route-learningtest was completed with a small number of mistakes by both sub-groups, probably as aconsequence of the instructions given to the participants. So, if we might have obtaineda small ‘‘ceiling’’ effect for the measure of the ‘‘trials’’, this was not the case for the mea-sure of the ‘‘time’’. This said, given the low effect size and statistical power of the routetask measures, the lack of gender difference on this task should be interpreted withcaution.

Overall, these results are in line with the evidence emerging from studies conducted indesktop VEs which indicate an advantage in favour of the males in the ability to acquirespatial information from large-scale unfamiliar environments (Coluccia & Louse, 2004;


Tlauka et al., 2005; Waller, 2000). In particular, the greater reliance by the males on theEuclidean features of the environment, such as direction and metric distances, otherwisedefined as survey knowledge or orientation strategy, was confirmed (Coluccia & Louse,2004; Lawton, 1994; Schmitz, 1997; Tlauka et al., 2005).

Other studies had specifically highlighted the greater accuracy of the males compared tothe females in the ability to point towards non-visible targets, and in a map placement task(Coluccia & Louse, 2004; Tlauka et al., 2005).

In addition, our results are in line with what Moffat and his team suggested (Moffatet al., 1998): when both sexes are allowed to acquire sufficient experience in a new environ-ment, the male performance exceeds the female one. Our survey tests were conducted afteran extensive phase of familiarisation, both passive and active, while the route test was car-ried out after a single learning trial. It would therefore seem that the males use experience,often a critical factor in the acquisition of survey knowledge, in a more effective way thanthe females to find their way in a new environment.

In addition, it has to be noted that the VE used in the study of Moffat and colleagueswas without landmarks, while we used both local and global landmark. So, our resultsshowed that this difference in favour of male is present also when salient information werepresent in the environment.

To summarise, our study would appear to show a neat advantage of the males in theability to use survey strategies.

One of the fundamental and peculiar aspects of our study was analysing the relation-ships between the various navigational tests, and the relationships between these andthe spatial tests. As expected, the performance by the males in the cognitive spatial testswas significantly better than the by the female participants, confirming the data emergingfrom previous studies (Halpern, 1992; Lawton, 1994; Orsini et al., 1986; Rahman & Wil-son, 2003). As we were expecting, from the correlational analyses between the tests con-ducted in the VEs, we did not find any correlation between the route-learning and thepointing tests. Such data would appear to confirm that the abilities examined by thetwo tasks, route vs. survey, are different.

An unexpected finding was the correlation between the route-learning test and the land-mark positioning test on 2D maps, a correlation which is significant both considering themales and females separately, as well as considering the entire sample at the same time. Wehad, in fact, hypothesised that the landmark positioning test, just like the pointing test,would require different abilities to those needed to carry out the route test. Probablythe ability to position the landmarks on the map, as well as implying adequate surveyknowledge, also requires other components, among which is mental rotation ability. Itis, in fact, a much more complex task than pointing. In addition, the test in question, eventhough examining the knowledge acquired during the VE exploration, is conducted on a2D map, thus adding an additional variability source. Several hypotheses regarding thispoint may be made by analysing the significant correlation which emerged between thelandmark positioning test and the pointing test (entire sample). This correlation remainssignificant only when the males are considered, but not when the results of the femalesare analysed. It would therefore seem that males and females use different strategies/abil-ities in the resolution of this test.

Additional interesting elements are obtained from the analysis of the correlationsbetween the VE tests and the spatial cognitive tests. By analysing the entire samplewe found a significant correlation between the route learning test and the Corsi Cubes


test. On the other hand, it is not surprising that subjects with a greater spatial span haveless difficulty in recalling a particular route in a short time. The relationship emergingbetween the route test and the mental rotations test is also fairly predictable: the subjectswere asked to take the same route backwards and not forwards. The performance in thistype of task is favoured by a greater capacity in manipulating spatial information(acquired in a certain direction) in order to rotate it in a backward representation, ashappens when, in everyday experience, we have to return to a starting point (for exam-ple, home) having reached a particular place (for example, the library). In the study ofSaucier and Green (Saucier & Green, 2002), where a backwards test like ours was notenvisaged, no relationship emerged between the scores of subjects following landmark-based instructions, a task leading back to route knowledge, and the mental rotationstask. This latter test demonstrated instead a significant correlation with the ability touse Euclidean information (survey knowledge). On the basis of this correlation, theauthors suggested that the performance in the two tasks (mental rotations/Euclideaninstructions) might derive from the use of similar spatial abilities. In particular, theauthors hypothesised that while subjects following landmark instructions could reachdifferent destinations by directly following directions, the participants following Euclid-ean instructions had to continually monitor their spatial orientation, an aspect con-nected to mental rotations. On the contrary, in the present study the ability to headtowards non-visible objects does not correlate with any of the spatial cognitive testsused. However, we have a significant correlation between the mental rotations testand the landmark positioning test. Coming back to the Saucier hypothesis (Saucier &Green, 2002), according to which the females make more ‘‘Euclidean mistakes’’ dueto their lesser ability in the mental rotations, we might suppose, on the basis of our data,that such a statement is even truer for tasks of a certain complexity (high level process-ing), like our landmark positioning task, but not with more elementary and basic surveytasks such as pointing (low level processing).

A further study in which significant correlations were shown between spatial cognitivetests, including the mental rotations test, and the tests conducted in VEs, is the study ofMoffat and his team (Moffat et al., 1998). The authors discussed the results by hypothes-ising a consistent overlap between the spatial processes involved in the two different typesof test. In this case too the task asked of the subjects, that is to say, finding a way out oftwo labyrinths in different trials, was rather complex and detailed, if compared to ourpointing test. As confirmation of this, also in our study the overlaps between the cognitivetests and the navigational tests are more consistent when we analyse the route learning testand the landmark positioning test, more articulate and complex than the pointing. Themore complex the specific navigational task, the greater will be the overlapping of the spa-tial abilities necessary to successfully complete them.

Regarding the self-evaluation of the subjects through the questionnaires, several inter-esting points emerged. The self-perception of the subjects with regard to their sense ofdirection and their preferences in navigational strategies, measured by self-report scales(SBSOD, WFS), unexpectedly found that no substantial differences existed between thetwo groups. One possible explanation, to some degree shared, might be found in the infor-mation provided in a recent study by Waller, Beall, and Loomis (2004). According to Wal-ler, individual differences in the measurements of spatial and environmental knowledge aregenerally very marked. We can reasonably hypothesise that such intersubjective variabilityis also present in the relative self-report scales, probably in a much more marked way. This


is due to the nature of the scales themselves, in which the phenomenon under examinationmay be further filtered and ‘‘obscured’’ by a non spatial gender bias, as the self-awarenessand the social desirability of the subject. We cannot however exclude the possibility thatthe small differences which emerged might have been more evident with a wider experi-mental sample.

The results emerging from the self-report scales which examined more specific and dis-tinct aspects, such as previous experience with video games and spatial anxiety, are clearer.

As argued by Waller (2000), differing ability in the use of experimental apparatus, espe-cially the device necessary for movement, when not adequately checked with a phase oftraining, can represent an important factor of interference. Despite the fact that the maleparticipants had declared having greater experience with video games, the analysis of thecovariants excluded the possibility that the differences observed in the navigational tasksmight in some way be attributable to such a factor. This result is in accordance with thestudy by Moffat et al. (1998), where these differences in route learning tasks remain signif-icant when experience with video games is imposed as a covariant.

Furthermore, we stress that a training phase with the VR apparatus was conductedwhich probably made the participants more homogeneous compared to the video gamesexperience. We would therefore rule out that the advantage that the males have in theVE tests is due exclusively to their having more experience in video games and by differ-ences in the ability to use experimental apparatus.

Although the females in our study admitted to experiencing greater spatial anxiety, inline with what emerged from other studies (Coluccia & Louse, 2004; Saucier & Green,2002; Schmitz, 1997), nevertheless, even in this case, the differences found in the VE tasksare substantial even when the level of spatial anxiety is imposed as a covariant. The studycarried out by Schmitz (1997) had shown how a factor like this could have a major influ-ence especially in the initial experimental trials (environment still unknown to the sub-jects). Also for this aspect we could hypothesise that the adequate training phase doneby the participants in our experiment had contained the potential interfering effect onthe variable targets.

To sum up, an important aspect of this study is represented by the fact that partic-ipants were accurately trained with the use of the VR apparatus before the experimentalsessions.

As far as the similarities/differences between virtual and real environments, variousauthors have demonstrated the effectiveness of VR in large-scale environmental learning.The desktop VEs may be considered valid and effective instruments in the study of spa-tial navigation abilities, both for route knowledge and in the acquistion of survey knowl-edge (Peruch et al., 1995; Ruddle et al., 1997; Tlauka & Wilson, 1994). When comparedto real environments, the VEs appear to be more suitable for certain experimental needs.In real environments a systematic modification of the environment is not always possi-ble, as is a systematic recording of behaviour. In addition, experiments conducted in realenvironments are often carried out in environments familiar to the participants, makingit difficult to measure the degree of familiarity, an important and fundamental aspect ofsurvey knowledge. But, unlike the process of learning spaces in the real world, learningspaces from desktop VEs does not involve vestibular or kinesthetic modalities (Waller,2000).

Regarding the transferability of knowledge acquired in VEs into real environments, arecent study by Hegarty and colleagues found a weak correlation between virtual and real


environments (Hegarty, Montello, Richardson, Ishikawa, & Lovelace, 2006). On the con-trary, Waller’s study demonstrates that the measurements taken in the VE are highly pre-dictable of the performance in the real environment, with a strong correlation emergingbetween the measurements, comparable to each other, taken in the two environments(Waller, 2000). Furthermore, he showed that individual differences observed in the VEoverlap with those found in the real environment (Waller, 2000).

In any case, since the males often possess greater experience in the use of the computerand video games than the females, intersubjective variability in the ability to performmovements through different interfaces and the ability to do them automatically representa potential interfering factor (Waller, 2000). Experiments in VEs must therefore anticipateadequate phases of training in order to homologate the differences between theparticipants.

This said, since we had adequately controlled one of the most important interfering fac-tor for the transferability of knowledge from virtual to real environment (individual differ-ences in using the VR apparatus), we can consider our results sufficiently transferable to areal environment, even if further studies are still needed to definitively clarify this impor-tant issue.

Our results are comparable to the ones obtained in similar experiments carried out inreal environment setting (Montello, Lovelace, Golledge, & Self, 1999). In this study theauthors found evidence supporting a route–survey distinction between the sexes. Specifi-cally our results seem to confirm the assertion by Montello and collegues: ‘‘. . .the route–survey distintion is actually a more one-sided preference for the survey style by males’’.

In conclusion, the present study, as well as confirming the validity of desktop VEs in thestudy of spatial navigational abilities, highlights a significant difference in favour of themales in the capacity to acquire survey knowledge in virtual large-scale unfamiliarenvironments.

4.1. Practical implications

As far as practical implications of our paper are concerned, our findings would appearto be relevant for the design and use of VEs.

Firstly, gender differences have implications for the use of a complex VE as a trainingtool. The gender of recruits for jobs concerning real/virtual navigation may be a factor totake into account when designing training programs using a VE. If the goal of training isto acquire the ability to draw maps, to point to unseen targets and to navigate in an ori-entation-free manner, then extended training time or explicit exposure to maps of the envi-ronment may be needed for female subjects (see Cutmore, Hine, Maberly, Langford, &Hawgood, 2000 for similar consideration concerning individual differences in spatial abil-ities). If the goal of training is simply to learn to cover a route, a simple training based onrepetitive reproduction of the route is much more appropriate.

Secondly, it is difficult to evaluate what constitutes an effective navigational aid, if onedoes not consider the gender of potential users. Some information (such as informationabout bearing or aerial distance; Peruch et al., 1995; Ruddle & Peruch, 2004) could beextremely useful for certain individuals (i.e. male subjects), but at the same time uselessfor others who benefit more from route information. Thus, as suggested by Cutmoreet al. (2000), empirical verification of potential aids is needed to better fit the aid to thepopulation of users.


Acknowledgements

This research was supported by a grant from ‘‘Carlo Molo Foundation’’ – Turin toL.C. and L.L.C. and by a MIUR Grant (cofin 2003–2005) to G.G. The authors thankDr. Mariateresa Molo for her help and support and Mr. Paul Kelly for his help withthe English.

References

Aginsky, V., Harris, C., Rensink, R., & Beusmans, J. (1997). Two strategies for learning a route in a driving

simulator. Journal of Environmental Psychology, 17, 317–331.Astur, R. S., Ortiz, M. L., & Sutherland, R. J. (1998). A characterization of performance by men and women in a

virtual Morris water task: A large and reliable sex difference. Behavioural Brain Research, 93, 185–190.Benton, A. L., Varney, N. R., & Hamsher, K. S. (1978). Visuospatial judgment: a clinical test. Archives of

Neurology, 35, 364–367.Bryant, K. J. (1982). Personality correlates of sense of direction and geographical orientation. Journal of

Personality and Social Psychology, 43, 1318–1324.Coluccia, E., & Louse, G. (2004). Gender differences in spatial orientation: A review. Journal of Environmental

Psychology, 24, 329–340.Cutmore, T. R. H., Hine, T. J., Maberly, K. J., Langford, N. M., & Hawgood, G. (2000). Cognitive and gender

factors influencing navigation in a virtual environment. International Journal of Human–Computer Interaction,

53, 223–249.Dabbs, J. M., Jr., Chang, E. L., Strong, R. A., & Milun, R. (1998). Spatial ability, navigation strategy, and

geographic knowledge among men and women. Evolution and Human Behaviour, 19, 89–98.Darken, R. P., & Silbert, J. L. (1996). Navigating large virtual spaces. International Journal of Human–Computer

Interaction, 8, 49–71.Galea, L. A. M., & Kimura, D. (1993). Sex differences in route learning. Personality and Individual Differences, 14,

53–65.Gale, N., Golledge, R. G., Pellegrino, J. W., & Doherty, S. (1990). The acquisition and integration of route

knowledge in an unfamiliar neighbourhood. Journal of Environmental Psychology, 10, 3–25.Golledge, R. G., Doughery, V., & Bell, S. (1995). Acquiring spatial knowledge: Survey versus route-based

knowledge in unfamiliar environments. Annals of the Associations of American Geographers, 85(1),134–158.

Halpern, D. L. (1992). Sex differences in cognitive abilities (pp. 68–77). Hillsdale, NJ: Erlbaum.Hart, R. A., & Moore, G. T. (1973). The development of spatial cognition. In R. M. Downs & D. Stea (Eds.),

Image and environment (pp. 246–288). Chicago: Aldine publishing company.Hegarty, M., Montello, D. R., Richardson, A. E., Ishikawa, T., & Lovelace, K. (2006). Spatial abilities at

different scales: Individual differences in aptitude-test performance and spatial layout learning. Intelligence,

34(2), 151–176.Hegarty, M., Richardson, A. E., Montello, D. R., Lovelace, K., & Subbiah, I. (2002). Development of a self-

report measure of environmental spatial ability. Intelligence, 30, 425–447.Holding, C. S., & Holding, C. H. (1989). Acquisition of route network knowledge by males and females. The

Journal of General Psychology, 116, 29–41.Jacobs, W. J., Laurance, H. E., & Thomas, K. G. F. (1997). Place learning in virtual space I: Acquisition,

overshadowing, and transfer. Learning and Motivation, 28, 521–541.Jacobs, W. J., Thomas, K. G. F., Laurance, H. E., & Nadel, L. (1998). Place learning in virtual space

II: Topographical relations as one dimension of stimulus control. Learning and Motivation, 29,288–308.

Lawton, C. A. (1994). Gender differences in way-finding strategies: Relationship to spatial ability and spatial

anxiety. Sex Roles, 30, 765–779.Lawton, C. A. (1996). Strategies for indoor wayfinding: The role of orientation. Journal of Environmental

Psychology, 16, 137–145.Maguire, E. A., Burgess, N., & O’Keefe, J. (1999). Human spatial navigation: Cognitive maps, sexual

dimorphism, and neural substrates. Cognitive Neuroscience, 9, 171–177.


Maguire, E. A., Frith, C. D., Burgess, N., Donnett, J. G., & O’Keefe, J. (1998). Knowing where things are:

Parahippocampal involvement in encoding object locations in virtual large-scale space. Journal of Cognitive

Neuroscience, 10, 61–76.Moffat, S. D., Hampsom, E., & Hatzipantelis, M. (1998). Navigation in a ‘‘virtual maze: Sex differences and

correlation with psychometric measures of spatial ability in humans.’’. Evolution and Human Behavior, 19,73–87.

Montello, D. R. (1998). A new framework for understanding the acquisition of spatial knowledge in large-scale

environment. In M. J. Egenhofer & R. G. Golledge (Eds.), Spatial and temporal reasoning in geographic

information systems (pp. 143–154). New York: Oxford University Press.Montello, D. R., Lovelace, K. L., Golledge, R. G., & Self, C. M. (1999). Sex-related differences and similarities in

geographic and environmental spatial abilities. Annals of the Associations of American Geographers, 89(3),515–534.

O’Keefe, J., & Nadel, L. (1978). Spatial behaviour. The hippocampus as a cognitive map. Oxford Clarendon Press.Orsini, A., Chiacchio, L., Cinque, M., Cocchiaro, C., Schiappa, O., & Grossi, D. (1986). Effect of age, education

and sex on two tests of immediate memory: a study of normal subjects from 20 to 99 years of age. Perceptual

and Motor Skills, 63(2 Pt 2), 727–732.Peruch, P., Vercher, J., & Gauthier, G. M. (1995). Acquisition of spatial knowledge through visual exploration of

simulated environments. Ecological Psychology, 7, 1–20.Peters, M., Laeng, B., Latham, K., Jackson, M., Zaiyouna, R., et al. (1995). A redrawn Vandenberg and Kuse

Mental Rotations Test: Different versions and factors that affect performance. Brain and Cognition, 28, 39–58.Piaget, J., & Inhelder, B. (1967). The child conception of space. New York: Norton.Pick, H. L. (1993). Organization of spatial knowledge in children. In N. Eilan, R. McCharthy, & B. Brewer

(Eds.), Spatial representation. Oxford Blackwell Publisher.Rahman, Q., & Wilson, G. D. (2003). Large sexual-orientation-related differences in performance on mental

rotation and judgement of line orientation tasks. Neuropsychology, 17(1), 25–31.Roof, R. L. (1993). Neonatal exogenous testosterone modifies sex differences in radial arm and Morris water

maze performance in prepubescent and adult rats. Behavioral Brain Research, 53, 1–10.Roof, R. L., Zhang, Q., Glasier, D. G., & Stein, D. G. (1993). Gender specific impairment on Morris water maze

task after after ento-rhinal cortex lesion. Behavioral Brain Research, 57, 47–51.Ruddle, R. A., Payne, S. J., & Jones, D. M. (1997). Navigating buildings in ‘‘desk-top’’ virtual environments:

Experimental investigations using extended navigational experience. Journal of experimental Psychology:

Applied, 3, 143–159.Ruddle, R. A., & Peruch, P. (2004). Effects of proprioceptive feedback and environmental characteristics on

spatial learning in virtual environments. International Journal of Human–Computer Interaction, 60, 299–326.Russell, J. A., & Ward, L. M. (1982). Environmental psychology. Annual Review of Psychology, 33, 651–688.Sandstrom, N. J., Kaufman, J., & Huettel, S. A. (1998). Males and females use different distal cues in a virtual

environment navigation task. Cognitive Brain Research, 6, 351–360.Saucier, D. M., & Green, S. M. (2002). Are sex differences in navigation caused by sexually dimorphic strategies

or by differences in the ability to use the strategies? Behavioral Neuroscience, 116(3), 403–410.Schmitz, S. (1997). Gender-related strategies in environmental development: Effects of anxiety on wayfinding in

and representation of a three-dimensional maze. Journal of Environmental Psychology, 17, 215–228.Shepard, R. N., & Metzler, J. (1971). Mental rotation of three-dimensional objects. Science, 171, 701–703.Siegel, A. W., & White, S. H. (1975). The development of spatial representations of large-scale environments. In

H. W. Reese (Ed.). Advances in child development (Vol. 10). New York: Academic Press.Spinnler, H., & Tognoli, G. (1987). Standardizzazione e taratura italiana dei test neuropsicologici. Italian Journal

of Neurological Science(Suppl. 8), 1–113.Steck, S. D., & Mallot, H. A. (2000). The role of global and local landmarks in virtual environment navigation.

Presence, 9(1), 69–83.Tlauka, M., Brolese, A., Pomeroy, D., & Hobbs, W. (2005). Gender differences in spatial knowledge acquired

through simulated exploration of a virtual shopping center. Journal of Environmental Psychology, 25, 111–118.Tlauka, M., & Wilson, P. N. (1994). The effect of landmark on route-learning in a computer-simulated

environment. Journal of Environmental Psychology, 14, 306–313.Vanderberg, S. G., & Kuse, A. R. (1978). Mental rotations: a group test of three-dimensional spatial

visualization. Perceptual and Motor Skills, 47, 599–604.Waller, D. (2000). Individual differences in spatial learning from computer-simulated environments. Journal of

Experimental Psychology Applied, 6(4), 307–321.


Waller, D., Beall, A. C., & Loomis, J. M. (2004). Using virtual environments to assess directional knowledge’’.Journal of Environmental Psychology, 24, 105–116.

Williams, C. L., Barnett, A. M., & Meck, W. H. (1990). Organizational effects early gonadal secretions on sexual

differentiation in spatial memory. Behavioural Neuroscience, 104, 84–97.Williams, C. L., & Meck, W. H. (1991). The organizational effect of gonadal steroids on sexually dimorphic

spatial ability. Psychoneuroendocrinology, 155–176.

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