TRANSFER OF SPATIAL KNOWLEDGE TO A TWO-LEVEL ...

Environment and Behavior http://eab.sagepub.com

Transfer of Spatial Knowledge to a Two-Level Shopping Mall in Older People, Following Virtual Exploration Nigel Foreman, Danae Stanton-Fraser, Paul N. Wilson, Hester Duffy and Richard Parnell Environment and Behavior 2005; 37; 275 DOI: 10.1177/0013916504269649 The online version of this article can be found at: http://eab.sagepub.com/cgi/content/abstract/37/2/275

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ENVIRONMENT 10.1177/0013916504269649 Foreman et al. / VIRTUAL AND BEHA ENVIRONMENTS VIOR / March 2005

TRANSFER OF SPATIAL KNOWLEDGE TO A TWO-LEVEL SHOPPING MALL IN OLDER PEOPLE, FOLLOWING VIRTUAL EXPLORATION NIGEL FOREMAN worked in St. Andrews, Nottingham, and Leicester Universities before joining Middlesex University as professor of psychology and convenor of a research group investigating applications of virtual environment technology. DANAE STANTON-FRASER is a senior lecturer in psychology at the University of Bath. She carries out research in the areas of spatial cognition and virtual environments, collaborative learning and novel technology design, and evaluation for education. PAUL N. WILSON is a reader in the Department of Psychology at the University of Hull. His research interests are in the area of learning theory, particularly theories of associative and spatial learning. HESTER DUFFY studied psychology and information processing at York University before joining the virtual reality project at Leicester. After a brief period working at the BabyLab at the University of Oxford, she now works at the Open University as a researcher and tutor. RICHARD PARNELL is head of research and public policy for Scope, a national disability charity for the United Kingdom that focuses on cerebral palsy. He has an academic background in social science and information and represents his organization on major medical research projects and government committees.

ABSTRACT: Groups of older and younger participants explored a virtual shopping mall composed of more than 60 retail outlets on 2 levels. They were then compared with guessing controls for their understanding of the spatial layout of the real equivalent building. Experimental groups showed greater accuracy in making pointing judgments toward targets not visible from the pointing site, took shorter times to perform route tasks on foot, made better left-right directional judgments, and sketched better maps of the mall. Of the older participants, 2 out of 8 performed at chance throughout. ENVIRONMENT AND BEHAVIOR, Vol. 37 No. 2, March 2005 275-292 DOI: 10.1177/0013916504269649 © 2005 Sage Publications

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276 ENVIRONMENT AND BEHAVIOR / March 2005

Younger experimental participants remembered better than did older ones on which level targets were located. The study shows that many older people remain spatially competent and that age is not a barrier to the effective use of virtual environment technology, which may be used in the future to increase inclusion of older populations by encouraging their confident use of public buildings. Keywords:

older people; virtual environments; spatial cognition; virtual-real transfer; age

In recent years, numerous studies have shown that the exploration of three dimensional (3-D) computer-generated virtual environments (VEs) can impart spatial knowledge resulting in representations of space that are similar to real exploration (e.g., Jacobs, Laurance, & Thomas, 1997; Rossano, West, Robertson, Wayne, & Chase, 1999; Ruddle, Payne, & Jones, 1997; Wilson, Foreman, & Tlauka, 1997; Witmer, Bailey, Knerr, & Parsons, 1996). Despite the unintuitive features of desk-top virtual reality (VR), interactivity via a manual device and sensory limitations such as narrow visual field extent (Lewis & Griffin, 1997), movement within a virtual space substantially reproduces the experience of moving about within an equivalent real space. Further, studies have shown that spatial information acquired from virtual exploration transfers successfully to an equivalent real environment (Foreman et al., 2000; McComas, Pivik, & Laflamme, 1998; Wilson, Foreman, & Tlauka, 1996, 1997). In one study, a group of children with motor disabilities who had experienced a single-level school in virtual form, when subsequently taken to the real school, were able to identify target locations within the school with relative ease and accuracy by making horizontal pointing judgments. Similarly, they could take economical routes and claimed to feel relatively confident about their understanding of the environment (Foreman, Stanton, Wilson, & Duffy, 2003; Stanton, Wilson, & Foreman, 1996). Virtual exploration does not wholly substitute for real exploration insofar as directional judgments following real exploration are more accurate than AUTHORS’NOTE: The authors gratefully acknowledge financial support from British Telecom and the disability charity Scope. They also appreciate the enthusiastic cooperation of the staff of Ruth Winston House, Palmers Green, London. We are also grateful to Steve Kerr (VIRART, Nottingham University) who advised on the construction of the virtual environment, Dave Newson and Ananthy Baskaran who assisted with computing, and Will Seager, Jody Smith, George Koulieris, Lucy Byrne, Nichola Brown, and Katie Sharp who assisted with data collection. Correspondence concerning this article should be addressed to Nigel Foreman, Middlesex University, Enfield Campus, Queensway EN1 4TL, United Kingdom; phone: 44-0-208-411-2617; fax: 44-0-208-411-5343; e-mail: [email protected].


Foreman et al. / VIRTUAL ENVIRONMENTS 277

those following virtual exploration, though the difference is modest (Wilson et al., 1997). However, the skills acquired from virtual exploration are adequate for many practical purposes, and many studies emphasize the suitability of VEs as spatial training media (e.g., Bliss, Tidwell, & Guest, 1997; Foster, Wenn, & Harwin, 1998; Tate, Silbert, & King, 1997). In most studies of this kind, participants have been university undergraduates or school pupils. Those concerned with remediation have involved children with locomotor or learning difficulties or adults with brain injuries (see Rose & Foreman, 1999, for a review). However, these are not the only groups who can potentially benefit from such training. Indeed, children with locomotor restrictions may not have acquired the spatial skills or cognitive procedures to take maximum advantage of VE learning because they often exhibit a poor understanding of spatial environmental relationships in both virtual and real environments (Foreman, Orencas, Nicholas, Morton, & Gell, 1989; Stanton, Wilson, & Foreman, 2002). This, however, is a debatable point, because, in the course of spatial training in three separate VEs of equal complexity, some improvement in general spatial functioning could be seen in disabled children as though the virtual experience had begun to compensate for their usual lack of independent movement in space and had encouraged the development of cognitive mapping skills (Stanton et al., 1996). This is also the case for stroke patients, for whom VEs have been used in both the assessment and training of spatial skills. Skelton, Bukach, Laurance, Thomas, and Jacobs (2000) found that humans with traumatic brain injuries performed worse than did controls on a virtual water maze task, but Brooks et al. (2000) found that a stroke patient’s understanding of the layout of hospital wards showed significant improvement following VE training, perhaps because VE training allows patients to take advantage of their intact procedural learning skills despite the loss of cognitive mapping and more global spatial abilities. In other words, patients with spatial dysfunction may use a visual medium such as a VE to acquire simple procedural route information (turn right at the blue door) although not necessarily acquiring the map-like survey representation of the environment that is generated by an individual whose spatial functions are intact. It is not clear whether such allocentric spatial mapping abilities can be trained using VEs in different spatially challenged groups. It is of particular interest to know whether older individuals can make effective use of VE technology in the spatial domain. Clearly, there are limitations to VE use by older individuals that do not apply to other groups. With advancing age, visual image resolution is poorer at the low illumination levels (greater intraocular light scatter in the ageing eye precluding the use of higher intensities of illumination) that typically characterize VE displays.



Visual acuity is lower and both vergence eye movements and accommodation are reduced (though such effects may not always be selectively disadvantageous; see McDonald et al., 1999) and the fixed accommodative distance of VE displays may conflict less with binocular fusion in older than in younger participants (cf. Loomis, Blascovich, & Beall, 1999). Older individuals are slower and less dextrous when making motor responses and controlling displacements; their memory may be impaired, and they are generally less familiar with computers compared with younger age groups (Bucur & Kwon, 1999). Liu, Watson, and Miyazaki (1999) found older participants to be especially prone to cybersickness in immersion VEs. However, such factors do not preclude the use of VEs by older groups (McGee et al., 2000; Wiederhold & Wiederhold, 2000). McDonald et al. (1999) found that a group aged around 70 years took twice as long as younger participants to navigate through doorways in a series of virtual rooms, yet they completed the task without difficulty. Rose et al. (1999) found that stroke patients aged 25 to 85 years (M = 61 years) with a wide range of motor and cognitive impairments but with less skill at acquiring information about building layouts as compared with non-brain-injured controls nevertheless showed significant spatial learning particularly when actively directing their own virtual exploration. Greater performance variability is to be expected in older participant groups (McGee et al., 2000). Difficulties in accessing public buildings remains a major cause of mobility limitation in disabled individuals (Foster et al., 1998). For example, those whose agility and speed of locomotion is restricted will often report that they fear venturing into public spaces because they could become disoriented and lose their way. This phenomenon occurs more frequently in older individuals and may have a knock-on effect as a secondary consequence of impaired mobility, leading to a progressive loss of navigational skills and increasing isolation as the individual ventures into public places less and less. This functional change may be additive to the degenerative loss of tissue in those neural structures that mediate spatial cognition, and the loss of exploratory experience may lead to further atrophy. Studies have shown that advancing age typically reduces activity in those forebrain structures that are known to be important in allocentric spatial memory and the executive use of spatial information in both humans and animals (Barnes, 1990, 1998; Barrash, 1998) such as the hippocampal formation (Maguire et al., 1998). Consistent with this general idea, aging individuals (71-84 years) have been shown, in a study requiring place discriminations in a VE, to use fewer allocentric spatial strategies than younger age groups (Thomas, Laurance, Luczak, & Jacobs, 1999). In a complex virtual maze environment, Moffat, Zonderman, and Resnick (2001) found that, after five trials, whereas 86% of young participants took



error-free routes, only 24% of elderly participants did so. However, performance that is poor, relative to younger participants, does not rule out the beneficial use of VEs in training spatial skills, either procedural spatial skills (stroke patients; cf. Brooks et al., 2000; Rose et al., 1999) or allocentric mapping skills, in older individuals, and thus VEs might be valuable training media, enabling the optimal maintenance of spatial skills into old age. In terms of spatial cognition, older individuals may make more profitable use of VEs than the disabled children and stroke patients described earlier. They are better primed to acquire and interpret spatial information than are children, having had lifelong experience of independent navigation in a wide range of environments. Moreover, unlike stroke patients, they have usually not suffered a specific loss of a particular memory component (e.g., allocentric spatial skills; cf. Kirasic, 1991), and they are therefore not restricted to using particular strategies to solve spatial problems (cf. Brooks et al., 2000; Rose et al., 1999). As the population ages, older people might be expected to make increasing use of VE training (see McDonald et al., 1999) and may thereby be able to overcome some aspects of social exclusion by maintaining spatial memory skills and neighborhood knowledge, both of which are important determinants of neighborhood use in older individuals (Simon, Walsh, Regnier, & Krauss, 1992). Because many of the environments that older people may wish to visit but feel reluctant to visit are public buildings, the present study examined exploration in a complex public shopping mall having over 60 retail outlets on two shopping levels. Able-bodied individuals will, anecdotally, report losing their way from time to time within this complex environment, particularly when the routes they need to take between target shop locations involve moving among vertical levels. Most previous studies of VEs as spatial training media have employed single-level environments such as single-tier schools (Stanton et al., 1996) and have required judgments to be made solely in the horizontal plane. Studies employing tiered environments have variously reported that routes are selected efficiently (Regian, Shebilske, & Monk, 1992), that routes but not survey or mapping information are learned (Witmer et al., 1996), and that both route and survey information is learned well (Wilson et al., 1997). Directional pointing judgments were less accurate when pointing location and target objects were on different vertical levels than when they were within the same level (Richardson, Montello, & Hegarty, 1999; Wilson et al., 1997) and more accurate to downward targets than to upward targets (Wilson, Foreman, Stanton, & Duffy, 2004). Thus, the present study investigated the generality of VEs as spatial training media by investigating both route and survey learning, incorporating directional judgments to targets on the same or different levels within the environment.



A desk-top VE was used because these have previously been shown to be effective in spatial navigational studies (Wilson et al., 1997) and to be as effective (Johnson & Stewart, 1999), or in certain respects more effective, than immersive displays (Gamberini, 2000). They were also used to avoid the simulator sickness associated with immersive displays (Kesztyues et al., 2000) to which older individuals seem particularly prone (Liu et al., 1999).

METHOD PARTICIPANTS

Thirty-two participants were recruited, 16 of whom were over 60 years and 16 of whom were university undergraduates. The older participants were volunteers, recruited via an advertisement posted in a drop-in center for people of retirement age. They were not paid for participating, but the costs of their participation were reimbursed. None had prior experience in the shopping mall used in the test. Each age group was subdivided into 8 experimental and 8 controls, and within-age groups were assigned via random allocation. The younger groups’mean ages were 26.3 years (range 21-33) for the experimental and 21.75 years (range 17-35) for the control. The groups had three males and four males, respectively. The older groups’ corresponding mean ages were 73.9 years (range 62-82) and 74.6 years (range 64-82). The older groups had two and three males, respectively. All had normal or corrected-tonormal vision, and their ability to see and identify objects and targets clearly on the screen was checked and confirmed during training. All were mobile on foot. They were informed of their right to withdraw from the experiment at any time. MATERIALS

The environment consisted of two levels of a shopping mall (The Shires) in Leicester, United Kingdom. It is a 1980s building that contains over 60 colorful retail outlets (see Figure 1). Most outlets line the sides of a wide main concourse that is about 360 feet in length, but branching alleyways, also lined with shops, lead from the concourse toward restroom facilities, ATMs, restaurants, and entrances and exits. The concourse is open-plan, with bridges connecting the two sides of the main concourse on the upper level, on which vending outlets are located. Between the bridges are open spaces surrounded by railings through which one level is visible from another. On the lower



Figure 1: A View of the Virtual Environment Showing the Upper and Lower Floors of the Main Concourse

level, the center of the concourse contains flowers and seating plus displays and vending outlets. Levels are connected by an escalator and stairway (at the two ends of the mall) and a centrally located elevator. Two of the outlets are department stores with upper and lower floors. Above the shopping levels are parking areas. The mall was modeled to scale using Superscape Virtual Reality Toolkit, and the model was based on the architects’ plans. Shop frontages were composed of texture-mapped images of the actual frontages. The interiors of shops could not be explored. In some cases, images of shop frontages unavoidably included one or two shoppers. Stairways and the elevator could be used in the course of virtual exploration to move among levels and to access the first parking level (although the parking areas per se were not simulated). Two areas of the mall with retail outlets, peripheral to the central concourse, were not included in the simulation and were ignored for testing purposes (though one of these unexplored areas was used to transport participants into the mall for testing). The viewing height was fixed at approximately human eye level, assuming average height to be about 5 feet, 6 inches. The device used for making pointing judgments in the test consisted of a moveable, hand-held metal pointer attached to two fixed, 360-degree pro-



tractors in the vertical and horizontal planes. The device was held with the horizontal protractor parallel with the floor and was initially set to zero in both planes. The participant moved the pointer horizontally and vertically to indicate the pan and tilt angle of the center of each target specified by the experimenter, the two angles being read from the protractors. PROCEDURE

Prior to the study, the older experimental group participated in a computer awareness course. The two experimental groups were given individual experiences exploring the VE shopping mall for four sessions of 30 minutes each. In each session, the participant sat at a comfortable viewing distance from a standard Toshiba laptop computer on which the VE was displayed. They explored the mall while being observed by the experimenter, displacements within the VE being controlled via depression of the cursor keys on the keyboard: The up and down cursors created forward and back movements, whereas the left and right cursors created left and right rotation. Participants in both experimental groups were able to control their own displacements after a short period of practice. (Occasionally, where collision detection was faulty in the VE, a participant who passed through a wall had to be asked to reverse back into the mall area, although this happened rarely.) Entry into the VE always occurred at the same location (a bland, gray-walled entrance at one end of the mall), but this entrance was not used when participants were escorted into the real mall for testing. On days 3 and 4 of exploration, target locations that were to be used for testing in the real mall were emphasized to participants who were asked to remember them. Several targets were chosen among those that a visitor to the mall would be likely to need to access. These consisted of several shops (both distinctive and less distinctive), the post office, the chemist, a coffee shop, a flower-vending barrow, the elevator, the restrooms, and the ATMs. Two days after the final exploration session, participants were transported by bus over a distance of approximately 93 miles to the actual shopping mall. They did not enter the mall until testing was about to commence. Testing was conducted individually. On entry via an unfamiliar part of the mall (see above), the participant was first escorted to one of the locations pointed out in the simulation, a travel center from which they could see only a few shops at one end of the main concourse. From this location, they were asked to make pointing judgments to four targets that were not directly visible using the pointing device. They were taken to three further locations within the mall, at which they made five, four, and five judgments, respectively. Of the 18



obscured targets, 6 were on a floor above, 6 were on a floor below, and 6 were on the same floor as the pointing location. (Because for each judgment the target could be only on the same floor or above or on the same floor or below, the participants had a 50% chance of being correct on each trial). The participant then completed six errand tasks that required moving on foot from a starting point to a specific target location. For example, after locating a card shop, the participant was told, “Now you need to buy a stamp for the card, so where is the post office? Please go to the post office taking the shortest route.” The time taken to walk to each target was recorded. If the target had not been reached (or, in the case of controls, discovered) after 180 seconds, the participant was escorted to the target, and the next task was presented. Three tasks involved traveling on the same floor, two involved descending a level, and one involved ascending a level. Two tasks required the participant to traverse the length of the mall, whereas four tasks demanded relatively short local excursions. Following testing, participants were escorted from the mall. They later completed two questionnaires. One asked for information about the layout of the mall and about which stores were located above or below others. It also asked 12 directional questions such as, “When approaching shop X, are the toilets to your left or your right?” Participants were asked to draw freehand sketch maps of the two floors of shops, incorporating as much landmark information as possible. A second questionnaire, directed particularly toward the older group, asked for personal details relating to their occupations (type of job prior to retirement, highest educational qualification) and health (eyesight problems, physical limitations, whether they had suffered any form of brain injury). The confidentiality of this information was assured via a numerical coding system to which only the experimenter had access for data collation purposes. Between the dates of construction of the simulation and testing, a small number of changes had occurred within the building. For example, a shop had been replaced, and a letter posting box near the post office had not been included in the simulation. These changes did not include any of the target landmarks to which participants’ attention had been drawn in testing. Nevertheless, we were able to ask experimental participants to list discrepancies that they noted within the actual mall compared with the simulation. Such mismatch information is important in the maintenance of cognitive environmental maps (cf. O’Keefe & Nadel, 1978) and was therefore used in the present study as a further cognitive spatial measure reflecting the strategic spatial information acquired in the course of visiting the mall for testing.



Pointing error (deg.)

80

SEM = 1.79

SEM = 3.41

70 60 50

SEM = 7.03

SEM = 4.60

40 30 20

33.86

65.04

39.25

69.71

10 0 Young exp

Young con

Older exp

Older con

Figure 2: Horizontal Pointing Accuracy in Degrees (M and SE ) in Young and Older Experimental and Control Groups When Estimating the Directions of Targets Within the Actual Shopping Mall NOTE: exp = experimental group; con = control group; SEM = standard error of the mean. N = 8 (for all groups).

RESULTS

No participant complained of cybersickness or other discomfort during training or testing. In completing the health and occupation questionnaire, none reported illnesses (e.g., brain injury, stroke) that were likely to have specifically impaired their spatial cognition, and their former occupations did not include any that specifically demanded spatial skills (e.g., taxi driving). Figure 2 shows the mean individual horizontal pointing accuracy scores for all participants as averaged across the four pointing locations (18 targets). Data were analyzed using a two-way analysis of variance (ANOVA), with age (students vs. older people) and condition (VE experience vs. no VE experience) the factors. This revealed that although age did not significantly affect horizontal pointing accuracy, F(1, 28) = 1.18, p > .05, condition was highly significant, F(1, 28) = 44.59, p < .001, with the VE-trained groups pointing significantly more accurately than controls. There was no significant interaction effect, F < 1. There was no significant difference between horizontal pointing errors made when pointing to targets on the same or different levels of the mall. Unlike studies that required pointing to a small number of well-trained targets (cf. Wilson et al., 1997), vertical pointing judgments in the present study included many that were inaccurate, precluding meaningful measurement of vertical pointing accuracy per se. However, analysis of the judgments



160

SEM = 9.52

Time (sec.)

140 SEM = 8.75

120 100 80

SEM = 11.25 SEM = 5.93

60 40 20

59.40

106.03

70.30

131.58

0 Young exp

Young con

Older exp

Older con

Figure 3: Average Time in Seconds (M and SE ) Taken to Complete Tasks Within the Actual Shopping Mall in Young and Older Experimental and Control Groups NOTE: exp = experimental group; con = control group; SEM = standard error of the mean. N = 8 (for all groups).

of level (below vs. same, for upper, and above vs. same, for lower floor pointing locations) showed that although the two control groups scored at chance level (students = 50.0%, older people = 50.7%), the two experimental groups performed substantially above chance (students = 75.7%, older people = 60.4%). The student experimental group was significantly more accurate on this measure than was the older experimental group, T(14) = 3.31, p < .01. When asked to walk to specified target locations within the shopping mall (see Figure 3), groups’ latencies differed significantly. The data were analyzed using a two-way ANOVA, with age and condition as factors. Condition was found to be highly significant, F(1, 28) = 35.88, p < .001, both young and older VE-trained participants finding targets significantly more quickly than controls. However, for this measure, age was also significant, F(1, 28) = 4.45, p < .05, with older people taking longer than their student counterparts. There was no significant interaction effect, F < 1. Young controls were timed out after 3 minutes on an average of 2.4 occasions compared with older controls’ 3.3. Maps were rated on a scale of 0 to 10, according to a scale that was devised for the purpose, by two separate blind raters who knew the Shires environment well. The scale took into account the overall organization of the map (e.g., depiction of a clear concourse) and the relative positions of those landmarks depicted. Ratings for level 1 and level 2 maps were combined to form a single score. There was good agreement between raters, Spearman’s rho(n =


286 ENVIRONMENT AND BEHAVIOR / March 2005 TABLE 1 Correlations Among Performance Measures in Experimental Participants

Average time Directions Pointing error

Directions

Pointing Error

Map Rating

r = –.785 p < .001 —

r = .377 ns r = –.438 ns —

rho = –.244 ns rho = .693 p < .004 rho = –.062 ns

32) = .90. Six participants were unable to draw any kind of map, but with these zero scores excluded, interrater agreement was still high, rho(n = 26) = .84. Kruskal-Wallis nonparametric ANOVA was used to compare the map rating scores of the two experimental groups (students and older people, each n = 8), with the two control groups combined together (n = 16). This revealed group differences, chi-square (df = 2) = 7.47, p = .024. Group comparisons using the Mann-Whitney U test (corrected for ties) showed that the student and older experimental groups were not significantly different, but both scored significantly higher than did controls (Us = 29.5 and 26.5, respectively, ps < .05). When asked in the follow-up questionnaire about the directions (left or right) of particular targets in relation to specified landmarks, groups again differed in the mean number correct. The data were analyzed using a twoway ANOVA, with age and condition as factors, that found condition to be highly significant, F(1, 28) = 8.52, p < .008. VE-trained groups again outperformed controls, but age was not significant, F(1, 28) = 0.34, p > .05. There was no significant interaction effect, F < 1. Intercorrelations (Pearson’s r) were calculated for the above measures (horizontal pointing accuracy, time taken to walk to targets, and the number of correctly judged directions of targets from specified landmarks) for the student and older experimental groups combined (n = 16 for each comparison). These intercorrelations are shown in Table 1. Nonparametric correlations (Spearman’s rho) are also shown in Table 1 for the mean map-rating measure. The number of correctly judged directions was significantly negatively correlated with the time taken to complete errand tasks but was significantly positively correlated with the ability to draw maps of the mall. These significant correlations were not artifactual because, in all cases, equivalent correlations for the combined control groups failed to approach significance.



When asked about discrepancies detected between the real mall and the VE, student experimentals tended to list more than older experimentals (Mann-Whitney U test: U = 14.5; n1 = n2 = 8; p = .052.

DISCUSSION

This study complements many earlier studies that have demonstrated that good spatial information about buildings and large-scale environments can be acquired from virtual displays (Foreman et al., 2000, 2003; Jacobs et al., 1997; Ruddle et al., 1997; Stanton et al., 1996; Wilson et al., 1996, 1997; Witmer et al., 1996). However, the present results have extended these findings, showing that a VE can be used beneficially not only by younger participants but also by older people to enhance their spatial knowledge of a novel, unfamiliar building. All of the present group of older people had some computer familiarity. Two of the older participants appeared to be unable to benefit from the training and performed at chance level throughout all aspects of spatial testing. Further studies, incorporating full clinical assessment prior to training, would be needed to determine whether this reflects age-related deterioration in spatial brain processing per se (cf. Barnes, 1990, 1998; Barrash, 1998; Moffat et al., 2001; Thomas et al., 1999) or alternatively idiosyncratic changes, such as the absence of scanning-while-stationary, that are seen in those older individuals who perform poorly on spatial navigational tasks (Kirasic, 1991). In the present study, there were clear and highly statistically reliable beneficial effects of VE training in a group that included octogenarians, and although greater variability was observed in older than in younger participants (cf. McGee et al., 2000), there was no detectable relationship within this group between age and performance. The data support the accumulating evidence that many older individuals remain capable of acquiring spatial information effectively, if more slowly, in novel, real environments such as supermarkets (Kirasic, 1991) and in VEs where they are able to recall and reconstruct a spatial layout successfully despite mis-locating specific targets (Laurance et al., 2002). However, it would be interesting to know whether the general improvements in spatial judgments seen in children exposed to a series of VEs (Stanton et al., 1996) would apply to older individuals and thus whether VE training benefits generalize across VE-based tasks or transfer to subsequent real environments. Older participants clearly have performance limitations in terms of dexterity and speed of movement, both in the real environment and in navigating



the VE (McDonald et al., 1999). Speed of mobility must have influenced latencies in the way finding task in the real environment. The younger controls were perhaps quicker and more agile when moving in the mall and may thus have happened upon target locations by chance more often within the time allowed. Older controls were timed out more often than younger controls. However, in pointing, map drawing, and directional judgments, age is unlikely to have had this kind of secondary impact on test performance. The pattern of intercorrelations among the measures of spatial skill suggest that different aspects of spatial cognition were tested. The longer participants took to walk to landmarks (way finding), the poorer they were in making correct left or right judgments of target directions from specified landmarks, suggesting that these measures are related, reflecting landmarkbased skills. However, way finding did not correlate with measures of map drawing or horizontal pointing accuracy toward targets, the latter arguably making greater demands on allocentric survey knowledge. Thus, the significantly better map sketching, directional pointing, and way finding in the experimental than in control groups, both young and old, suggest that the virtual spatial training influenced not only procedural- and landmark-based skills (such as turn left at the cash dispensers to reach the post office, reflected in way finding) but also imparted knowledge of a configurational or survey nature (reflected by pointing and map drawing). It is difficult to separate the influences of procedural and configurational knowledge on most spatial measures, and both are probably used conjointly in the course of everyday exploration. Yet in this study, as in previous studies with both disabled and nondisabled children across several sessions of virtual exploration (Stanton et al., 1996), both types of knowledge seemed to have been effectively acquired. No specific attempts were made in the present study to train procedural memory, as was done in a previous VE study with a severely impaired patient who had stroke-induced brain damage (Brooks et al., 2000). It is possible that the two older participants who responded by chance on several spatial tasks in the present study might have benefited from such specific procedural instructions. However, there was little evidence in the present data to support the widespread use of simple cue-based orienting strategies among the more spatially competent older participants, as might have been predicted from the results of Thomas, Laurance, Luczak, and Jacobs (1999). In particular, the use of allocentric mapping-like strategies that specifically took into account interrelationships among diverse and noncurrently visible landmarks when making pointing judgments was evident from casual comments made by older participants to the experimenter in the course of testing within the actual mall.



There was a preponderance of female participants in both age groups in the present study, which might limit the generality of the conclusions particularly because large gender differences, favoring males, have been reported in a virtual maze task by Astur, Ortiz, and Sutherland (1998). However, in many other studies, gender differences were small. For example, Thomas et al. (1999, p. 563) reported that from a total of 1,800 participants in a virtual arena task, there were at best variable and inconsistent gender differences. Where such effects are observed, these are largely accounted for by differential familiarity with computers and computer games (Waller, 2000). Both the males and the females in the crucial older experimental group in the present study, although having had limited computer exposure during their lives, had all recently been given computer familiarization, both factors minimizing the impact of this possible source of variance. As part of the information age and postindustrial society, VE technology can offer an opportunity to reverse the tendency for information products to increase the isolation of families and households by encouraging disadvantaged groups back into the community. Radio and television, video games, personal computers, the internet, e-mail, and intelligent global positioning guidance technology all enable passive and effortless experience of the world. VEs as used in the present study, in contrast, offer older people or others who lack confidence in engaging with the world an opportunity to reengage in their daily lives. The choice of a shopping mall in the present study is especially significant because maintenance of spatial skills and the encouragement of social engagement via shopping amongst groups of people who are likely to have been either gradually socially excluded (as in this study, older people) or people with disabilities (who may never have been wholly socially included) is important when the ability to shop is seen in its full cultural context. Shopping is about buying goods, but more importantly it is about maintaining contacts with the community. The results of this study further emphasize that age is no barrier to the use of VEs (McGee et al., 2000; Wiederhold & Wiederhold, 2000) and bode well for the future use of VEs as assessment (Rizzo et al., 2001) and training media (Bliss, Tidwell, & Guest, 1997), particularly among the burgeoning postretirement population (McDonald et al., 1999). Our results reinforce the view of Bucur and Kwon (1999) that “the myth that ‘older people cannot use computers’ should be revisited” (p. 541). However, further studies are needed to assess whether VE training is beneficial for older people who are less familiar with computers, less independently mobile, and more fearful of venturing into public buildings (cf. Foster et al., 1998) and who are in more complex and confusing situations (cf. Moffat et al., 2001) than were those



older people who participated in the present study. It is also important to establish whether VE training improves upon suitable training regimes within real environments or with other media (cf. Hunt, Arch, & Roll, 1987) and whether different forms of VE spatial training, for example emphasizing procedural spatial learning (Brooks et al., 2000), could make VE training in a shopping mall environment universally beneficial among older participants.

REFERENCES Astur, R. S., Ortiz, M. L., & Sutherland, R. J. (1998). A characterization of performance by men and women in a virtual Morris water maze task: A large and reliable sex difference. Behavioural Brain Research, 93, 185-190. Barnes, C. A. (1990). Animal models of age-related cognitive decline. In F. Boller & J. Grafman (Eds.), Handbook of neuropsychology (Vol. 4, pp. 169-196). Amsterdam: Elsevier. Barnes, C. A. (1998). Spatial cognition and functional alterations of aged rat hippocampus. In E. Wang & D. S. Snyder (Eds.), Handbook of the aging brain (pp. 51-66). New York: Academic Press. Barrash, J. (1998). A historical review of topographical disorientation and its neuroanatomical correlates. Journal of Clinical and Experimental Neuropsychology, 20, 807-827. Bliss, J. P., Tidwell, P. D., & Guest, M. A. (1997). The effectiveness of virtual reality for administering spatial navigational training to firefighters. Presence, Teleoperators and Virtual Environments, 6, 73-86. Brooks, B. M., NcNeil, J. E., Rose, F. D., Greenwood, R. J., Attree, E. A., & Leadbetter, A. G. (2000). Route learning in a case of amnesia: The efficacy of training in a virtual environment. Neuropsychological Rehabilitation, 9, 63-76. Bucur, A., & Kwon, S. (1999). Computer hardware and software interfaces: Why the elderly and under-represented as computer users. Cyberpsychology and Behavior, 2, 535-543. Foreman, N. P., Orencas, C., Nicholas, E., Morton, P., & Gell, M. (1989). Spatial awareness in seven to eleven year-old physically handicapped children in mainstream schools. European Journal of Special Needs Education, 4, 171-179. Foreman, N., Stanton, D., Wilson, P., & Duffy, H. (2003). Spatial knowledge of a real school environment acquired from virtual or physical models by able-bodied children and children with physical disabilities. Journal of Experimental Psychology: Applied, 9, 67-74. Foreman, N., Stirk, J., Pohl, J., Mandelkow, L., Lehnung, M., Herzog, A., et al. (2000). Spatial information transfer from virtual to real versions of the Kiel locomotor maze. Behavioural Brain Research, 112, 53-61. Foster, G. T., Wenn, D. E. N., & Harwin, W. S. (1998). Generating virtual environments to allow increased access to the built environment. The International Journal of Virtual Reality, 3, 12-20. Gamberini, L. (2000). Virtual reality as a new research tool for the study of human memory. Cyberpsychology and Behavior, 3, 337-342. Hunt, M. E., Arch, D., & Roll, M. K. (1987). Simulation in familiarizing older people with an unknown building. The Gerontologist, 27, 169-175. 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.


Foreman et al. / VIRTUAL ENVIRONMENTS 291 Johnson, D. M., & Stewart, J. E. (1999). Use of virtual environments for the acquisition of spatial knowledge: Comparison among different visual displays. Military Psychology, 11, 129-148. Kesztyues, T. I., Mehlitz, M., Schilken, E., Weniger, G., Wolf, S., Piccolo, U., et al. (2000). Preclinical evaluation of a virtual reality neuropsychological test system: Occurrence of side effects. Cyberpsychology and Behavior, 3, 343-354. Kirasic, K. C. (1991). Spatial cognition and behavior in young and elderly adults: Implications for learning new environments. Psychology and Aging, 6, 10-18. Laurance, H. E., Thomas, K. G. F., Newman, M. C., Kaszniak, A. W., Nadel, L., & Jacobs, W. J. (2002). Older adults map novel environments but do not place learn: Findings from a computerized spatial task. Aging, Neuropsychology, and Cognition, 9, 85-97. Lewis, C. H., & Griffin, M. J. (1997). Human factors consideration in clinical applications of virtual reality. In G. Riva (Ed.), Virtual reality in neuro-psycho-physiology (pp. 35-36). Amsterdam: IOS Press. Liu, L., Watson, B., & Miyazaki, M. (1999). VR for the elderly: Quantitative and qualitative differences in performance with a driving simulator. Cyberpsychology and Behavior, 2, 567-576. Loomis, J. M., Blascovich, J. J., & Beall, A. C. (1999). Immersive virtual environment technology as a basic research tool in psychology. Behavior Research Methods, Instruments and Computers, 31, 557-564. Maguire, E. A., Burgess, N., Donnett, J. G., Frackowiak, R. S. J., Frith, C. D., & O’Keefe, J. (1998). Knowing where and getting there: A human navigation network. Science, 280, 921924. McComas, J., Pivik, J., & Laflamme, M. (1998). Children’s transfer of spatial learning from virtual reality to real environments. Cyberpsychology and Behavior, 1, 121-128. McDonald, D. P., Vincenzi, D. A., Muldoon, R. V., Tyler, R. R., Barlow, A. S., & Smither, J. A. (1999). Performance differences between older and younger adults for a virtual environment locomotor task. In M. W. Scerbo & M. Mouloua (Eds.), Automation technology and human performance: Current research and trends (pp. 262-269). Mahwah, NJ: Lawrence Erlbaum. McGee, J. S., Van der Zaag, C., Buckwalter, J. G., Thiebaux, M., Van Rooyen, A., Neumann, U., et al. (2000). Issues for the assessment of visuospatial skills in older adults using virtual environment technology. Cyberpsychology and Behavior, 3, 469-482. Moffat, S. D., Zonderman, A. B., & Resnick, S. M. (2001). Age differences in spatial memory in a virtual environment navigation task. Neurobiology of Aging, 22, 787-796. O’Keefe, J., & Nadel, L. (1978). The hippocampus as a cognitive map. London: Oxford University Press. Regian, J. W., Shebilske, W. L., & Monk, J. M. (1992). Virtual reality: An instructional medium for visuo-spatial tasks. Journal of Communication, 42, 136-149. Richardson, A. E., Montello, D. R., & Hegarty, M. (1999). Spatial knowledge acquisition from maps and from navigation in real and virtual environments. Memory and Cognition, 27, 741750. Rizzo, A. A., Buckwalter, J. G., McGee, J. S., Bowerly, T., van der Zaag, C., Neumann, U., et al. (2001). Virtual environments for assessing and rehabilitating cognitive/functional performance. Presence, 10, 359-374. Rose, F. D., Brooks, B. M., Attree, E. A., Parslow, D. M., Leadbetter, A. G., McNeil, J. E., et al. (1999). A preliminary investigation into the use of virtual environments in memory retraining after vascular brain injury: Indications for future strategy? Disability and Rehabilitation, 21, 548-554. Rose, D., & Foreman, N. (1999). Virtual reality: A new tool for psychology? The Psychologist, 12, 550-554.


292 ENVIRONMENT AND BEHAVIOR / March 2005 Rossano, M. J., West, S. O., Robertson, T. J., Wayne, M. C., & Chase, R. B. (1999). The acquisition of route and survey knowledge from computer models. Journal of Environmental Psychology, 19, 101-115. 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. Simon, S. L., Walsh, D. A., Regnier, V. A., & Krauss, I. K. (1992). Spatial cognition and neighborhood use: The relationship in older adults. Psychology and Aging, 7, 389-394. Skelton, R. W., Bukach, C. M., Laurance, H. E., Thomas, K. G. F., & Jacobs, W. J. (2000). Humans with traumatic brain injuries show place-learning deficits in computer-generated virtual space. Journal of Clinical and Experimental Neuropsychology, 22, 157-175. Stanton, D., Wilson, P., & Foreman, N. (1996). Using virtual reality environments to aid spatial awareness in disabled children. In P. Sharkey (Ed.), Proceedings of the first European Conference on Disability, Virtual Reality and Associated Technologies (pp. 93-101). Maidenhead, Berkshire, UK: University of Reading. Stanton, D., Wilson, P., & Foreman, N. (2002). Effects of early mobility on shortcut performance in a simulated maze. Behavioural Brain Research, 136, 61-66. Tate, D. L., Silbert, L., & King, T. (1997). Using virtual environments to train firefighters. IEEE Computer Graphics and Applications, 17, 23-29. Thomas, K. G. F., Laurance, H. F., Luczak, S. E., & Jacobs, W. J. (1999). Age-related changes in a human cognitive mapping system: Data from a computer-generated environment. Cyberpsychology and Behavior, 2, 545-566. Waller, D. I. (2000). Individual differences in spatial learning from computer-generated environments. Journal of Experimental Psychology: Applied, 6, 307-321. Wiederhold, B. K., & Wiederhold, M. D. (2000). Lessons learned from 600 virtual reality sessions. Cyberpsychology and Behavior, 3, 393-400. Wilson, P., Foreman, N., Stanton, D., & Duffy, H. (2004). Memory for targets in a multi-level simulated environment: Evidence for vertical asymmetry in spatial memory. Memory and Cognition, 32, 283-297. Wilson, P. N., Foreman, N., & Tlauka, M. (1996). Transfer of spatial information from a virtual to a real environment in physically disabled children. Disability and Rehabilitation, 18, 633-637. Wilson, P. N., Foreman, N., & Tlauka, M. (1997). Transfer of spatial information from a virtual to a real environment. Human Factors, 39, 526-531. Witmer, B. G., Bailey, J. H., Knerr, B. W., & Parsons, K. C. (1996). Virtual spaces and real world places: Transfer of route knowledge. International Journal of Human-Computer Studies, 45, 413-428.


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