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Pointing accuracy: Does individual pointing accuracy differ for indoor vs. outdoor locations?
Journal of Environmental Psychology 38 (2014) 175e185
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Journal of Environmental Psychology journal homepage: www.elsevier.com/locate/jep
Pointing accuracy: Does individual pointing accuracy differ for indoor vs. outdoor locations? Pamela L.J. Berry*, Scott Bell University of Saskatchewan, 105 Administration Place, Saskatoon, SK S7N 5A2, Canada
a r t i c l e i n f o
a b s t r a c t
Article history: Available online 7 February 2014
Pointing accuracy to and from indoor and outdoor locations was examined to reveal any significant differences in the accuracy with which we recall the arrangement of unseen locations in the world around us. Spatial ability and navigational strategy were included to better understand the cognitive processes involved in pointing accuracy and subsequent environmental knowledge. Results from this study indicate that knowledge for indoor and outdoor environments is indeed different. Individual pointing is more accurate to landmarks and locations that are inside buildings than to those outside, whether or not they point from an indoor or outdoor origin. As well, the preference for configurational and somewhat more complex navigational strategies, as expressed through questionnaire results, is positively correlated with increased pointing accuracy. Ó 2014 Elsevier Ltd. All rights reserved.
Keywords: Spatial cognitive microgenesis Pointing error Spatial ability Navigation
1. Introduction We have all experienced navigational difficulties requiring maps, GPS, or other individuals at one time or another. Often these difficulties tend to arise in specific environments that vary for individuals. Some may be uncomfortable driving in a new city, while others may find it difficult to navigate in a complex building with many functions and floor levels. What is it about these differing environments that affect our ability to navigate efficiently? Studies have shown that despite becoming familiar with certain environments (such as the workplace), the navigational difficulties an individual first experiences can continue for years (Wang & Brockmole, 2003a). These difficulties may cause decreased safety, stress, discomfort, and loss of time. In extreme cases, getting lost in isolated environments can be life-threatening (Montello & Sas, 2006). Despite scientific evidence that the nature of an environment can impact how we learn and move through it, the majority of research relies on a common and relatively narrow set of principles of spatial knowledge acquisition and use. To remedy these issues, it is important to understand how navigation is affected by elements within and associated with the built environment. There are a variety of characteristics within our environment, both visual and structural, that support navigation. Effective navigation is defined by Montello and Sas (2006) as requiring individuals to apply psychological skills such as perception and * Corresponding author. Tel.: þ1 306 261 0460. E-mail addresses: [email protected], [email protected] J. Berry), [email protected] (S. Bell). http://dx.doi.org/10.1016/j.jenvp.2014.01.007 0272-4944/Ó 2014 Elsevier Ltd. All rights reserved.
(P.L.
cognition in conjunction with motor behaviors. Goal directed use of knowledge, cognitive processes, and locomotion to travel from one location to the next is referred to as wayfinding (Montello & Sas, 2006). An important factor in wayfinding is orientation. For wayfinding to be effective, one must be aware of their position in relation to other places, destinations, and objects. Precision is often not required in orientation, as effective navigation can occur even when one’s orientation is coarse or partial (Montello & Sas, 2006). The availability of information during wayfinding differs among environments. Factors affecting these differences include differentiation (ability to distinguish between within environment elements), visual access, and layout complexity (Montello, 2007). Differentiation is characterized by variation in size, shape, and color of items; in the case of built environments; differences in architectural style tend to aid navigation. While increased within environment differentiation typically aids navigation, too much can be disorienting (Montello & Sas, 2006). Both differentiation and visual access affect landmark effectiveness during navigation. As well, the type and availability of landmarks is thought to affect navigational success (Goldberg, 2008). Outdoor landmarks tend to consist of large, highly visible objects such as buildings, while indoor landmarks tend to be smaller objects, such as lobbies, paintings, and other features (Giudice, Walton, & Worboys, 2010). Layout complexity is the final environmental factor that is thought to affect wayfinding. This factor is difficult to define, as complexity is dependent on individual abilities to visually and cognitively organize complex environments. If patterns and effective organization are apparent to the navigating individual, complex environments become much easier to understand and navigate (Montello & Sas, 2006).
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Differences between environments that might affect wayfinding or spatial knowledge acquisition have not been studied extensively within the spatial cognitive domain. Specifically, studies have yet to analyze any differences in our ability to locate and use indoor versus outdoor locations. As indoor spaces are considered more challenging for apprehension and learning, it would be useful to empirically test this logic (Goldberg, Wilson, Knoblock, Ritz, & Cockburn, 2008). One apparent difference between indoor and outdoor environments is the availability of landmarks. As noted above, landmarks utilized for indoor navigation tend to differ greatly in both availability and type from landmarks associated with outdoor locations. As well, the field of view available to an individual in each environment differs greatly with respect to the number of landmarks for building the cognitive maps for the entire surroundings. The distinction between indoor and outdoor environment belies the variation that can be found within either category. Perhaps the most compelling characteristic of indoor spaces is the constrained field of view created within built structures. Furthermore, limited visual access to the larger surrounding environment (either outdoor or indoors) could be potentially troublesome (Goldberg et al., 2008). This might suggest that outdoor landmarks are advantageous for navigation due to their visibility from several locations and greater distances, thus providing a reference for a variety of routes (Giudice et al., 2010). However, the constrained nature of indoor spaces and the visual framing that can support landmark storage and recall, could provide additional information for recording landmark location, as long as connection to the larger surrounding environment is available or possible. Landmarks are particularly important for orientation tasks as they are the basis of route knowledge and more complex survey knowledge (Belingard & Peruch, 2000). If individuals must rely on a high number of local landmarks indoors, presumably it would be difficult to build a survey map requiring greater use of route knowledge on the navigator’s part.
Montello, 2006; Montello & Pick, 1993). To date, spatial cognitive microgenesis has been studied primarily in two-dimensional spaces. Only a few studies have utilized the large-scale three-dimensional spaces in researching orientation and wayfinding that will be used in the present study (Montello & Pick, 1993). 1.2. Cognitive mapping Landmark, route, and survey knowledge are acquired via the process of cognitive mapping (Ishikawa & Montello, 2006). Cognitive maps refer to a global representation of space which we create through experience, learning, and problem solving (Goldberg et al., 2008). Spatial information and relationships are stored, recalled, and decoded via cognitive mapping (Montello & Sas, 2006). This phenomenon is an essential tool utilized in our daily life to solve both simple and complex spatial tasks, with new information being constantly acquired and integrated into the knowledge already held within our cognitive map (Ishikawa & Montello, 2006; Montello, 1998). Cognitive mapping is a component of spatial cognition which refers more generally to our internal structuring of space. It is not thought to rely on any one sensory modality more than others, and thus draws upon all of them (Golledge & Stimson, 1997). Experience and meaning must also be taken into account when discussing the development of cognitive maps. Each play an integral role in how information about an environment is acquired, stored, and recalled (Bell, 2002). As well, the way in which spatial information is encoded and subsequently represented and stored in our cognitive map does not appear to depend on the size of a space. Both large and small-scale spaces have been studied by RoskosEwoldsen, McNamara, Shelton, and Carr (1998) providing evidence that both spaces are coded using the same methods (Bell, 2002). Increasing our knowledge of how individuals process and understand spatial knowledge enables us to further predict and explain human behavior as well as ensure that planning and policymaking reflects the needs of the population (Montello, 2009).
1.1. Theoretical framework 1.3. Indoor vs. outdoor To understand the differences in navigation and wayfinding ability, researchers have turned to the theoretical framework of spatial cognitive microgenesis, which is introduced by Siegel and White (1975), comprised of landmarks, route, and subsequent survey knowledge (Griffin, MacEachren, Hardisty, Steiner, & Li, 2006). According to spatial cognitive microgenesis, knowledge progresses from landmark knowledge to route knowledge, and ends in survey knowledge. Survey knowledge is a mental representation of space including both distance and directional relationships among landmarks (Griffin et al., 2006; Ishikawa & Montello, 2006; Montello & Pick, 1993). Route knowledge refers to the connections between landmarks and the knowledge required to get from one landmark to the next. Distance and direction are not necessarily encompassed in this form of knowledge (Ishikawa & Montello, 2006; Montello & Pick, 1993). Survey knowledge builds on landmark and route information and has been shown to create a cognitive representation of space that supports shortcutting and accurate pointing to distant unseen landmarks. This is generally assumed to be possible because the representations include both metric and non-metric elements. Unlike route knowledge, survey knowledge is thought to be metric, with distance and direction being accounted for, even on routes which have not been previously traveled (Ishikawa & Montello, 2006). Survey knowledge is responsible for our ability to take shortcuts, plan efficient routes, and point accurately to landmarks in the environment (Ishikawa & Montello, 2006; Montello & Pick, 1993). In essence, survey knowledge is a compilation of all previously learned routes and the intervening spaces which are subsequently combined and integrated into a series of mentally accessible routes (Ishikawa &
It has been found to be more difficult to build cognitive maps for indoor versus outdoor locations. When discussing cognitive maps, outdoor spaces are typically referred to and thought of in either two, or two and a half dimensions (position and elevation). On the other hand, indoor locations have multiple floors and require cognitive maps to be thought of in three dimensions (Goldberg et al., 2008). In support of the concept that developing cognitive maps for indoor locations is more difficult, a number of studies have suggested that the complexity of a floor plan is the primary influence on wayfinding performance and is thus a main reason for the increased difficulty of navigating indoors. Moeser (1988) found that 56% of the variance in individual ability in wayfinding was explained by floor plan complexity, whereas experience with the floor plan of a building only accounted for 9%. According to Golledge and Stimson (1997), floor plans cannot be mentally represented until the building has been travelled repeatedly. Further, studies have provided evidence that individual spatial learning for the orientation of different sections of a building or interior rooms relative to outdoor environments is especially difficult. This holds true even after an individual has had continuous experience navigating the environment for several years (Wang & Brockmole, 2003a). 1.4. Potential contributions There are several contributions that could be made by better understanding how spatial knowledge varies regarding indoor spaces, outdoor spaces, and their confluence. Floor plan
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development and spatial layout has long been studied within urban planning and architecture. Despite this, little has been explored regarding how individuals, especially those with cognitive impairments, wayfind in large complex spaces. Strategies currently in place to aid individuals with cognitive impairments are extremely labor intensive (Ward et al., 2005). An inability to navigate effectively due to cognitive impairments has been found to affect employment rates, prevent access to appropriate community services, and increase social isolation (Ward et al., 2005). Increasing our understanding of spatial knowledge might provide needed insight into how to create better navigation strategies for those with cognitive impairments. Navigation and wayfinding for individuals with visual impairments is another critical and longstanding area of research, both to inform the literature and to better support the blind community. Research in this area has a significant impact on the social, economic, and emotional importance of individual travel (Montello & Sas, 2006). Implications of this research are important as we move towards a reality that provides positioning and navigation support in both outdoor and indoor settings. Understanding our internal mental representation of space (or cognitive map) and how it adapts to experience and map use is essential to understanding the role maps play in human navigation (Bell & Saucier, 2004; Hegarty, Richardson, Montello, Lovelace, & Subbiah, 2002). 1.5. Pointing accuracy The present study aims to reveal if individuals represent and point with different accuracy to locations inside buildings (rooms, offices, and other destinations) versus locations outdoors (typically main entrances). This will be examined by controlling for the location from which pointing is performed (either indoors or outdoors) as well as varying the location to which they are pointing (indoor or outdoor). The main method used in determining any differences in accuracy between indoor and outdoor locations will be pointing tasks. These tasks require participants to point to unseen locations. Pointing accuracy is often used as a measure of environmental orientation (Bell & Saucier, 2004; Hegarty et al., 2002). Based on research regarding landmarks, layout complexity, and the differences in visual accessibility between indoor and outdoor locations, one would expect individuals to exhibit more accuracy in pointing towards outdoor, rather than indoor locations. Indoors, there is some likelihood that individuals may become disoriented. While the spatial relationships between locations may remain intact, orientation of oneself within the building may be compromised. The main premise is that there is greater availability of visual cues outdoors during the microgenesis of the cognitive map, during experience, thus an individual’s ability to contextualize a discrete landmark in their cognitive map is greater. However, one could counter that since indoor spaces are more complex we pay more attention to our surroundings and develop a more comprehensive cognitive map. Furthermore, when calling up a landmark or location in one’s cognitive map, the constrained nature of indoor spaces might provide a frame or targeting apparatus for point. Because indoor environments are nested (sub-environments nested within gradually larger scale environments), more effort may be required in order to create a mental spatial representation and recall indoor locations (Wang & Brockmole, 2003a). From this logic, one must first recall the largest available environment and work through each nested environment while becoming increasingly more precise in pointing accuracy. Thus, individuals may very well point more accurately to indoor locations. A second facet of this research is to confirm that survey and route strategy affect performance on navigation; to this end, a survey will be included. This survey will determine what type of
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navigation strategy is most dominantly used by each participant (Lawton, 1996). Research on wayfinding has revealed that there are two main navigational strategies utilized by individuals. The first is landmark-based and requires the use of both internal and external memory to recognize features and places, and is referred to as route strategy (Montello & Sas, 2006). The survey strategy is referred to as the dead-reckoning process and includes monitoring components of movement, such as velocity or acceleration, during travel (for example, noting time between landmarks during travel) (Montello & Sas, 2006). According to a research examining wayfinding performance with the aid of guide signs and you-are-here maps, females tend to use route strategy while males prefer survey strategy (Chen, Chang, & Chang, 2009). Prestopnik and Roskos-Ewoldsen (2000) found that wayfinding ability could be predicted through individual use of a survey strategy in a study requiring participants to point to unseen targets. In contrast, no effect was found between route strategy and pointing tasks. Route strategies often rely on landmarks and have a local focus, whereas survey or orientation strategies utilize an overall cognitive map of the environment in which knowledge of places and the relations among them are already integrated. As well, these survey and orientation strategies tend towards a more global focus which reduces error when changing direction as orientation does not seem to affect the cognitive map (Prestopnik & Roskos-Ewoldsen, 2000). Strategy type was determined via distribution of a survey comprised of statements representing either survey or route strategies. A combination of statements from Prestopnik and Roskos-Ewoldsen (2000), Lawton (1996) as well as Kato and Takeuchi (2003) was used in the present study to ensure the navigational strategy survey gathered information for both indoor and outdoor locations as well as any differences that may exist in strategy between the two locations. Navigational strategy was also compared with pointing error to determine whether the type of navigational strategy used influences pointing accuracy. Based on the literature, we expect to see greater pointing accuracy for survey navigators regardless of whether an individual is pointing to, or from, indoor or outdoor locations. Furthermore, individuals with higher accuracy overall will tend to utilize more complex navigational strategies that go beyond recognizing landmarks. A gender difference is also expected, as past research illustrates that women tend to use nearby landmarks rather than distant landmarks as compared to men (Kindig & Movassaghi, 1989). Another sex difference worth noting is the variation in styles of orientating oneself in the environment. When performing navigational tasks, men show a strong preference for orientation strategies such as cardinal directions (north, south, east, and west), spatial configuration, and distance concepts. Females on the other hand, utilize landmarks along with relative directions when navigating (Zimmerman & Li, 2010). As a result, men show superior performance on orientation tasks in both familiar and unfamiliar environments (Iachini, Ruotolo, & Ruggiero, 2009). These strategies of orientation have also been linked to spatial perception abilities (Schootman et al., 2007). As part of our study, we will look at these sex differences for pointing tasks and spatial tasks to reveal any significant differences. 1.6. Spatial ability In order to more fully understand the cognitive processes involved in pointing accuracy, mental rotation will be analyzed (Bagheri, Benwell, & Holt, 2005; Korda, Butler, Clements, & Kunitz, 2007; Zhan, Brender, De Lima, Suarez, & Langlois, 2006). Mental rotation is utilized to measure individual spatial ability. The task is comprised of pairs of three-dimensional geometric figures. These pairs can be identical, mirrored, or have one figure within the pair rotated between zero degrees and 180 . The subject’s task is to
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indicate whether the pairs are the same or different (Korda et al., 2007; Zhan et al., 2006). Sex differences within this measure have been studied extensively, with males showing a strong advantage in mental rotation ability. This finding appears to be generalizable to different ethnic groups as well as to various countries (Zimmerman & Li, 2010). 2. Method An experiment was conducted utilizing the software application SaskEXP designed for the iPad. Within the application, mental rotation and pointing accuracy tasks were completed along with two paper surveys to determine individual differences in ability to point to indoor vs. outdoor locations. 2.1. Participants Eighty volunteers from the University of Saskatchewan participated in the study; each received two credits towards their first year psychology course for their participation. There were forty four women and thirty six men with an average age of 20.9 (SD ¼ 3.45). All recruitment was done via the University of Saskatchewan Sona System. 2.2. Apparatus Instructions and stimuli for mental rotation and pointing tasks appeared within the iPad application, SaskEXP, on an iPad 2. SaskEXP measured response time for mental rotation to 0.000001 s. 2.3. Stimuli and design A single experiment was designed with three distinct sections. The first section was comprised of the psychometric mental rotation task, presented within the iPad application. This task replicated Shepard and Metlzer’s (1971) original stimuli. Section two consisted of an indoor versus outdoor strategy scale. The Indoor vs. Outdoor Strategy Scale is an adaptation of three different scales designed and validated by Prestopnik and Roskos-Ewoldsen (2000), Lawton (1996), and Kato and Takeuchi (2003). These scales were combined and minimally altered to incorporate questions on navigational strategies for both indoor and outdoor locations. An example stimulus is “I always keep in mind which direction I am moving (e.g. north, south, east, west) a) inside buildings and b) outdoors.” Refer to the Appendix for a complete list of stimuli. Section three included pointing tasks and a knowledge-check survey. Pointing tasks were presented on the iPad at four discrete locations (origins) on the university campus; two were outdoor locations and two were indoor locations. Each origin location included six indoor and six outdoor targets, all of which were occluded from view. It was found that to achieve an acceptable level of accuracy indoors, the application needed to complete at least two tasks before achieving five to ten meter accuracy. Because of this, three additional stimuli were included at the beginning of indoor origin tasks. Participants were informed that the initial three tasks of both indoor origins would not be included in the analysis, and were used to ensure that participants understood the procedure for what to do when you are unfamiliar with one of the stimuli (rate as having no confidence). Each origin point was tested to ensure that the order of target presentation reduced overlap in the direction of pointing, as well as dispersing the targets as equally around the origin location as possible. The iPad interface for pointing tasks was designed so that a prominent arrow remains continually on the screen, pointing to the top of the device. A circular compass surrounds the arrow and
moves during testing in the intended direction. Within the compass circle and on top of the arrow are directions on where to point, an example stimulus would be “point to the front entrance of the cancer center.” A Start button is located near the bottom of the screen, with a Submit button replacing it once pressed. For an example of the SaskEXP pointing task interface, refer to Fig. 1. To increase accuracy of our results, SaskEXP was calibrated to ensure that the recording of pointing tasks would occur only if GPS accuracy was ten meters or lower (meaning that the origin location was being recorded in the same place/location used to design the study). Following completion of each pointing estimation, a pop-up window appeared with instructions for the participant to rate his/ her confidence of pointing accuracy for each task. Five different ratings were available from “very confident” to “not at all confident.” The follow-up survey used a Likert-scale from one to seven in order to collect the participant’s knowledge of the forty-eight targets pointed to during testing. 2.4. Procedures Demographic information was obtained for each participant, including information about their age, gender, year in university, and how many years they had resided in Saskatoon, Saskatchewan (the location of the University of Saskatchewan). Information gathered from the demographics form allowed us to analyze sex differences in our tasks, as well as identify participant familiarity with the targets used during the pointing tasks. The participant completed the first two tasks, mental rotation and the Indoor vs. Outdoor Strategy Scale, in a quiet room. All instructions were provided within SaskEXP and at the top of the survey paper. In addition, the researcher was always available for clarification. As there is no evidence that presentation order, either presenting tasks before or after the pointing experiments is statistically significant, the task order
Fig. 1. iPad interface screenshot showing the arrow and compass utilized during the pointing tasks. Accuracy, measured in meters, is displayed at the top of the screen. A compass ring is utilized for the purpose of allowing the participant to recognize when the iPad is updating their location indicated by the movement of the ring.
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was not randomized (Hegarty et al., 2002). Next, participants were taken to four locations (origins) across campus and were asked to point to various other locations on campus (targets) (none of the origins were used as targets and vice versa). After each pointing task, participants rated their confidence in their estimate. It is important to note that while confidence and campus knowledge were generally rated medium to high by all participants most of the time, there was a distinct pattern. The majority of the least confident ratings were for locations in the university’s engineering building, for participants rating these targets as low (confidence or knowledge) they were removed from analysis (just the data for those specific targets). This was less than 5% of the data. Origin locations were balanced by alternating between indoor and outdoor origins. Participants began at an indoor origin, moving to an outdoor origin then to the next indoor origin and ending at the last outdoor origin. A total of forty-eight locations were pointed to: six indoor targets and six outdoor targets (excluding the additional three added to the indoor origins) at each origin location. An equal number of indoor and outdoor targets were assigned to each origin. The targets were randomly organized and the type of target was unidentified to the participant. At no point during the study were participants informed of their performance. 3. Results 3.1. Indoor vs. outdoor targets The dependent variable in this experiment was pointing error, measured in degrees. We recorded pointing error for every target location. The experiment was a 2 2 repeated measures analysis of variance (ANOVA) with factors Origin (indoor vs. outdoor) and Target (indoor vs. outdoor). Refer to Fig. 2 for the four cell analysis of pointing error for Origin Target. There was a main effect of Origin on pointing error between indoor (66.37) and outdoor (45.47) locations, F(1,205) ¼ 39.38, MSE ¼ 201,965.81, p ¼ .000. There was also a main effect of Target on pointing error between indoor (50.53) and outdoor (61.31) locations, F(1,205) ¼ 10.48, MSE ¼ 53,763.30, p ¼ .001. There was no interaction of Origin and Target type, F(1,205) ¼ .20, MSE ¼ 1024.81, p ¼ .66. Effect size for the interaction was small, thus we would have needed much greater power to observe an effect. 3.2. Individual differences
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Fig. 2. Mean pointing accuracy for indoor and outdoor origins between indoor and outdoor targets. Error bars in the figure represent standard error for each column.
the correlation remained stronger for survey strategy. Individual ttests were run to determine any significant gender differences in navigation strategy. A significant difference was present between male (26.18) and female (32.10) participants in outdoor route strategy (higher scores indicate greater preference for that strategy), t(77) ¼ 2.24, p < .05, as well as between male (18.68) and female (22.72) participants in indoor route strategy t(77) ¼ 2.27, p < .05. tTests did not reveal any significant differences in participant pointing ability for indoor or outdoor survey strategies between sexes, t(78) ¼ 1.09, p ¼ .28 and t(78) ¼ .036, p ¼ .97 respectively. 4. Discussion Based on our hypotheses, pointing accuracy was expected to be more accurate for outdoor origins when compared to indoor origins. Two contrasting hypotheses were presented for pointing accuracy regarding targets (Section 1.5, above). Depending on the logic followed, participants could display more accurate pointing accuracy for either indoor or outdoor targets. These hypotheses were based on evidence regarding the effects that landmarks, visual access, and layout complexity may have on one’s ability to
Correlations were used to analyze any significant differences between mental rotation and pointing accuracy. To analyze mental rotation, an average response time for each individual was used along with the number of correctly answered responses. Pointing error and mental rotation were negatively correlated such that as pointing error decreased, mental rotation ability increased, r(78) ¼ .298, p < .01. As well, individual t-tests illustrated a significant difference between male (.81) and female (.72) participants in the mental rotation spatial task, t(78) ¼ 2.36, p < .05. 3.3. Route vs. survey strategy Indoor and outdoor navigation strategy was tested against pointing error to reveal any significant relationships between strategy and pointing accuracy. For this, navigation strategy type was divided into route and survey. Average responses were calculated between route and survey strategy for both indoor and outdoor locations. Refer to Table 1 for the Pearson r correlation coefficients between pointing error, gender, and navigation strategy. Pointing error was found to be positively correlated with survey and route strategy when individuals were both indoors and outdoors; however,
Fig. 3. Average distance to targets and origins. Error bars in the figure represent standard error for each column.
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Table 1 Pearson correlations among pointing error and navigational strategy. Measure
Pointing error Outdoors e survey strategy Outdoors e route strategy Indoors e survey strategy Indoors e route strategy
Pointing Outdoors e Outdoors e Indoors e Indoors e error survey route survey route strategy strategy strategy strategy
.733** .523**
.382**
.784**
.656**
.479**
.471**
.347**
.717**
.384**
*p < .05, **p < .001.
develop a cognitive map for varying environments (Montello & Sas, 2006). As suggested in the previous research, utilizing global over local landmarks one can reduce the traveling distance in terms of searching for targets in a grid-like environment (Lin et al., 2012). Based on the definition of the two types of landmarks, the global landmarks are distant from the observer while the local ones are relatively closer (Steck & Mallot, 2000). In this case, it is not surprising that participants perform better when pointing from outdoor origins, because there are apparently a larger number of global landmarks outdoors than indoors which supports orientation. While pointing from indoor origins, where the space is much limited, participants have less visual access to determine their location and orientation. They were also based on whether or not nested environments play a role in the level of precision utilized during wayfinding. It is possible that utilizing the nested structure for direction support from outdoors (pointing from outdoor origins) is easier than indoors (pointing from indoor origins) as buildings are built as part of the campus environment (Wang & Brockmole, 2003b). In support of our first hypotheses, origin was found to influence pointing accuracy with individuals pointing more accurately from outdoor origins. For targets, individual pointing accuracy was more accurate for indoor locations when compared to outdoor locations. t-Test results suggest that the average distance to indoor targets is smaller than that to outdoor targets (t(46) ¼ 2.50, p < .05), while there is no significant difference between the average distance from indoor origins and outdoor origins (t(46) ¼ 1.19, p ¼ .24) as shown in Fig. 3. As to more accurate pointing TO indoor locations, we believe the strongest explanation is twofold: 1. the increased attention necessary
during microgenesis for the greater complexity of indoor spaces (multiple levels, constrained visual field, etc.) and 2. When calling up indoor locations from our cognitive map, the immediate surrounding are likely to be more closely spaced, resulting in the potential for a pointing frame or targeting apparatus that might improve our ability to point to discrete objects. Furthermore, with outdoor locations, they were (and are) often attached to larger buildings, therefore, if accurate storage of such landmarks is not as critical, because they are attached to a building, perhaps participants were pointing to the building. Both of these latter explanations suggest that it might not be the accuracy of the cognitive map for such locations (indoor vs. outdoor) but the extent to which their character supports or inhibits accurate pointing. Our second hypothesis was that individual differences in mental rotation as well as strategy type (as measured by the Indoor and Outdoor Strategy Scale) would affect pointing accuracy while illustrating significant differences between male and female performance. As expected, mental rotation ability predicted pointing accuracy. The gender differences reported in favor of men for mental rotation were again confirmed in our study (Zimmerman & Li, 2010). Results from this study confirm that individual differences are related to our navigational abilities and strategies. One explanation that could account for increased pointing accuracy from outdoor origins is orientation. It was noted by the researchers that participants often expressed feelings of being turned around during indoor origin pointing tasks. To explore this, participants’ average pointing error was analyzed individually. The standard deviation appeared to remain quite small, thus we plotted several individuals’ pointing accuracy for one indoor origin. Next, we subtracted the average error to see whether participants’ spatial relationships remained intact between target locations. This subtraction represents their consistency across target error; we believe this is a reasonable proxy for overall or baseline disorientation (bias). Once the average error was accounted for it becomes apparent that the individual’s orientation was simply in the wrong direction and a greater clustering of pointing accuracy is seen. As shown in Fig. 4, participants did appear to recognize the spatial relationships between target locations while indoors. While our experiment was not designed to statistically analyze these relationships, there is some empirical evidence in the literature. Wang and Brockmole (2003a) found that although many individuals were incorrect in determining their own positions within an environment relative to targets, they displayed relatively consistent accuracy and knowledge of the relationships between targets.
Fig. 4. Mean pointing accuracy for one participant at an indoor origin point. On the left side is their original pointing accuracy. The right side illustrates how their pointing accuracy changes when you remove error due to the participant’s incorrect mental orientation within the building. Dark bars indicate the actual target locations (see the black arrows).
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To better explain individuals’ increased accuracy in pointing towards indoor targets, characteristics of indoor environments were reconsidered. One possible limitation to this study, as well as a potential confound, is the design of the University of Saskatchewan campus. While the majority of spaces we navigate are orthogonally aligned (typically in grid-like patterns), most of the campus is designed in an oval shape around a central “bowl.” A grid-like pattern only occurs on campus for indoor environments. As Giudice et al. (2010) notes, one advantage of indoor spaces is that they typically display more regular geometrics when compared to outdoor environments. It would be interesting in future research to explore how the different complexities of the environments used in this study affect wayfinding ability. The difference in navigation ability between indoor and outdoor environments should be applied within the domain of spatial cognitive research. Research in this area could aid in the identification of techniques to produce building floor plans which allow for successful navigation for both visitors and individuals who frequently wayfind within the building. The type of landmarks used indoors, the availability of differing colors and shapes within a building’s design, and the intention to improve visual accessibility and reduce layout complexity could all aid in the improvement of indoor wayfinding. The extent to which the information researchers have gathered for outdoor environments is still applicable within buildings as well as within built environments, where navigation between indoor and outdoor environments is required, should also be addressed. While all navigational strategies predicted pointing accuracy, correlations remained stronger for survey strategy. This adds support for cognitive spatial microgenesis, as survey strategy is thought to be the most complex and advanced form of navigation (Ishikawa & Montello, 2006; Montello & Pick, 1993). There were also sex differences in route strategy use, illustrating that women were more likely to rely on route strategy compared to men. This supports the current literature and findings that women have a tendency to navigate based on landmarks, whereas men prefer orientation and survey navigational strategies (Kindig & Movassaghi, 1989). It is also worth noting that there were no significant differences found between navigation strategies employed indoors versus outdoors. Subsequently, it does not provide us with any additional insight into any navigational ability differences that exist between indoor and outdoor locations. Support for the theoretical framework of spatial microgenesis is further provided from these results, as the theory stipulates that the availability of landmarks (utilized for the subsequent creation of route and survey knowledge) has an effect on one’s ability to navigate (Griffin et al., 2006). While our results do not indicate what aspects of indoor and outdoor locations are creating the observed differences, they do indicate the presence of differences that need to be further explored. In particular the greatest accuracy (as a category of pointing) was pointing from outdoor origins to indoor locations. One “grand” hypothesis might be that combination and order present a daunting transition during navigation and that accurate orientation of outdoor spaces with indoor destinations is important to minimizing stress and maximizing successful movement through space. As well, because the survey navigation strategy was more predictive of pointing accuracy than route strategy, we confirm that route knowledge develops before survey knowledge and that survey knowledge represents a more complete ‘map-like’ representation of space (Griffin et al., 2006; Ishikawa & Montello, 2006; Montello & Pick, 1993). Based on the results of the present study, it appears that navigation is most difficult within the built environment, thus adding to the importance of developing effective navigational tools for indoor environments. Currently, integration between outdoor and indoor
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spatial information systems is lacking. Research has primarily focused on navigation outdoors, however individuals are increasingly tending to spend the majority of their time indoors (Goldberg et al., 2008). Also of interest is the lack of a universally used technology for indoor navigation, such as GPS to aid in wayfinding (Goldberg, 2008). Our results can aid in the exploration of differences in individual cognitive mapping of both indoor and outdoor spaces, and how these differences can subsequently be applied to the design of maps, wayfinding material (such as indoor signage) and GPS devices. As well, further research could look at the factors influencing individuals with cognitive and visual impairments. The strategies used for navigating and wayfinding may be altered to accommodate the specific impairments of those individuals affected. Individuals with visual impairments would naturally rely less on their visual sense compared to the average individual. What factors within our environment can be adjusted to increase the ease of wayfinding for these individuals? As well, what differences present themselves cognitively in individuals with cognitive impairments? Do individuals with this impairment utilize the same navigational strategies as the general population? Are some factors, such as landmarks, more important in effective wayfinding? One potential limitation of this study is the population sample utilized. Individuals in first year psychology courses may not be as familiar with the campus, and subsequently the target locations used for this study. As well, this sample represents a particular subset of the population. It would be interesting to explore pointing accuracy and individual differences within professions typically thought to have high levels of spatial skills (such as engineers or architects) in comparison to a control group (a profession which typically does not rely on well-developed spatial skills). As well, the sample used in this study does not vary significantly in age. It may be interesting to investigate how navigational ability changes over time, or between the young and old. Another possible limitation within this study is the design of the University of Saskatchewan campus, as mentioned previously. 5. Conclusions and implications The results from this study confirm the importance of further research in the area of spatial cognition within indoor environments. The increased accuracy in pointing towards indoor locations suggests that these locations were stored in cognitive maps with more accuracy, that they were recalled with more precision, or that there are aspects of how we store information about indoor locations that allows for more consistent recall of location. Greater care may be taken when pointing to indoor locations if more attention is required. This may result in increased precision, and we could conclude that similar to our hypothesis, more processing is required when pointing to indoor locations. In contrast, Prestopnik and Roskos-Ewoldsen (2000) stipulate that outdoor spaces may actually be more difficult for apprehension due to the increased amount of information required for analysis outdoors. Individuals need to recall street names, their locations, as well as their relation to other streets along with the layout of buildings and their orientation in relation to street patterns. More research will be required in order to understand more fully the cognitive processes occurring between indoor and outdoor orientation and navigation. Acknowledgments This study was conducted in the SAPHIR lab funded by the Canada Foundation for Innovation. We would like to extend our thanks to the students who helped throughout the research process
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Appendix. Indoor and Outdoor Strategy Scale
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including Lauren Arnold, Lindsay Aspen, Craig Siemens, Kumaran Vijayan, and Anton Sizo.
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R. G. Golledge (Eds.), Spatial and temporal reasoning in geographic information systems (pp. 143e154). New York: Oxford University Press. Montello, D. R. (2007). The contribution of space syntax to a comprehensive theory of environmental psychology. Paper presented at the 6th International Space Syntax Symposium, Istanbul, Turkey. Montello, D. R. (2009). A conceptual model of the cognitive processing of environmental distance information. In K. Hornsby, C. Claramunt, M. Denis, & G. Ligozat (Eds.), Spatial information theory (Vol. 5756); (pp. 1e17). Berlin Heidelberg: Springer. Montello, D. R., & Pick, H. L. (1993). Integrating knowledge of vertically aligned large-scale spaces. Environment and Behavior, 25(3), 457e484. Montello, D. R., & Sas, C. (2006). Human factors of wayfinding in navigation. In W. Karwowski (Ed.), International encyclopedia of ergonomics and human factors (pp. 2003e2008). CRC Press/Taylor & Francis, Ltd. Moeser, S. D. (1988). Cognitive mapping in a complex building. Environment and Behavior, 20(1), 21e49. Prestopnik, J. L., & Roskos-Ewoldsen, B. (2000). The relations among wayfinding strategy use, sense of direction, sex, familiarity, and wayfinding ability. Journal of Environmental Psychology, 20(2), 177e191. Roskos-Ewoldsen, B., McNamara, T. P., Shelton, A. L., & Carr, W. (1998). Mental representations of large and small spatial layouts are orientation dependent. Journal of Experimental Psychology: Learning, Memory, & Cognition, 24(1), 215e 226. Schootman, M., Sterling, D. A., Struthers, J., Yan, Y., Laboube, T., Emo, B., et al. (2007). Positional accuracy and geographic bias of four methods of geocoding in epidemiologic research. Annals of Epidemiology, 17(6), 464e470. http:// dx.doi.org/10.1016/j.annepidem.2006.10.015. Shepard, R. N., & Metzler, J. (1971). Mental rotation of three-dimensional objects. Science, 171(3972), 701e703. Siegel, A. W., & White, S. H. (1975). The development of spatial representations of large-scale environments. In W. R. Hayne (Ed.), Advances in child development and behavior (Vol. 10); (pp. 9e55). JAI. Steck, S. D., & Mallot, H. A. (2000). The role of global and local landmarks in virtual environment navigation. Presence: Teleoperators and Virtual Environments, 9(1), 69e83. http://dx.doi.org/10.1162/105474600566628. Wang, R. F., & Brockmole, J. R. (2003a). Human navigation in nested environments. Journal of Experimental Psychology: Learning, Memory, and Cognition, 29(3), 398e 404. Wang, R. F., & Brockmole, J. R. (2003b). Simultaneous spatial updating in nested environments. Psychonomic Bulletin & Review, 10(4), 981e986. Ward, M. H., Nuckols, J. R., Giglierano, J., Bonner, M. R., Wolter, C., Airola, M., et al. (2005). Positional accuracy of two methods of geocoding. Epidemiology, 16(4), 542e547. http://dx.doi.org/10.1097/01.ede.0000165364.54925.f3. Zhan, F. B., Brender, J. D., De Lima, I., Suarez, L., & Langlois, P. H. (2006). Match rate and positional accuracy of two geocoding methods for epidemiologic research. Annals of Epidemiology, 16(11), 842e849. http://dx.doi.org/10.1016/ j.annepidem.2006.08.001. Zimmerman, D., & Li, J. (2010). The effects of local street network characteristics on the positional accuracy of automated geocoding for geographic health studies. International Journal of Health Geographics, 9(1), 1e11. http://dx.doi.org/10.1186/ 1476-072x-9-10.
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Journal of Environmental Psychology journal homepage: www.elsevier.com/locate/jep
Pointing accuracy: Does individual pointing accuracy differ for indoor vs. outdoor locations? Pamela L.J. Berry*, Scott Bell University of Saskatchewan, 105 Administration Place, Saskatoon, SK S7N 5A2, Canada
a r t i c l e i n f o
a b s t r a c t
Article history: Available online 7 February 2014
Pointing accuracy to and from indoor and outdoor locations was examined to reveal any significant differences in the accuracy with which we recall the arrangement of unseen locations in the world around us. Spatial ability and navigational strategy were included to better understand the cognitive processes involved in pointing accuracy and subsequent environmental knowledge. Results from this study indicate that knowledge for indoor and outdoor environments is indeed different. Individual pointing is more accurate to landmarks and locations that are inside buildings than to those outside, whether or not they point from an indoor or outdoor origin. As well, the preference for configurational and somewhat more complex navigational strategies, as expressed through questionnaire results, is positively correlated with increased pointing accuracy. Ó 2014 Elsevier Ltd. All rights reserved.
Keywords: Spatial cognitive microgenesis Pointing error Spatial ability Navigation
1. Introduction We have all experienced navigational difficulties requiring maps, GPS, or other individuals at one time or another. Often these difficulties tend to arise in specific environments that vary for individuals. Some may be uncomfortable driving in a new city, while others may find it difficult to navigate in a complex building with many functions and floor levels. What is it about these differing environments that affect our ability to navigate efficiently? Studies have shown that despite becoming familiar with certain environments (such as the workplace), the navigational difficulties an individual first experiences can continue for years (Wang & Brockmole, 2003a). These difficulties may cause decreased safety, stress, discomfort, and loss of time. In extreme cases, getting lost in isolated environments can be life-threatening (Montello & Sas, 2006). Despite scientific evidence that the nature of an environment can impact how we learn and move through it, the majority of research relies on a common and relatively narrow set of principles of spatial knowledge acquisition and use. To remedy these issues, it is important to understand how navigation is affected by elements within and associated with the built environment. There are a variety of characteristics within our environment, both visual and structural, that support navigation. Effective navigation is defined by Montello and Sas (2006) as requiring individuals to apply psychological skills such as perception and * Corresponding author. Tel.: þ1 306 261 0460. E-mail addresses: [email protected], [email protected] J. Berry), [email protected] (S. Bell). http://dx.doi.org/10.1016/j.jenvp.2014.01.007 0272-4944/Ó 2014 Elsevier Ltd. All rights reserved.
(P.L.
cognition in conjunction with motor behaviors. Goal directed use of knowledge, cognitive processes, and locomotion to travel from one location to the next is referred to as wayfinding (Montello & Sas, 2006). An important factor in wayfinding is orientation. For wayfinding to be effective, one must be aware of their position in relation to other places, destinations, and objects. Precision is often not required in orientation, as effective navigation can occur even when one’s orientation is coarse or partial (Montello & Sas, 2006). The availability of information during wayfinding differs among environments. Factors affecting these differences include differentiation (ability to distinguish between within environment elements), visual access, and layout complexity (Montello, 2007). Differentiation is characterized by variation in size, shape, and color of items; in the case of built environments; differences in architectural style tend to aid navigation. While increased within environment differentiation typically aids navigation, too much can be disorienting (Montello & Sas, 2006). Both differentiation and visual access affect landmark effectiveness during navigation. As well, the type and availability of landmarks is thought to affect navigational success (Goldberg, 2008). Outdoor landmarks tend to consist of large, highly visible objects such as buildings, while indoor landmarks tend to be smaller objects, such as lobbies, paintings, and other features (Giudice, Walton, & Worboys, 2010). Layout complexity is the final environmental factor that is thought to affect wayfinding. This factor is difficult to define, as complexity is dependent on individual abilities to visually and cognitively organize complex environments. If patterns and effective organization are apparent to the navigating individual, complex environments become much easier to understand and navigate (Montello & Sas, 2006).
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Differences between environments that might affect wayfinding or spatial knowledge acquisition have not been studied extensively within the spatial cognitive domain. Specifically, studies have yet to analyze any differences in our ability to locate and use indoor versus outdoor locations. As indoor spaces are considered more challenging for apprehension and learning, it would be useful to empirically test this logic (Goldberg, Wilson, Knoblock, Ritz, & Cockburn, 2008). One apparent difference between indoor and outdoor environments is the availability of landmarks. As noted above, landmarks utilized for indoor navigation tend to differ greatly in both availability and type from landmarks associated with outdoor locations. As well, the field of view available to an individual in each environment differs greatly with respect to the number of landmarks for building the cognitive maps for the entire surroundings. The distinction between indoor and outdoor environment belies the variation that can be found within either category. Perhaps the most compelling characteristic of indoor spaces is the constrained field of view created within built structures. Furthermore, limited visual access to the larger surrounding environment (either outdoor or indoors) could be potentially troublesome (Goldberg et al., 2008). This might suggest that outdoor landmarks are advantageous for navigation due to their visibility from several locations and greater distances, thus providing a reference for a variety of routes (Giudice et al., 2010). However, the constrained nature of indoor spaces and the visual framing that can support landmark storage and recall, could provide additional information for recording landmark location, as long as connection to the larger surrounding environment is available or possible. Landmarks are particularly important for orientation tasks as they are the basis of route knowledge and more complex survey knowledge (Belingard & Peruch, 2000). If individuals must rely on a high number of local landmarks indoors, presumably it would be difficult to build a survey map requiring greater use of route knowledge on the navigator’s part.
Montello, 2006; Montello & Pick, 1993). To date, spatial cognitive microgenesis has been studied primarily in two-dimensional spaces. Only a few studies have utilized the large-scale three-dimensional spaces in researching orientation and wayfinding that will be used in the present study (Montello & Pick, 1993). 1.2. Cognitive mapping Landmark, route, and survey knowledge are acquired via the process of cognitive mapping (Ishikawa & Montello, 2006). Cognitive maps refer to a global representation of space which we create through experience, learning, and problem solving (Goldberg et al., 2008). Spatial information and relationships are stored, recalled, and decoded via cognitive mapping (Montello & Sas, 2006). This phenomenon is an essential tool utilized in our daily life to solve both simple and complex spatial tasks, with new information being constantly acquired and integrated into the knowledge already held within our cognitive map (Ishikawa & Montello, 2006; Montello, 1998). Cognitive mapping is a component of spatial cognition which refers more generally to our internal structuring of space. It is not thought to rely on any one sensory modality more than others, and thus draws upon all of them (Golledge & Stimson, 1997). Experience and meaning must also be taken into account when discussing the development of cognitive maps. Each play an integral role in how information about an environment is acquired, stored, and recalled (Bell, 2002). As well, the way in which spatial information is encoded and subsequently represented and stored in our cognitive map does not appear to depend on the size of a space. Both large and small-scale spaces have been studied by RoskosEwoldsen, McNamara, Shelton, and Carr (1998) providing evidence that both spaces are coded using the same methods (Bell, 2002). Increasing our knowledge of how individuals process and understand spatial knowledge enables us to further predict and explain human behavior as well as ensure that planning and policymaking reflects the needs of the population (Montello, 2009).
1.1. Theoretical framework 1.3. Indoor vs. outdoor To understand the differences in navigation and wayfinding ability, researchers have turned to the theoretical framework of spatial cognitive microgenesis, which is introduced by Siegel and White (1975), comprised of landmarks, route, and subsequent survey knowledge (Griffin, MacEachren, Hardisty, Steiner, & Li, 2006). According to spatial cognitive microgenesis, knowledge progresses from landmark knowledge to route knowledge, and ends in survey knowledge. Survey knowledge is a mental representation of space including both distance and directional relationships among landmarks (Griffin et al., 2006; Ishikawa & Montello, 2006; Montello & Pick, 1993). Route knowledge refers to the connections between landmarks and the knowledge required to get from one landmark to the next. Distance and direction are not necessarily encompassed in this form of knowledge (Ishikawa & Montello, 2006; Montello & Pick, 1993). Survey knowledge builds on landmark and route information and has been shown to create a cognitive representation of space that supports shortcutting and accurate pointing to distant unseen landmarks. This is generally assumed to be possible because the representations include both metric and non-metric elements. Unlike route knowledge, survey knowledge is thought to be metric, with distance and direction being accounted for, even on routes which have not been previously traveled (Ishikawa & Montello, 2006). Survey knowledge is responsible for our ability to take shortcuts, plan efficient routes, and point accurately to landmarks in the environment (Ishikawa & Montello, 2006; Montello & Pick, 1993). In essence, survey knowledge is a compilation of all previously learned routes and the intervening spaces which are subsequently combined and integrated into a series of mentally accessible routes (Ishikawa &
It has been found to be more difficult to build cognitive maps for indoor versus outdoor locations. When discussing cognitive maps, outdoor spaces are typically referred to and thought of in either two, or two and a half dimensions (position and elevation). On the other hand, indoor locations have multiple floors and require cognitive maps to be thought of in three dimensions (Goldberg et al., 2008). In support of the concept that developing cognitive maps for indoor locations is more difficult, a number of studies have suggested that the complexity of a floor plan is the primary influence on wayfinding performance and is thus a main reason for the increased difficulty of navigating indoors. Moeser (1988) found that 56% of the variance in individual ability in wayfinding was explained by floor plan complexity, whereas experience with the floor plan of a building only accounted for 9%. According to Golledge and Stimson (1997), floor plans cannot be mentally represented until the building has been travelled repeatedly. Further, studies have provided evidence that individual spatial learning for the orientation of different sections of a building or interior rooms relative to outdoor environments is especially difficult. This holds true even after an individual has had continuous experience navigating the environment for several years (Wang & Brockmole, 2003a). 1.4. Potential contributions There are several contributions that could be made by better understanding how spatial knowledge varies regarding indoor spaces, outdoor spaces, and their confluence. Floor plan
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development and spatial layout has long been studied within urban planning and architecture. Despite this, little has been explored regarding how individuals, especially those with cognitive impairments, wayfind in large complex spaces. Strategies currently in place to aid individuals with cognitive impairments are extremely labor intensive (Ward et al., 2005). An inability to navigate effectively due to cognitive impairments has been found to affect employment rates, prevent access to appropriate community services, and increase social isolation (Ward et al., 2005). Increasing our understanding of spatial knowledge might provide needed insight into how to create better navigation strategies for those with cognitive impairments. Navigation and wayfinding for individuals with visual impairments is another critical and longstanding area of research, both to inform the literature and to better support the blind community. Research in this area has a significant impact on the social, economic, and emotional importance of individual travel (Montello & Sas, 2006). Implications of this research are important as we move towards a reality that provides positioning and navigation support in both outdoor and indoor settings. Understanding our internal mental representation of space (or cognitive map) and how it adapts to experience and map use is essential to understanding the role maps play in human navigation (Bell & Saucier, 2004; Hegarty, Richardson, Montello, Lovelace, & Subbiah, 2002). 1.5. Pointing accuracy The present study aims to reveal if individuals represent and point with different accuracy to locations inside buildings (rooms, offices, and other destinations) versus locations outdoors (typically main entrances). This will be examined by controlling for the location from which pointing is performed (either indoors or outdoors) as well as varying the location to which they are pointing (indoor or outdoor). The main method used in determining any differences in accuracy between indoor and outdoor locations will be pointing tasks. These tasks require participants to point to unseen locations. Pointing accuracy is often used as a measure of environmental orientation (Bell & Saucier, 2004; Hegarty et al., 2002). Based on research regarding landmarks, layout complexity, and the differences in visual accessibility between indoor and outdoor locations, one would expect individuals to exhibit more accuracy in pointing towards outdoor, rather than indoor locations. Indoors, there is some likelihood that individuals may become disoriented. While the spatial relationships between locations may remain intact, orientation of oneself within the building may be compromised. The main premise is that there is greater availability of visual cues outdoors during the microgenesis of the cognitive map, during experience, thus an individual’s ability to contextualize a discrete landmark in their cognitive map is greater. However, one could counter that since indoor spaces are more complex we pay more attention to our surroundings and develop a more comprehensive cognitive map. Furthermore, when calling up a landmark or location in one’s cognitive map, the constrained nature of indoor spaces might provide a frame or targeting apparatus for point. Because indoor environments are nested (sub-environments nested within gradually larger scale environments), more effort may be required in order to create a mental spatial representation and recall indoor locations (Wang & Brockmole, 2003a). From this logic, one must first recall the largest available environment and work through each nested environment while becoming increasingly more precise in pointing accuracy. Thus, individuals may very well point more accurately to indoor locations. A second facet of this research is to confirm that survey and route strategy affect performance on navigation; to this end, a survey will be included. This survey will determine what type of
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navigation strategy is most dominantly used by each participant (Lawton, 1996). Research on wayfinding has revealed that there are two main navigational strategies utilized by individuals. The first is landmark-based and requires the use of both internal and external memory to recognize features and places, and is referred to as route strategy (Montello & Sas, 2006). The survey strategy is referred to as the dead-reckoning process and includes monitoring components of movement, such as velocity or acceleration, during travel (for example, noting time between landmarks during travel) (Montello & Sas, 2006). According to a research examining wayfinding performance with the aid of guide signs and you-are-here maps, females tend to use route strategy while males prefer survey strategy (Chen, Chang, & Chang, 2009). Prestopnik and Roskos-Ewoldsen (2000) found that wayfinding ability could be predicted through individual use of a survey strategy in a study requiring participants to point to unseen targets. In contrast, no effect was found between route strategy and pointing tasks. Route strategies often rely on landmarks and have a local focus, whereas survey or orientation strategies utilize an overall cognitive map of the environment in which knowledge of places and the relations among them are already integrated. As well, these survey and orientation strategies tend towards a more global focus which reduces error when changing direction as orientation does not seem to affect the cognitive map (Prestopnik & Roskos-Ewoldsen, 2000). Strategy type was determined via distribution of a survey comprised of statements representing either survey or route strategies. A combination of statements from Prestopnik and Roskos-Ewoldsen (2000), Lawton (1996) as well as Kato and Takeuchi (2003) was used in the present study to ensure the navigational strategy survey gathered information for both indoor and outdoor locations as well as any differences that may exist in strategy between the two locations. Navigational strategy was also compared with pointing error to determine whether the type of navigational strategy used influences pointing accuracy. Based on the literature, we expect to see greater pointing accuracy for survey navigators regardless of whether an individual is pointing to, or from, indoor or outdoor locations. Furthermore, individuals with higher accuracy overall will tend to utilize more complex navigational strategies that go beyond recognizing landmarks. A gender difference is also expected, as past research illustrates that women tend to use nearby landmarks rather than distant landmarks as compared to men (Kindig & Movassaghi, 1989). Another sex difference worth noting is the variation in styles of orientating oneself in the environment. When performing navigational tasks, men show a strong preference for orientation strategies such as cardinal directions (north, south, east, and west), spatial configuration, and distance concepts. Females on the other hand, utilize landmarks along with relative directions when navigating (Zimmerman & Li, 2010). As a result, men show superior performance on orientation tasks in both familiar and unfamiliar environments (Iachini, Ruotolo, & Ruggiero, 2009). These strategies of orientation have also been linked to spatial perception abilities (Schootman et al., 2007). As part of our study, we will look at these sex differences for pointing tasks and spatial tasks to reveal any significant differences. 1.6. Spatial ability In order to more fully understand the cognitive processes involved in pointing accuracy, mental rotation will be analyzed (Bagheri, Benwell, & Holt, 2005; Korda, Butler, Clements, & Kunitz, 2007; Zhan, Brender, De Lima, Suarez, & Langlois, 2006). Mental rotation is utilized to measure individual spatial ability. The task is comprised of pairs of three-dimensional geometric figures. These pairs can be identical, mirrored, or have one figure within the pair rotated between zero degrees and 180 . The subject’s task is to
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indicate whether the pairs are the same or different (Korda et al., 2007; Zhan et al., 2006). Sex differences within this measure have been studied extensively, with males showing a strong advantage in mental rotation ability. This finding appears to be generalizable to different ethnic groups as well as to various countries (Zimmerman & Li, 2010). 2. Method An experiment was conducted utilizing the software application SaskEXP designed for the iPad. Within the application, mental rotation and pointing accuracy tasks were completed along with two paper surveys to determine individual differences in ability to point to indoor vs. outdoor locations. 2.1. Participants Eighty volunteers from the University of Saskatchewan participated in the study; each received two credits towards their first year psychology course for their participation. There were forty four women and thirty six men with an average age of 20.9 (SD ¼ 3.45). All recruitment was done via the University of Saskatchewan Sona System. 2.2. Apparatus Instructions and stimuli for mental rotation and pointing tasks appeared within the iPad application, SaskEXP, on an iPad 2. SaskEXP measured response time for mental rotation to 0.000001 s. 2.3. Stimuli and design A single experiment was designed with three distinct sections. The first section was comprised of the psychometric mental rotation task, presented within the iPad application. This task replicated Shepard and Metlzer’s (1971) original stimuli. Section two consisted of an indoor versus outdoor strategy scale. The Indoor vs. Outdoor Strategy Scale is an adaptation of three different scales designed and validated by Prestopnik and Roskos-Ewoldsen (2000), Lawton (1996), and Kato and Takeuchi (2003). These scales were combined and minimally altered to incorporate questions on navigational strategies for both indoor and outdoor locations. An example stimulus is “I always keep in mind which direction I am moving (e.g. north, south, east, west) a) inside buildings and b) outdoors.” Refer to the Appendix for a complete list of stimuli. Section three included pointing tasks and a knowledge-check survey. Pointing tasks were presented on the iPad at four discrete locations (origins) on the university campus; two were outdoor locations and two were indoor locations. Each origin location included six indoor and six outdoor targets, all of which were occluded from view. It was found that to achieve an acceptable level of accuracy indoors, the application needed to complete at least two tasks before achieving five to ten meter accuracy. Because of this, three additional stimuli were included at the beginning of indoor origin tasks. Participants were informed that the initial three tasks of both indoor origins would not be included in the analysis, and were used to ensure that participants understood the procedure for what to do when you are unfamiliar with one of the stimuli (rate as having no confidence). Each origin point was tested to ensure that the order of target presentation reduced overlap in the direction of pointing, as well as dispersing the targets as equally around the origin location as possible. The iPad interface for pointing tasks was designed so that a prominent arrow remains continually on the screen, pointing to the top of the device. A circular compass surrounds the arrow and
moves during testing in the intended direction. Within the compass circle and on top of the arrow are directions on where to point, an example stimulus would be “point to the front entrance of the cancer center.” A Start button is located near the bottom of the screen, with a Submit button replacing it once pressed. For an example of the SaskEXP pointing task interface, refer to Fig. 1. To increase accuracy of our results, SaskEXP was calibrated to ensure that the recording of pointing tasks would occur only if GPS accuracy was ten meters or lower (meaning that the origin location was being recorded in the same place/location used to design the study). Following completion of each pointing estimation, a pop-up window appeared with instructions for the participant to rate his/ her confidence of pointing accuracy for each task. Five different ratings were available from “very confident” to “not at all confident.” The follow-up survey used a Likert-scale from one to seven in order to collect the participant’s knowledge of the forty-eight targets pointed to during testing. 2.4. Procedures Demographic information was obtained for each participant, including information about their age, gender, year in university, and how many years they had resided in Saskatoon, Saskatchewan (the location of the University of Saskatchewan). Information gathered from the demographics form allowed us to analyze sex differences in our tasks, as well as identify participant familiarity with the targets used during the pointing tasks. The participant completed the first two tasks, mental rotation and the Indoor vs. Outdoor Strategy Scale, in a quiet room. All instructions were provided within SaskEXP and at the top of the survey paper. In addition, the researcher was always available for clarification. As there is no evidence that presentation order, either presenting tasks before or after the pointing experiments is statistically significant, the task order
Fig. 1. iPad interface screenshot showing the arrow and compass utilized during the pointing tasks. Accuracy, measured in meters, is displayed at the top of the screen. A compass ring is utilized for the purpose of allowing the participant to recognize when the iPad is updating their location indicated by the movement of the ring.
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was not randomized (Hegarty et al., 2002). Next, participants were taken to four locations (origins) across campus and were asked to point to various other locations on campus (targets) (none of the origins were used as targets and vice versa). After each pointing task, participants rated their confidence in their estimate. It is important to note that while confidence and campus knowledge were generally rated medium to high by all participants most of the time, there was a distinct pattern. The majority of the least confident ratings were for locations in the university’s engineering building, for participants rating these targets as low (confidence or knowledge) they were removed from analysis (just the data for those specific targets). This was less than 5% of the data. Origin locations were balanced by alternating between indoor and outdoor origins. Participants began at an indoor origin, moving to an outdoor origin then to the next indoor origin and ending at the last outdoor origin. A total of forty-eight locations were pointed to: six indoor targets and six outdoor targets (excluding the additional three added to the indoor origins) at each origin location. An equal number of indoor and outdoor targets were assigned to each origin. The targets were randomly organized and the type of target was unidentified to the participant. At no point during the study were participants informed of their performance. 3. Results 3.1. Indoor vs. outdoor targets The dependent variable in this experiment was pointing error, measured in degrees. We recorded pointing error for every target location. The experiment was a 2 2 repeated measures analysis of variance (ANOVA) with factors Origin (indoor vs. outdoor) and Target (indoor vs. outdoor). Refer to Fig. 2 for the four cell analysis of pointing error for Origin Target. There was a main effect of Origin on pointing error between indoor (66.37) and outdoor (45.47) locations, F(1,205) ¼ 39.38, MSE ¼ 201,965.81, p ¼ .000. There was also a main effect of Target on pointing error between indoor (50.53) and outdoor (61.31) locations, F(1,205) ¼ 10.48, MSE ¼ 53,763.30, p ¼ .001. There was no interaction of Origin and Target type, F(1,205) ¼ .20, MSE ¼ 1024.81, p ¼ .66. Effect size for the interaction was small, thus we would have needed much greater power to observe an effect. 3.2. Individual differences
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Fig. 2. Mean pointing accuracy for indoor and outdoor origins between indoor and outdoor targets. Error bars in the figure represent standard error for each column.
the correlation remained stronger for survey strategy. Individual ttests were run to determine any significant gender differences in navigation strategy. A significant difference was present between male (26.18) and female (32.10) participants in outdoor route strategy (higher scores indicate greater preference for that strategy), t(77) ¼ 2.24, p < .05, as well as between male (18.68) and female (22.72) participants in indoor route strategy t(77) ¼ 2.27, p < .05. tTests did not reveal any significant differences in participant pointing ability for indoor or outdoor survey strategies between sexes, t(78) ¼ 1.09, p ¼ .28 and t(78) ¼ .036, p ¼ .97 respectively. 4. Discussion Based on our hypotheses, pointing accuracy was expected to be more accurate for outdoor origins when compared to indoor origins. Two contrasting hypotheses were presented for pointing accuracy regarding targets (Section 1.5, above). Depending on the logic followed, participants could display more accurate pointing accuracy for either indoor or outdoor targets. These hypotheses were based on evidence regarding the effects that landmarks, visual access, and layout complexity may have on one’s ability to
Correlations were used to analyze any significant differences between mental rotation and pointing accuracy. To analyze mental rotation, an average response time for each individual was used along with the number of correctly answered responses. Pointing error and mental rotation were negatively correlated such that as pointing error decreased, mental rotation ability increased, r(78) ¼ .298, p < .01. As well, individual t-tests illustrated a significant difference between male (.81) and female (.72) participants in the mental rotation spatial task, t(78) ¼ 2.36, p < .05. 3.3. Route vs. survey strategy Indoor and outdoor navigation strategy was tested against pointing error to reveal any significant relationships between strategy and pointing accuracy. For this, navigation strategy type was divided into route and survey. Average responses were calculated between route and survey strategy for both indoor and outdoor locations. Refer to Table 1 for the Pearson r correlation coefficients between pointing error, gender, and navigation strategy. Pointing error was found to be positively correlated with survey and route strategy when individuals were both indoors and outdoors; however,
Fig. 3. Average distance to targets and origins. Error bars in the figure represent standard error for each column.
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Table 1 Pearson correlations among pointing error and navigational strategy. Measure
Pointing error Outdoors e survey strategy Outdoors e route strategy Indoors e survey strategy Indoors e route strategy
Pointing Outdoors e Outdoors e Indoors e Indoors e error survey route survey route strategy strategy strategy strategy
.733** .523**
.382**
.784**
.656**
.479**
.471**
.347**
.717**
.384**
*p < .05, **p < .001.
develop a cognitive map for varying environments (Montello & Sas, 2006). As suggested in the previous research, utilizing global over local landmarks one can reduce the traveling distance in terms of searching for targets in a grid-like environment (Lin et al., 2012). Based on the definition of the two types of landmarks, the global landmarks are distant from the observer while the local ones are relatively closer (Steck & Mallot, 2000). In this case, it is not surprising that participants perform better when pointing from outdoor origins, because there are apparently a larger number of global landmarks outdoors than indoors which supports orientation. While pointing from indoor origins, where the space is much limited, participants have less visual access to determine their location and orientation. They were also based on whether or not nested environments play a role in the level of precision utilized during wayfinding. It is possible that utilizing the nested structure for direction support from outdoors (pointing from outdoor origins) is easier than indoors (pointing from indoor origins) as buildings are built as part of the campus environment (Wang & Brockmole, 2003b). In support of our first hypotheses, origin was found to influence pointing accuracy with individuals pointing more accurately from outdoor origins. For targets, individual pointing accuracy was more accurate for indoor locations when compared to outdoor locations. t-Test results suggest that the average distance to indoor targets is smaller than that to outdoor targets (t(46) ¼ 2.50, p < .05), while there is no significant difference between the average distance from indoor origins and outdoor origins (t(46) ¼ 1.19, p ¼ .24) as shown in Fig. 3. As to more accurate pointing TO indoor locations, we believe the strongest explanation is twofold: 1. the increased attention necessary
during microgenesis for the greater complexity of indoor spaces (multiple levels, constrained visual field, etc.) and 2. When calling up indoor locations from our cognitive map, the immediate surrounding are likely to be more closely spaced, resulting in the potential for a pointing frame or targeting apparatus that might improve our ability to point to discrete objects. Furthermore, with outdoor locations, they were (and are) often attached to larger buildings, therefore, if accurate storage of such landmarks is not as critical, because they are attached to a building, perhaps participants were pointing to the building. Both of these latter explanations suggest that it might not be the accuracy of the cognitive map for such locations (indoor vs. outdoor) but the extent to which their character supports or inhibits accurate pointing. Our second hypothesis was that individual differences in mental rotation as well as strategy type (as measured by the Indoor and Outdoor Strategy Scale) would affect pointing accuracy while illustrating significant differences between male and female performance. As expected, mental rotation ability predicted pointing accuracy. The gender differences reported in favor of men for mental rotation were again confirmed in our study (Zimmerman & Li, 2010). Results from this study confirm that individual differences are related to our navigational abilities and strategies. One explanation that could account for increased pointing accuracy from outdoor origins is orientation. It was noted by the researchers that participants often expressed feelings of being turned around during indoor origin pointing tasks. To explore this, participants’ average pointing error was analyzed individually. The standard deviation appeared to remain quite small, thus we plotted several individuals’ pointing accuracy for one indoor origin. Next, we subtracted the average error to see whether participants’ spatial relationships remained intact between target locations. This subtraction represents their consistency across target error; we believe this is a reasonable proxy for overall or baseline disorientation (bias). Once the average error was accounted for it becomes apparent that the individual’s orientation was simply in the wrong direction and a greater clustering of pointing accuracy is seen. As shown in Fig. 4, participants did appear to recognize the spatial relationships between target locations while indoors. While our experiment was not designed to statistically analyze these relationships, there is some empirical evidence in the literature. Wang and Brockmole (2003a) found that although many individuals were incorrect in determining their own positions within an environment relative to targets, they displayed relatively consistent accuracy and knowledge of the relationships between targets.
Fig. 4. Mean pointing accuracy for one participant at an indoor origin point. On the left side is their original pointing accuracy. The right side illustrates how their pointing accuracy changes when you remove error due to the participant’s incorrect mental orientation within the building. Dark bars indicate the actual target locations (see the black arrows).
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To better explain individuals’ increased accuracy in pointing towards indoor targets, characteristics of indoor environments were reconsidered. One possible limitation to this study, as well as a potential confound, is the design of the University of Saskatchewan campus. While the majority of spaces we navigate are orthogonally aligned (typically in grid-like patterns), most of the campus is designed in an oval shape around a central “bowl.” A grid-like pattern only occurs on campus for indoor environments. As Giudice et al. (2010) notes, one advantage of indoor spaces is that they typically display more regular geometrics when compared to outdoor environments. It would be interesting in future research to explore how the different complexities of the environments used in this study affect wayfinding ability. The difference in navigation ability between indoor and outdoor environments should be applied within the domain of spatial cognitive research. Research in this area could aid in the identification of techniques to produce building floor plans which allow for successful navigation for both visitors and individuals who frequently wayfind within the building. The type of landmarks used indoors, the availability of differing colors and shapes within a building’s design, and the intention to improve visual accessibility and reduce layout complexity could all aid in the improvement of indoor wayfinding. The extent to which the information researchers have gathered for outdoor environments is still applicable within buildings as well as within built environments, where navigation between indoor and outdoor environments is required, should also be addressed. While all navigational strategies predicted pointing accuracy, correlations remained stronger for survey strategy. This adds support for cognitive spatial microgenesis, as survey strategy is thought to be the most complex and advanced form of navigation (Ishikawa & Montello, 2006; Montello & Pick, 1993). There were also sex differences in route strategy use, illustrating that women were more likely to rely on route strategy compared to men. This supports the current literature and findings that women have a tendency to navigate based on landmarks, whereas men prefer orientation and survey navigational strategies (Kindig & Movassaghi, 1989). It is also worth noting that there were no significant differences found between navigation strategies employed indoors versus outdoors. Subsequently, it does not provide us with any additional insight into any navigational ability differences that exist between indoor and outdoor locations. Support for the theoretical framework of spatial microgenesis is further provided from these results, as the theory stipulates that the availability of landmarks (utilized for the subsequent creation of route and survey knowledge) has an effect on one’s ability to navigate (Griffin et al., 2006). While our results do not indicate what aspects of indoor and outdoor locations are creating the observed differences, they do indicate the presence of differences that need to be further explored. In particular the greatest accuracy (as a category of pointing) was pointing from outdoor origins to indoor locations. One “grand” hypothesis might be that combination and order present a daunting transition during navigation and that accurate orientation of outdoor spaces with indoor destinations is important to minimizing stress and maximizing successful movement through space. As well, because the survey navigation strategy was more predictive of pointing accuracy than route strategy, we confirm that route knowledge develops before survey knowledge and that survey knowledge represents a more complete ‘map-like’ representation of space (Griffin et al., 2006; Ishikawa & Montello, 2006; Montello & Pick, 1993). Based on the results of the present study, it appears that navigation is most difficult within the built environment, thus adding to the importance of developing effective navigational tools for indoor environments. Currently, integration between outdoor and indoor
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spatial information systems is lacking. Research has primarily focused on navigation outdoors, however individuals are increasingly tending to spend the majority of their time indoors (Goldberg et al., 2008). Also of interest is the lack of a universally used technology for indoor navigation, such as GPS to aid in wayfinding (Goldberg, 2008). Our results can aid in the exploration of differences in individual cognitive mapping of both indoor and outdoor spaces, and how these differences can subsequently be applied to the design of maps, wayfinding material (such as indoor signage) and GPS devices. As well, further research could look at the factors influencing individuals with cognitive and visual impairments. The strategies used for navigating and wayfinding may be altered to accommodate the specific impairments of those individuals affected. Individuals with visual impairments would naturally rely less on their visual sense compared to the average individual. What factors within our environment can be adjusted to increase the ease of wayfinding for these individuals? As well, what differences present themselves cognitively in individuals with cognitive impairments? Do individuals with this impairment utilize the same navigational strategies as the general population? Are some factors, such as landmarks, more important in effective wayfinding? One potential limitation of this study is the population sample utilized. Individuals in first year psychology courses may not be as familiar with the campus, and subsequently the target locations used for this study. As well, this sample represents a particular subset of the population. It would be interesting to explore pointing accuracy and individual differences within professions typically thought to have high levels of spatial skills (such as engineers or architects) in comparison to a control group (a profession which typically does not rely on well-developed spatial skills). As well, the sample used in this study does not vary significantly in age. It may be interesting to investigate how navigational ability changes over time, or between the young and old. Another possible limitation within this study is the design of the University of Saskatchewan campus, as mentioned previously. 5. Conclusions and implications The results from this study confirm the importance of further research in the area of spatial cognition within indoor environments. The increased accuracy in pointing towards indoor locations suggests that these locations were stored in cognitive maps with more accuracy, that they were recalled with more precision, or that there are aspects of how we store information about indoor locations that allows for more consistent recall of location. Greater care may be taken when pointing to indoor locations if more attention is required. This may result in increased precision, and we could conclude that similar to our hypothesis, more processing is required when pointing to indoor locations. In contrast, Prestopnik and Roskos-Ewoldsen (2000) stipulate that outdoor spaces may actually be more difficult for apprehension due to the increased amount of information required for analysis outdoors. Individuals need to recall street names, their locations, as well as their relation to other streets along with the layout of buildings and their orientation in relation to street patterns. More research will be required in order to understand more fully the cognitive processes occurring between indoor and outdoor orientation and navigation. Acknowledgments This study was conducted in the SAPHIR lab funded by the Canada Foundation for Innovation. We would like to extend our thanks to the students who helped throughout the research process
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Appendix. Indoor and Outdoor Strategy Scale
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including Lauren Arnold, Lindsay Aspen, Craig Siemens, Kumaran Vijayan, and Anton Sizo.
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