Route and Survey Knowledge

Transcription

1 Computer Assisted Navigation and the Aquisition of Route and Survey Knowledge Stefan Münzer*, Hubert D. Zimmer*, Maximilian Schwalm*, Jörg Baus + & Ilhan Aslan + *Department of Psychology, Brain and Cognition Unit + German Research Center for Artificial Intelligence (DFKI) Correspondance address Dr. Stefan Münzer Saarland University Postfach D Saarbrücken Germany s.muenzer@mx.uni-saarland.de

2 Computer Assisted Navigation and the Aquisition of Route and Survey Knowledge 2 Abstract The incidental acquisition of spatial orientation knowledge when using a pedestrian navigation assistance system for wayfinding was compared to incidental learning during mapbased wayfinding. First-time visitors to a real environment (a zoo) took a guided tour. In the navigation assistance conditions, users were provided with direction information and viewbased pictures of the current intersection at each decision point, presented on a hand-held computer. In the map-based condition, participants derived route segments from a map (each segment comprising three or four intersections), and then walked the partial routes from memory. After walking, unexpected tests on route memory and survey knowledge were administered. Navigation assistance users showed good route knowledge and poor survey knowledge. In contrast, map users showed better survey knowledge and nearly perfect route knowledge. Variations of information presentation within navigation assistance conditions (auditory vs. visual direction command, additional presentation of allocentric spatial information) was not effective. Results are explained with an active encoding principle. Only information that is actually encoded, transformed, and/or memorized during the primary wayfinding activity, is incidentally learned. Since navigation assistance systems do not require users to encode, transform, and memorize spatial information, the spatial orientation knowledge of navigation assistance users is poor.

3 Computer Assisted Navigation and the Aquisition of Route and Survey Knowledge 3 1. Introduction When people navigate through a real environment, they might learn about the spatial configuration of the environment incidentally, i.e. as a side effect of wayfinding. This is particularly the case if maps are used. Maps support spatial learning in two ways. First, maps present spatial information as an allocentric survey representation of the environment, thereby showing the spatial relations between places within a stable reference frame. However, this presentation is orientation specific (e.g. Rossano & Warren, 1989; Rossano & Moak, 1998). Second, using a map for wayfinding purposes requires elaborated cognitive processing of the spatial information to derive the route from the map. The cognitive processing presumably involves mental rotation in order to align the map with the present view of the environment, which may partly overcome the orientation specificity of the map. While until recently people have commonly used maps to find their way in a novel environment, nowadays people more and more rely on navigation assistance systems. Such systems are widely used in cars, and pedestrian navigation assistance systems are available on mobile phones and hand-held computers (Baus, Kray & Krüger, 2001; Baus, Cheverst, & Kray, 2005; Krüger et al., 2004; Wasinger, Stahl & Krüger, 2003). Navigation assistance systems are helpful and comfortable wayfinding aids because they can indicate the to-be-adopted direction from the current position and perspective of the user. As a consequence, the cognitive spatial processing requirement on the user's side is minimized. Particularly when used in cars, the assistance systems are efficient wayfinding aids that can contribute to safety. However, navigation assistance make wayfinding comfortable and easy also for pedestrians (e.g. for tourists or business people in a foreign city). Comfortable wayfinding assistance might furthermore be used by elderly or disabled persons who have, for instance, difficulties in orientation in a new environment or in reading

4 Computer Assisted Navigation and the Aquisition of Route and Survey Knowledge 4 maps. However, the acquisition of spatial orientation knowledge is nevertheless considered desirable, for a number of reasons. First, people might simply wish to learn about the environment they are moving through, and after a few days in a new environment, people might wish to vary their routes, and might need less support by navigation assistance. Second, spatial orientation knowledge helps to plan routes that comprise a sequence of places. Third, assistance systems can fail or break down completely. Without spatial orientation knowledge, people would be lost. While the acquisition of spatial orientation knowledge might thus be generally desirable, the situations in which assistance systems are used differ with respect to the cognitive resources that can be devoted to spatial learning. In the car navigation situation, the driver should focus on the driving, and therefore, efficiency and wayfinding comfort as well as minimal load for the interaction with the system are the primary goals. However, effiency and minimal load while wayfinding might not be primary goals for a tourist in a city. For pedestrian wayfinding, spatial orientation learning could well be supported by a navigation assistance system. The acquisition of spatial knowledge when using a navigation assistance system might not longer occur incidentally as a consequence of the wayfinding effort. Unlike maps, assistance systems do not provide spatial information in a complete survey view with a stable reference frame. It might be the case that little is learned about the spatial configuration. In the present paper, the consequences of using navigation assistance for spatial learning of pedestrians are investigated. The present experiment was conducted in a real environment since it is possible that spatial learning is based on the stimuli in the environment rather than on information shown in a map or presented by an assistance system. Humans acquire different forms of knowledge of large-scale space, depending on the learning experience. Route knowledge is the knowledge of places or landmarks and the routes that connect them. The according mental representation can be conceived of as a sequence of

5 Computer Assisted Navigation and the Aquisition of Route and Survey Knowledge 5 view-based (egocentric) visual images of landmarks together with directions (Gillner & Mallot, 1998). When exploring an environment solely by navigation (i.e. without a map), the majority of people first acquire route knowledge. Since the mental representations of the landmarks are based on views from an individual s perspective, Aginsky, Harris, Rensinck and Beusmans (1997) called memory for routes "visually dominated". In contrast, survey knowledge indicates an understanding of the spatial relationships between locations. Survey representations provide an overview over the spatial layout, based on an extrinsic frame of reference, i.e. it is a map-like representation from an allocentric perspective (Evans, 1980; Hart & Moore, 1973; Kitchin, 1994; McNamara, Ratcliff, & McKoon, 1984; Siegel & White, 1975; Taylor & Tversky, 1992). This so-called "mental" or "cognitive" map allows flexible spatial orientation (e.g. drawing inferences about spatial relations between places, planning of routes not yet travelled). In general, the acquisition of survey knowledge appears desirable for successful and flexible orientation in an environment. It has been proposed that with growing experience survey knowledge is developed from route knowledge quite automatically (Siegel & White 1975; Cousins, Siegel & Maxwell, 1983; Kirasic, Allen & Siegel, 1984). However it seems that the acquisition of survey knowledge is strategic and cognitively effortful rather than automatic. People who have acquired their orientation knowledge solely by navigation have difficulties with spatial judgments that require a bird s eye view, even if they know the environment for months or years (e.g., Thorndyke & Hayes-Roth, 1982). People differ inter-individually with respect to preferences and strategies in building up survey knowledge from navigation experience (Kozlowsky & Bryant, 1977; Pazzaglia & De Beni, 2001), and only a minority deliberately choose to build up an allocentric, map-like mental representation when learning a route by navigation, i.e. to use a "spatially dominated strategy" (Aginsky et al., 1997). The acquisition of survey knowledge is supported by an appropriate information format. Maps directly provide a structured model of the environment including all spatial

6 Computer Assisted Navigation and the Aquisition of Route and Survey Knowledge 6 relations between the places in the environment. Investigations of map learning have shown that people built up a coherent spatial mental model when studying maps (e.g. Denis & Zimmer, 1992; Thorndyke & Hayes-Roth, 1982; Tlauka & Wilson, 1996; Rossano & Moak, 1998). In an everyday wayfinding situation, a map is used to derive a route. For this purpose, the information from the map as a model of the environment is extracted and transformed in order to make use of it for route derivation. For instance, the allocentric map perspective has to be transformed into the current egocentric perspective in the real environment, and vice versa. Thus, in the everyday wayfinding situation two presuppositions for spatial learning are fulfilled. First, the information in the map directly provides a survey model of the environment. Second, the information is actively processed, transformed, memorized etc. during the wayfinding activity. This makes it probable that incidental spatial learning will happen if people use maps for wayfinding. When using a navigation assistance system, however, people are presented with information that corresponds to their current perspective and view. Furthermore, depending on the design of the system, survey information is not presented at all, might be incomplete or might also correspond to the egocentric view. As a consequence, incidental spatial (survey) learning seems unprobable during wayfinding. According to the transfer appropriate processing account (Morris, Bransford, & Franks, 1977; McDaniel & Kearney, 1984) users will learn that information that has been processed to solve the goal of wayfinding. When using a navigation assistance system, route information (i.e. the combination of views and directions) is processed during travel. The incidental learning effect should therefore concern memory for the route, but not for spatial relations of places in the environment. In contrast, when using a map, survey information has been processed during wayfinding. In addition, using maps for wayfinding requires information transformation (as described above) while this is not necessary when using a navigation assistance system. The rather shallow processing of navigation assistance users should therefore result in less distinct (Jacoby,

7 Computer Assisted Navigation and the Aquisition of Route and Survey Knowledge 7 Craik, & Begg, 1979) and less elaborated encoding (Craik & Tulving, 1975) compared to the deeper processing of spatial information by map users. As a consequence, navigation assistance users should have less accurate knowledge of routes and spatial relations than map users after wayfinding in a real environment. Consistent with this expectation, moderate route memory and only poor survey knowledge was found in navigation assistance users (Krüger, Aslan & Zimmer, 2004). However, in this prior study no map-based wayfinding condition was included to test directly the hypothesis of poor incidental spatial learning of navigation assistance users. In the present study, three different navigation assistance conditions (differing with respect to presentation modality and the presentation of additional survey-like information) are compared with a map-based condition in a pedestrian wayfinding situation. In the assistance conditions, route information was always presented as view-based pictures at intersections (i.e. pictures of the environment as seen from the participants current point of view) together with a direction command. In two of three navigation assistance conditions, the direction command was presented auditorily-verbally (i.e. as a speech command together with the view-based picture of the intersection), while in one of the conditions, the direction was visually indicated as a red line included in the picture of the intersection. This variation was intended to check whether a combination of modalities (auditory-verbal plus visual) would lead to better learning. Multimedia learning theory (e.g. Mayer & Moreno, 1998) and cognitive load theory (Chandler & Sweller, 1991; Sweller & Chandler, 1994; Sweller, Van Merrienboer & Paas, 1998) predict that a combination of the auditory-verbal with the visual modality should be superior. However, recent studies conducted in our laboratory have demonstrated a robust picture superiority effect for route learning over combinations of verbal and pictorial information in route instructions. Two of the three navigation assistance conditions provided additional information that was intended to enhance spatial learning. A visual animation showed, from a bird's eye view,

8 Computer Assisted Navigation and the Aquisition of Route and Survey Knowledge 8 the shape of the current way segment from the last intersection to the present one and its continuation to the next intersection. Thus, the animation provided an allocentric view on three intersections, including their spatial relations. Animations generally are thought to enhance understanding of dynamic processes (e.g. Mayer & Anderson, 1992; Mayer & Moreno, 2002; but see Hegarty, Kriz & Cate, 2003). In the present experiment the animations illustrated the movement along the shape of the walked way as an aid for building the relation between the egocentric views on the landmarks, the actual movement in the environment, and the shape of the way seen from a bird s eye view. It was hypothesized that this additional context information would support the acquisition of survey knowledge. 2. Method 2.1 Participants and Design Sixty-four subjects took part in the study (33 were female, 31 were male). The mean age was 24 years (range 17 45). All participants were first-time visitors to the zoo environment. Participants were paid for their participation. The four experimental conditions mentioned in the introduction were realized in a between-subjects design. Sixteen participants took part in each condition. There was the same number of female and male participants in each of the conditions (accidentally in the map condition there were 9 females and 7 males). 2.2 Materials The zoo of Saarbrücken (Germany) was chosen as the real environment. A route through the zoo was selected as the walking path. The route consisted of 16 decision points and 15 pathway segments (see Figure 1). It was the same for all subjects in all conditions. In three out of four conditions, participants were equipped with a personal digital assistance (PDA) computer (Hewlett-Packard ipaq 5450 Pocket PC). This PDA computer

9 Computer Assisted Navigation and the Aquisition of Route and Survey Knowledge 9 served as the pedestrian navigation system. When a participant has reached a critical intersection along the route, a picture of that intersection appeared on the screen of his/her PDA. This picture (photograph) always corresponded to the actual view from the participants' perspective. The PDA computer used by the participant was connected via a wireless local area network using Bluetooth technology to another PDA computer that was used by the experimenter. The experimenter could send a signal to the participants' PDA computer. According to the signal, the next navigation information presentation appeared on the participants' PDA computer screen. This signal was sent at pre-defined positions along the route such that every participant received the navigation information at the same position. The presentation was varied as follows: Visual + context: Before a direction command was presented, there was a visual animation which consisted of a partial route showing the previous, the current and the next intersection, depicting their spatial relations from a bird's eye view. Additionally, the shape of the way was filled with an animation effect. When the animation started, the view-based picture of the current intersection was small, like a thumbnail-preview. It was visually attached to the representation of the current intersection. At the end of the animation, the attached view-based picture of the current intersection zoomed to a larger size until it filled the entire screen (see Figure 2 a). The direction was indicated by a red line in this picture of the intersection (as depicted in Figure 2 a). Auditory + context: In this condition, the picture of the intersection was complemented with an auditory-verbal command (e.g. "turn left"). There was a red dot in the picture indicating the exact position at which the command should be applied (see Figure 2 b). In this condition, the same spatial context animation was presented as in the visual + context condition.

10 Computer Assisted Navigation and the Aquisition of Route and Survey Knowledge 10 Auditory: The picture of the intersection was presented, and the direction command was provided auditorily-verbally as in the auditory + context condition. However, no context was presented (see Figure 2 c). Map: In the map-based wayfinding condition, participants did not use PDAs. They were shown a sheet of paper (DIN A 4 size) with a map fragment of the zoo. A fragment covered a part of the original route involving three or four intersections on the route. The map fragments only showed the shape of the ways, but no landmarks. The original route had been broken down into four such partial routes, and for each a fragmentary map had been prepared. Additionally, there were photographs of the three or four intersections of this part of the route depicted on the paper. These photographs were the same as used on the PDA computers in the navigation assistance conditions, but without location or direction information. The pictures were numbered to indicate their order. The start and destination positions on the map were marked, and the critical intersections (decision points) were indicated by dots (see Figure 3). With this information the to-be-adopted route could be inferred. The presentation of the map fragment required participants to find their way from a map under controlled conditions and similar landmark information as in the navigation assistance conditions (i.e. pictures of the intersections). The knowledge acquired by the participants was tested with a route recognition test and a test on survey knowledge. In the route recognition test, the ability to remember the correct direction given a picture of an intersection was tested. The same pictures that were presented during the walk were presented without any direction information on a tablet PC (Acer Travelmate C110) in randomized order. The images contained sensitive areas marked by red rectangles that could be tabbed by the subjects to indicate the direction they had taken at each decision point (see Figure 4). There were 13 items in the route recognition test for which the participant had to choose among two alternatives. There were three items in the test for which the participant had to choose among three alternatives.

11 Computer Assisted Navigation and the Aquisition of Route and Survey Knowledge 11 Survey knowledge was tested by a spatial relocation task. In this task, thumbnail pictures of the intersections had to be placed at their correct locations on a roadmap of the zoo. No landmarks were shown on this map. The pictures were the same as used in the route recognition test. Subjects were presented with the map on a tablet PC (Acer Travelmate C110) and they had to drag and drop the pictures of the intersections on the map (see Figure 5). The software for the pedestrian navigation system on the PDA computers as well as the route recognition and the survey knowledge test software on the tablet PC was developed and provided for the present study by the German Research Center for Artificial Intelligence (DFKI, Saarbrücken, Germany). 2.3 Procedure The experiment consisted of two parts. The guided walk realized the incidental study phase and afterwards, the two tests were administered. Participants were not informed that they would be tested for route and survey knowledge. The study was introduced as a usability study of navigation assistance systems. In the three navigation assistance conditions, the PDA computer was handed to the subject. In the auditory-verbal conditions, subjects wore one in-ear earphone. During the tour, the experimenter followed with a separate PDA computer at a distance of about 10 meters. When the subject has passed a pre-defined position, the experimenter sent a signal from his/her PDA computer to the subjects' PDA computer. The subjects' PDA computer then presented the relevant information for the approached intersection (the view-based picture of the current intersection, direction information and animation) dependent on the condition. In the map-based wayfinding condition, the participant was shown a map fragment. The participant had to infer which direction he/she would have to go at the intersections, and he/she was asked to indicate the direction by drawing an arrow on the picture for each of the intersections. The participant was asked to memorize the directions and the views of the three

12 Computer Assisted Navigation and the Aquisition of Route and Survey Knowledge 12 or four intersections for this segment of the walk. The map fragment then was taken away, and the participant walked the partial route from memory. This procedure was repeated for all four route segments until they the original route was completed. Walking the tour in the zoo environment took approximately 25 minutes. In the test phase, the route recognition test was administered first, followed by the survey knowledge test. Both tests were given to the participants after the study phase. Neither in the route recognition test nor in the survey knowledge test there was a time limit for giving the answer in a particular trial. Only accuracy performance was calculated. Since there was no laboratory room available in the zoo, participants completed the tests using a tablet PC suitable for outdoor use. Testing lasted about 25 minutes. 3. Results Route memory performance was evaluated on the basis of the number of correctly remembered directions in the route recognition test. Overall, participants performed quite well in this test (7 % to 25 % errors; see Table 1). The 95 % confidence intervals do not overlap with chance performance (see Figure 6), which is about 50 %. The four conditions differed. A one-way between subjects analysis of variances with navigation condition as factor revealed a significant difference for the relative number of false directions, F (3, 60) = 7.14, MSE = , p < No significant difference was obtained between the three conditions in which navigation assistance was used (F (2,45) = 0.85), and also all pair-wise comparisons were far from significance. However, route memory after map-based wayfinding was significantly better than after walking guided by navigation assistance (F (1, 60) = 19.54, MSE = , p < 0.001). Thus, route memory performance was good in the navigation assistance conditions, but it was nearly perfect in the map-based wayfinding condition. An additional analysis including gender as factor yielded no significant gender effects for route memory performance.

13 Computer Assisted Navigation and the Aquisition of Route and Survey Knowledge 13 In the survey knowledge test, subjects had to replace thumbnail pictures of the intersections onto a roadmap of the zoo. For evaluating the accuracy of survey knowledge, the deviations of the replacement from the correct place on the map were measured in pixels, and all deviation values were subsequently averaged. One subject had to be excluded from the data set due to missing data. Inspection of the descriptive results already showed that survey knowledge was quite poor in all experimental conditions in which participants had used navigation assistance. Deviation values of up to 200 pixels for the replacement of an intersection on a complete roadmap of the zoo that had been shown as a picture with 1024 x 768 pixels mean quite poor accuracy. In contrast, the mean deviation value in the map-based wayfinding condition was about 78 pixels which indicates a considerably better replacement performance. This impression was confirmed in an one-way between subjects analysis of variance with navigation condition as factor, which revealed a significant difference for the mean deviation in pixel, F (3, 59) = 8.31, MSE = 5462, p < A planned contrast showed that the map-based wayfinding condition differed significantly from the three navigation assistance conditions, F (1, 59) = 22.85, MSE = , p < 0.001). However, no significant differences were obtained between the three conditions in which navigation assistance was provided, F (2, 44) = 0.95, and also no pair-wise comparison was significant. Again gender did not influence these results. These data might suggest that the difference between the map condition and the assistance conditions were larger for the survey knowledge than for the route recognition performance. A comparison of effect sizes using Cohen's d revealed that this was not true. The size of the effect of the map condition compared with the mean of the assistance conditions was d = for route recognition performance, and the same comparison revealed d = for survey knowledge. Thus, the effect of the map condition was strong, and the effect did not differ considerably with respect to the dependent variable (route recognition vs. survey knowledge).

14 Computer Assisted Navigation and the Aquisition of Route and Survey Knowledge Discussion The main hypothesis that motivated the present experiment was that using a navigation assistance system results in poor spatial memory, because subjects would incidentally learn only that information they have dealt with during the wayfinding activity. It was therefore expected that users of navigation assistance systems would acquire route knowledge, but their memory for spatial survey information would be poor. In contrast, it was hypothesized that map users would acquire both route and survey knowledge as a side effect of their wayfinding effort. The pattern of results supports these hypotheses. Map users acquired better survey knowledge as well as better route knowledge, compared to the knowledge acquired by assistance users. However, more specific hypotheses regarding the effects of presentation modes by a navigation assistance system on memory were not confirmed. It has been expected that the acquisition of survey knowledge would be enhanced by a visual animation of the spatial context because an allocentric perspective is thereby presented in addition to the egocentric view. Due to results from explicit route learning, it has been furthermore assumed that visual presentation of direction information would be superior over an auditory presentation. None of these manipulations of the presentation format did influence learning in the real environment. All three assistance groups showed comparable results. Our explanation is that these manipulations were inefficient because the information provided was not actively processed by the pedestrians. The provided information was not needed for the primary goal of wayfinding. Since participants did not know that remembering would be relevant, they "passively" used the readily available direction information for navigation. In other words our attempts to enhance spatial information presentation did not overcome the less elaborated mode of processing of the navigation assistance users during their wayfinding activity. The observation of poor spatial orientation knowledge under these circumstances is in line with the view that spatial learning is an effortful and error-prone process (e.g. Thorndyke & Hayes-Roth, 1982; Aginsky et al., 1997; Gillner & Mallot, 1998).

15 Computer Assisted Navigation and the Aquisition of Route and Survey Knowledge 15 Map users not only acquired better survey knowledge but they also acquired better route knowledge, which additionally supports an active learning hypothesis. We assume that this learning advantage comes from the additional active effort that map users invested in dealing with the route information during wayfinding. Unlike the assistance users the map users had to derive the direction information by relating the pictures of the intersections to the marked intersections on a fragmentary map (thereby processing mental spatial transformations) and, by walking a route segment from memory, they had to keep the to-beadopted direction for the current segment in working memory. These processes are likely to enhance memory encoding and consolidation. Studies manipulating cognitive load show that working memory is indeed involved in spatial learning tasks (e.g. Lindberg & Gärling, 1981; Rossano & Moak, 1998). More specifically, visuo-spatial working memory (Logie, 1995) which is viewed as a specialized working memory component within the tripartite working memory model of Baddeley (1986) is thought to play an important role in spatial orientation (Smyth & Waller, 1998; Garden, Cornoldi & Logie, 2002; Bosco, Longoni & Vecchi, 2004; Coluccia & Louse, 2004; Coluccia & Martello, 2004). In the map condition these working memory processes should leave 'traces' for long-term memory. Moreover, if working memory is viewed as an activated sub-set of long-term memory (e.g., Cowan, 1988, 1995), more elaborated working memory structures should lead to better (i.e. more elaborated and highly accessible) long-term memory structures. We thus consider the active encoding explanation as the most likely reason for the superior spatial orientation knowledge of the map users. An alternative explanation would be that survey views were more familiar for the map users than for the assistance groups since they had studied map fragments. Map users might remember the allocentric views and match memory of the shape of the ways on a studied fragment with the shape of ways on the complete map during testing (however this is considered difficult given the complex map without any landmarks that was used in the test). Admittedly, this argument is a consequence

16 Computer Assisted Navigation and the Aquisition of Route and Survey Knowledge 16 of our dependent measure of survey knowledge, which involved using a roadmap of the zoo for the relocation of places. Other, additional measures such as a pointing test or sketch maps could have helped to further substantiate the difference between assistance and map users. However, the measure used in the present study reflects everyday spatial learning and retrieval. Both learning and retrieval of spatial orientation knowledge involves moving through and thereby studying the real environment as well as studying a map (as travelers often do) that represents it. In other words, the perception of the real environment and the cognitive processing of internal and external representations of it are intertwined both when learning and when retrieving spatial information in everyday orientation. From our point of view, the decisive point is that map users actively dealt with the information presented, and not that they matched roadmap fragments seen in the study phase. This argument is supported by the fact that assistance users also had spatial context information available during wayfinding. The visual animations that were provided in two of the assistance conditions comprised three intersections and the shape of the ways connecting them from an allocentric perspective. That is, the assistance users also saw roadmap fragments. Nevertheless survey memory of the navigation assistance users was poor. This suggests that the presence of survey information does not suffice. The information has to be used during walking to become effective for spatial learning. Finally, one might speculate that participants reconstruct survey knowledge from route memory. They might solve the replacement task by relating the remembered view-based pictures to the bird's eye perspective shown on the roadmap at the time of test, i.e., they mentally walk the route again and try to find the appropriate intersections on the map by transforming the egocentric perspective of a particular intersection into an allocentric perspective. This strategy would have been possible since the start position was provided as a reference point on the map in the replacement task. Direction knowledge (i.e. in which direction one walked at a particular intersection) would help to successfully solve the

17 Computer Assisted Navigation and the Aquisition of Route and Survey Knowledge 17 replacement task. However, this presupposes that the order of intersections is remembered without errors, since after a single mistake all subsequent reconstructions would be wrong. There is no indication in the data that participants applied such a strategy, neither in the assistance nor in the map conditions. Participants misplaced intersections at the beginning of the walk in the same way as they misplaced intersections later on the route. Performance was generally poor independent of the serial position. On the contrary, when making an attempt to describe the observed replacement behavior of the participants, it resembles more a reconstruction of configurations by provisional placements and replacements than by following an explicit strategy. Finally, if the strategy would have been actually applied, then both navigation assistance users and map users should have been successful in the replacement task. Because the data show a clear advantage of map users, we therefore believe that the better performance of map-users in the replacement test is a consequence of the better memory of survey information acquired during wayfinding. In summary, the present study puts forward an extended focus on the design of navigation assistance systems including their consequences for memory and for acquisition of spatial orientation knowledge. The design of navigation systems is usually optimized with respect to cognitive ergonomics during wayfinding. Direction information is provided in a way such that navigation is as easy as possible. This may have consequences on spatial learning, which is rarely discussed. We hypothesized that navigation assistance systems reduce spatial processing to a minimum, and consequently spatial knowledge would be poor. Our data confirm this hypothesis. Both survey and route knowledge were considerably better in the map guided group than in the navigation assistance groups. Hence, if spatial learning would be relevant for users e.g. for tourists, but also for elderly and/or disabled persons, it is necessary to adopt the design in a way that the acquisition of spatial orientation knowledge is also supported. The presentation of additional allocentric information using animations and/or the manipulation of presentation modality did not work in the present real environment

18 Computer Assisted Navigation and the Aquisition of Route and Survey Knowledge 18 study. We assume that those manipulations were inefficient because they did not initiate active encoding. It remains therefore a challenge for intelligent human-computer interaction design to find a way to both present information and to require the user to deal actively with this information. It might be suggested that for spatial learning, route instructions and working with maps with the requirement of some spatial processing could be combined. Such a specific combination taking an individual's preferences and spatial strategies into account may stimulate and support the acquisition of spatial orientation knowledge. Acknowledgments This research was supported by a grant from the Deutsche Forschungsgemeinschaft in a Special Collaborative Research Group on Resource Adaptive Cognitive Processes (SFB 378) to Hubert Zimmer. We wish to thank three anonymous reviewers for valuable comments on this paper. Correspondence concerning this article should be addressed to Stefan Münzer or Hubert Zimmer, Dept. of Psychology, Saarland University, P. O. Box , D Saarbrücken, Germany. Electronic mail should be addressed to s.muenzer@mx.unisaarland.de or huzimmer@mx.uni-saarland.de.

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23 Computer Assisted Navigation and the Aquisition of Route and Survey Knowledge 23 Table 1. Results of the route recognition test and the survey knowledge test. Condition Route recognition (percent error) Survey knowledge (deviation in pixels) Mean SD Mean SD Visual + context 25 % 15 % Auditory + context 20 % 10 % Auditory 22 % 11 % Map 7 % 10 % 75 52

24 Computer Assisted Navigation and the Aquisition of Route and Survey Knowledge 24 Figure 1. The roadmap of the real environment (a zoo) with the intersections of the route designed for the present study. Figure 2. The navigation assistance conditions differing with respect to the modality of the direction command (auditory vs. visual) and the presentation of an additional visual animation for providing spatial context; (a) visual command with spatial context, (b) auditory ommand with spatial context, (c) auditory command without spatial context. Figure 3. Example of the materials used in the map condition for wayfinding (map fragment and photographs of intersections). Figure 4. The route recognition test (example). Participants could indicate the correct direction by clicking into one of the marked boxes. Figure 5. The survey knowledge test (replacement task). Figure 6. Result of the route memory test (mean percent error). Vertical bars denote 95 % confidence intervals. Figure 7. Result of the survey knowledge test (mean deviation in pixels). Vertical bars denote 95 % confidence intervals.

25 Computer Assisted Navigation and the Aquisition of Route and Survey Knowledge 25 Fig. 1

26 Computer Assisted Navigation and the Aquisition of Route and Survey Knowledge 26 (a) (b) (b) (c) Fig. 2

27 Computer Assisted Navigation and the Aquisition of Route and Survey Knowledge 27 Fig. 3

28 Computer Assisted Navigation and the Aquisition of Route and Survey Knowledge 28 Fig. 4

29 Computer Assisted Navigation and the Aquisition of Route and Survey Knowledge 29 Fig. 5

30 Computer Assisted Navigation and the Aquisition of Route and Survey Knowledge 30 0,35 0,30 0,25 percent error 0,20 0,15 0,10 0,05 0,00 visual+context auditory+context auditory map Fig. 6

31 Computer Assisted Navigation and the Aquisition of Route and Survey Knowledge deviation in pixels visual+context auditory+context auditory map Fig 7