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Computer Assisted Navigation and the Aquisition of Route ... - About

Computer Assisted Navigation and the Aquisition of

Route and Survey Knowledge

Stefan Münzer*, Hubert D. Zimmer*, Maximilian Schwalm*, Jörg Baus + & Ilhan

Correspondance address

Dr. Stefan Münzer

Saarland University

Postfach 15 11 50

D-66041 Saarbrücken

Germany

Aslan +

*Department of Psychology, Brain and Cognition Unit

+ German Research Center for Artificial Intelligence (DFKI)

s.muenzer@mx.uni-saarland.de


Abstract

Computer Assisted Navigation and the Aquisition of Route and Survey Knowledge 2

The incidental acquisition of spatial orientation knowledge when using a pedestrian

navigation assistance system for wayfinding was compared to incidental learning during map-

based 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 view-

based 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.


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


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


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


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,


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,


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


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.


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.


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


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 = 0.0135, p < 0.001. 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 = 0.0135, 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.


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 < 0.001. A planned contrast showed

that the map-based wayfinding condition differed significantly from the three navigation

assistance conditions, F (1, 59) = 22.85, MSE = 5461.6, 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 = 1.347 for route recognition performance, and the same comparison

revealed d = 1.513 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).


Computer Assisted Navigation and the Aquisition of Route and Survey Knowledge 14

4. 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).


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-be-

adopted 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


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


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


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 151150, D-66041

Saarbrücken, Germany. Electronic mail should be addressed to s.muenzer@mx.uni-

saarland.de or huzimmer@mx.uni-saarland.de.


Computer Assisted Navigation and the Aquisition of Route and Survey Knowledge 19

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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 % 192 80

Auditory + context 20 % 10 % 186 79

Auditory 22 % 11 % 155 82

Map 7 % 10 % 75 52


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.


Computer Assisted Navigation and the Aquisition of Route and Survey Knowledge 25

Fig. 1


Computer Assisted Navigation and the Aquisition of Route and Survey Knowledge 26

(a)

(b)

(c)

(b)

Fig. 2


Computer Assisted Navigation and the Aquisition of Route and Survey Knowledge 27

Fig. 3


Computer Assisted Navigation and the Aquisition of Route and Survey Knowledge 28

Fig. 4


Computer Assisted Navigation and the Aquisition of Route and Survey Knowledge 29

Fig. 5


percent error

Computer Assisted Navigation and the Aquisition of Route and Survey Knowledge 30

0,35

0,30

0,25

0,20

0,15

0,10

0,05

0,00

visual+context auditory+context auditory map

Fig. 6


Computer Assisted Navigation and the Aquisition of Route and Survey Knowledge 31

deviation in pixels

260

240

220

200

180

160

140

120

100

80

60

40

20

0

Fig 7

visual+context auditory+context auditory map

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