Memory & Cognition
2007, 35 (5), 895-909
Learning geographical information
from hypothetical maps
Nora S. Newcombe
Temple University, Philadelphia, Pennsylvania
and
Noelle Chiau-Ru Chiang
Shih-Hsin University, Taiwan
People show biases or distortions in their geographical judgments, such as mistakenly judging Rome to be
south of Chicago (the Chicago–Rome illusion). These errors may derive from either perceptual heuristics or
categorical organization. However, previous work on geographic knowledge has generally examined people’s
judgments of real-world locations for which learning history is unknown. This article reports experiments on the
learning of hypothetical geographical spaces, in which participants acquired information in a fashion designed
to control real-world factors, such as variable travel experiences or stereotypes about other countries, as well as
to mimic initial encounters with locations through reading or conventional school-based geography education.
Five experiments combine to suggest that biases in judgment based on learning of this kind are different in key
regards from those seen with real-world geography and may be based more on the use of perceptual heuristics
than on categorical organization.
There are several important reasons to study geographical learning. First, knowledge of geographical or larger
scale space is important for effective functioning in the
modern world. Recent data show that American children
and even adults have very little knowledge of world geography, leading to concern that the country is ill-equipped
to consider important questions concerning international
relations and an increasingly global economy (Liben &
Downs, 1994). Second, studying geographical learning
offers a real and complex context in which to examine
the integration and the interaction of information from
many disciplines and knowledge domains. Learning geography requires more than simply encoding the spatial
layout of cities and countries. It also involves learning the
nature of the environments and climates in which these
places are embedded, what natural resources these places
possess, and the human aspects of such spatial contexts,
such as cultures, political systems, and economic activities (National Geographic Research and Exploration,
1994). Third, in recent years, people working with geographic information systems (GISs) have called for input
from cognitive scientists, because understanding of how
human minds process geographical information is vital
to building and improving the application of GIS technology (Blades, Lippa, Golledge, Jacobson, & Kitchin,
2002; Freundschuh, 2000; Mark, Freksa, Hirtle, Lloyd,
& Tversky, 1999). Fourth, geographic learning offers an
important real-world context for further investigating the
effects of categorization and perceptual processes on spatial estimation (Huttenlocher, Hedges, & Duncan, 1991).
The study of spatial learning dates back to Tolman’s
(1948) cognitive map research, but research on geographic
knowledge has not been common until more recently. Stevens and Coupe (1978) provided the first empirical evidence demonstrating that representations of the environment are hierarchically organized. It is now well known
that people misjudge location in ways apparently based
on membership in superordinate categories (e.g., placing
Reno to the east of San Diego because Nevada is largely
east of California). Hirtle and Jonides (1985) extended
Steven and Coupe’s model to a situation in which the hierarchical categories were ambiguous and ill-defined. The
participants in their experiment were University of Michigan students who were asked about landmarks in a map of
Ann Arbor. Using a variety of dependent measures, Hirtle
and Jonides found that the participants overestimated distances for between-cluster pairs and underestimated them
for within-cluster pairs, suggesting that they formed subjective spatial categories even without seeing well-­defined
boundaries in the space.
Tversky (1981) argued that distortions or biases in the
estimation of geographic location occur due to heuristics
derived from principles of perceptual organization. For example, in her view, people tend to misjudge South America to be far more west than it actually is because they
“align” North America and South America into a simple
N. S. Newcombe, [email protected]
895
Copyright 2007 Psychonomic Society, Inc.
896 Newcombe and Chiang
unit along a longitudinal axis. Similarly, because they
“align” North America with Europe along a latitudinal
axis, people tend to misjudge Rome to be to the south of
Chicago. Tversky’s perceptual approach has been elaborated in several further studies (Glicksohn, 1994; Schiano
& Tversky, 1992; Tversky & Schiano, 1989).
Huttenlocher et al. (1991) have proposed a different
conceptual framework concerning the processes that
could create biases in estimates of geographic location.
Their category adjustment (CA) model posits that people
represent spatial locations at more than one level of spatial resolution and that they make estimates by combining
information from a fine-grained level and a categorical
level. When memories at the fine-grained level are more
inexact, categorical information is more heavily weighted,
and biases can arise. For example, if people do not remember exactly where a particular object is located, they
might weight their estimate with categorical information
concerning the region in which it is located, using the
prototype location of the region. Although this process
creates bias, it is adaptive in that it reduces variability
of estimates. The CA model has been largely developed
using data from spatial location estimates in simple and
highly controlled contexts, such as the location of a dot
in a circle, but it has also been extended to learning from
simple maps (Newcombe, Huttenlocher, Sandberg, Lie,
& Johnson, 1999).
Recently, Friedman and Brown (2000a, 2000b) have
proposed that real-world geographical knowledge shows
effects of categorization. They asked participants to estimate the locations of a set of world cities. In some experiments, the participants were asked to estimate the latitudes of those cities, whereas in other experiments, they
were asked to estimate the longitudes. Interestingly, Friedman and Brown found that although people have quite
accurate qualitative (or categorical) knowledge about city
locations, their quantitative knowledge is often inaccurate.
Two main patterns of biases were identified in their studies. First, there was a tendency for people to group North
America into four regions (Canada, the northern U.S., the
southern U.S., and Mexico) and to group Europe into three
regions (northern Europe, central Europe, and Mediterranean Europe) but to discriminate relatively little within
each region. That is, people’s estimates showed definite
jumps when country (or region) boundaries were crossed,
with little differentiation for estimates within countries
(or regions). Second, in addition, people tended to coordinate (or “line up”) countries or regions from different
continents—for example, Canadian cities with cities in
northern Europe, cities in the northern U.S. with cities
in central Europe, and cities in the southern U.S. with
cities in Mediterranean Europe. This type of processing
provides one possible explanation for the Chicago–Rome
illusion: Because participants categorized these two cities
as in the “northern U.S.” and “Mediterranean Europe,”
their estimates for these cities were different, even though,
in fact, these two cities have similar latitudes. Thus, Friedman and Brown proposed that the phenomenon that Tversky attributed to an alignment process occurred because
of categorical judgments, rather than due to perceptual (or
figurative) processing. Friedman, Brown, and McGaffey
(2002) provided direct evidence for this proposal.
Friedman and Brown (2000a, 2000b) examined whether
people’s knowledge could be improved using the seeding
paradigm, developed by Brown and Siegler (1996). They
provided participants with the exact locations of a few cities and found that these “seeds” profoundly improved the
accuracy of second estimates. In addition to being practically and educationally useful, seeds also offer a window
for understanding how old knowledge is reorganized by
accommodating new information. For example, seeds
from one category can improve knowledge about different categories only if those categories of knowledge are
coordinated. Thus, it is interesting that learning southern
U.S. seeds not only moved estimates of the location of
southern U.S. cities north, but also moved estimates of
Mexican cities north. This fact indicates that the participants coordinated the locations of these two regions. Similarly, because southern European cities are coordinated
with southern U.S. cities, seeds moved southern European
cities accordingly. However, people did not move African
cities north following seeding, possibly because there is a
gap (the Mediterranean Sea) between southern European
cities and northern African cities. The participants may
simply have concluded that the Mediterranean Sea was
larger than they had imagined.
Friedman, Kerkman, and Brown (2002) extended this
line of work to examine one possible cause for biases and
distortions in people’s subjective representations of geographical knowledge: the home location of the participants. Prior work had involved people living in Edmonton,
Alberta, so their estimates might have been influenced by
physical proximity to various locations. Physical proximity
hypotheses predict that an increase of the distance from a
participant’s home will cause more biases in geographical
knowledge. Surprisingly, however, Texan college students
produced more biased estimates of Mexican cities (about
16º more biased) than did Canadian college students. Subsequent research has confirmed these findings and has
shown that even Mexican participants bias estimates of
Mexican cities towards the equator (Friedman, Kerkman,
Brown, Stea, & Cappello, 2005). The categorical organization of North America varied, with Mexicans dividing
Mexico into two regions but viewing the United States
as consisting of only one region, whereas Americans and
Canadians continued to show the two-category organization of the United States observed previously, with only
one category for Mexico.
Friedman et al.’s research is important for several reasons. First, it supports the notion that people’s subjective
representation of geographical knowledge is categorical
in nature. Therefore, it reinforces Stevens and Coupe’s
(1978) classic findings and suggests the utility of Huttenlocher et al.’s (1991) hierarchical model for thinking
about people’s geographical knowledge. People’s location
judgments of world cities seem to depend on their knowledge of the superordinate categories to which those cities belong. Second, their seeding paradigm is important
both theoretically and practically. Theoretically, the seeding paradigm provides us with a technique for examining
Learning Geographical Information 897
how people correct their incorrect geographical beliefs
and restructure their geographical knowledge to accommodate new information. Practically, in terms of educational application, this method is particularly useful for
teachers who wish to help students improve their overall
knowledge by offering only critical information.
Friedman and Brown’s work does not, however, definitively settle the issue of the role of perceptual heuristics
and categorical organization in geographic learning. It is
possible that both factors are relevant or that one or the
other factor is more important, depending on the context
in which information is learned or used. In particular,
categorical structure might be relatively more important
when people have a strong knowledge base about countries based, in part, on personal experience, whereas
perceptual factors might loom larger early in geography
learning, when books, maps, lectures, or film are the primary means of information transmission. In the present
work, we studied geographical learning by using fictional
cities and countries, allowing us to study situations in
which people bring no specific information to an experiment. Our aim was to simulate conventional school-based
geography classes.
In Experiments 1 and 2, we explored whether we
could replicate some of the key findings of Friedman
and Brown, using hypothetical countries. In particular,
we asked whether we would see large differences in location estimates across country boundaries, along with little
within-country differentiation, as predicted by categorical coding. An alternative was that the participants would
simply memorize locations individually, with either constant variability around absolute accuracy or overall shifts
caused by the use of heuristics. To preview, we found more
evidence for the latter than for the former possibility. In
Experiment 3, we then investigated the use of perceptual
heuristics more directly, and in Experiment 4, we sought
to determine whether we could strengthen the acquisition
of categorical knowledge by changing the learning paradigm. Given that we continued to find more evidence for
perceptual than for categorical learning, in Experiment 5,
we asked whether providing reference information would
still improve performance by offering anchors for judgments, even though there might not be categories to be
“seeded.”
EXPERIMENT 1
Experiment 1 was designed to explore whether key
findings regarding cognitive representations of real-world
geography can be replicated in cases in which people are
learning hypothetical geography. Several prior studies
have reported that people are able to learn from artificial
maps (e.g., Clayton & Habibi, 1991; McNamara, Hardy, &
Hirtle, 1989; Newcombe et al., 1999; Thorndyke, 1981).
However, many of these studies have involved maps of
small-scale spaces, such as room layouts or building interiors. In this research, our aim was to investigate spatial
learning in which maps of an extensive area (i.e., a continent) were shown as part of learning about the climates,
people, and cultures of countries. We set up a continent
analogous to North America, creating three countries
whose locations roughly mapped to Canada, the United
States, and Mexico, in order to examine whether the bias
patterns found by Friedman and Brown in real geography
would appear in the hypothetical situation.
Method
Participants. Eighteen students from Temple University participated in Experiment 1. They were either graduate students who participated voluntarily or undergraduates who participated for partial
fulfillment of a course requirement.
Materials. A hypothetical map (19 cm high 3 23.5 cm wide on
the computer screen) with three countries and 12 target cities was
created to illustrate the relationships among these countries and cities (see Figure 1). The three countries were situated in the lower,
middle, and upper parts of the map. Six of 12 target cities were
located in the middle country, and 3 of 12 cities were located in both
the lower and the upper countries. A second map (see Figure 2) was
also created to illustrate the location of these countries relative to
the whole world. The second map was 21.5 cm (high)  14.5 cm
(wide), with 90º of latitude equal to 21 cm in height. On this map,
three latitude lines were presented: the equator (0º), the north pole
(90º), and the arctic circle (roughly 66.5º). The reason for using two
maps was to require the participants to learn generalizable location
information that was not dependent on the frame of the page. Our
aim was to simulate the process of learning locations of cities and
countries from a variety of different graphic displays. Integrating
across such displays requires inferential processes.
The participants learned about these cities and countries by reading a display program with illustrated texts, pictures, and maps indicating the capital city, climates, industries, and famous places for
the countries and cities. This information was created and controlled
by a Superlab Pro program.
The participants were tested using a grid pattern (18.5 cm high
3 26 cm wide), generated by a computer program created using the
C11 programming language. The grid pattern showed lines at 10º
increments, with latitudes ranging from 0º (the equator) to 90º north
(the north pole) and longitudes ranging from 40º west to 160º west
(see Figure 3). In the real world, this grid would roughly cover the
area of North America.
Procedure. The participants were asked to sit at a PC computer
terminal and to follow the display program presented on the computer screen, which would lead them on geographical tours of the
three hypothetical countries and 12 target cities. In this experiment,
all the participants pretended that they lived in the capital city of the
middle country and started the tour from there. The participants were
asked to learn 3 cities at a time by following the display program,
which presented them with information about climate, industries,
and famous places in these cities. The main map, as shown in Figure 1, was presented in the display program asking the participants
to locate a particular city every time when they finished the textual
information with pictures for that city, and the second map, as shown
in Figure 2, was also presented in the display program every time
when they finished learning the first city in a new country. After 3
cities had been learned, the participants were tested with a grid task,
which asked them to estimate the locations of 12 target cities. The
participants were told that they could make an educated guess concerning the cities that they had not learned yet. The order of learning
was fixed, beginning with 3 cities in the middle (or home country),
followed by the other 3 cities in that country, the 3 cities in the lower
country, and finally, the 3 cities in the upper country. Thus, learning
was categorically grouped.
In the grid task, the participants first saw the name of a city presented at the center of the computer screen. The participants were
told that they were required to press the space bar when they were
ready to estimate the location of that city. After the space bar had
been pressed, a grid pattern with latitude and longitude numbers was
shown to the participants. They were told that all three countries and
898 Newcombe and Chiang
Figure 1. Hypothetical map with three countries and 12 target cities used to illustrate the relations among countries
and cities.
cities would fall on this grid. The participants were informed about
the mapping between the easternmost and westernmost points on
the main map and the corresponding grid. The participants were
also directed to pay attention to the latitude numbers shown on the
grid and were told to infer the north–south location of the city on the
basis of the numbers. The participants were asked to move an “X”
on the computer screen by moving the mouse to indicate the location
where they thought the city would belong on a real map. A red dot
with a 2-mm diameter would show up when the participants pressed
the left button of the mouse to indicate the location of the city. The
participants were allowed to make changes on the location of the
red dot when they pressed the left button of the mouse again. After
the estimation was finished, they were required to press the right
button of the mouse to go to the next trial. The participants were not
provided any feedback about their performance. The procedure was
repeated four times until the trials for all 12 target cities in the three
countries were finished.
Results and Discussion
On the basis of box plots, five extreme outliers for latitude estimates and one extreme outlier for longitudes were
deleted from the data set. These outliers may have been
caused by the fact that the participants occasionally forgot
completely where the cities were and simply guessed. The
participants’ mean latitude and longitude estimates, as
well as the actual latitudes and longitudes, are presented
in Figure 4. These estimates come from performance in
the final grid task after all the cities had been learned.
The correlation (Spearman rho correlation) between actual longitudes and mean estimated longitudes was .986.
As Figure 4 shows, the estimates for longitudes were not
only ordinally accurate, but also, in most cases, very close
to the correct values. This fact is likely due to the fact that
success along this dimension could be based on figurative
memory. Mapping between the easternmost and westernmost points on the maps and on the test grid occurred directly, whereas, for latitudes, the participants had to infer
the northernmost and southernmost points of the continent by relating their figurative memory to the latitude
map. Confidence intervals across all participants for each
city indicated that the mean estimated longitudes were
not different from the actual longitudes for most of the
cities, except for very small westward biases for Roscommon, Hamersley, Limerick, and Armidale. Although these
biases were small, biases in longitude had not been expected, so this was somewhat surprising. However, the
same result did not appear in Experiment 2, so these data
should not be overinterpreted.
Learning Geographical Information 899
Figure 2. Second hypothetical map used to illustrate the locations of countries relative to the wider world.
The results for latitudes were quite different from
those for longitudes. For this dimension, the participants
had to encode values so that they could be transferred to
a different scale on the grid. That is, the participants had
to infer where the northernmost point and the southernmost point of the continent they had learned would fall
on the grid in order to respond correctly. Although the
correlation between actual latitudes and mean estimated
latitudes was .979, suggesting accuracy in ordinal terms,
the participants showed systematic biases, as Figure 4
shows. They placed cities in the upper country and the
northern part of the middle country further north than
they should have, and they placed cities in the lower
country further south. Confidence intervals across all
participants for each city indicated that the mean latitudes for all three cities in the upper country were significantly north of the actual latitudes and that the mean
estimated latitudes for two of the three cities in the lower
country were significantly south of the actual latitudes.
The mean estimated latitudes for southern cities of the
middle country (including Krefeld, Limerick, and Mycenae) were not different from the actual latitudes, but the
latitudes for the northern cities of the middle country (including Ciron, Oldham, and Tuscan) were significantly
further north than the actual latitudes.
In some ways, the pattern found in Experiment 1 fits
what Friedman and Brown (2000a, 2000b) found in realworld geography in terms of bias patterns. That is, in
general, the estimates for the upper country (which can
be mapped to Canada) are biased to the north, and the
estimates for the lower country (which can be mapped to
Mexico) are biased to the south, with some biases also
found for the middle country, possibly based on regional
division. However, the pattern in Experiment 1 does not
fit Friedman and Brown’s data in other ways. First, there
is no clear break across country lines. Although the difference between Matterhorn and Limerick may be somewhat exaggerated, no such tendency appears for Tuscan
900 Newcombe and Chiang
Figure 3. Grid pattern used in the testing phase.
and Roscommon. Second, the participants seem to have
differentiated latitudes about as much within a country
as across boundaries. To examine latitude differentiation
among cities within a country, we computed a regression
slope for the middle country, using actual latitudes to predict estimated latitudes. (Only cities in the middle country
were fitted with the regression, because with three cities
in the lower country and three cities in the upper country, there were too few data points to get reasonable estimates.) The results indicated a slope significantly larger
than zero [t(17) 5 5.97, p 5 .000]. Thus, cities were significantly differentiated within a country, unlike the pattern generally found in Friedman and Brown’s work on
real countries.
These aspects of the data suggest that categorical structure might not be the key to the observed biases. An alternative mechanism is that participants simply attempt to
preserve the ordering of the cities they learned, spreading
them out across the response grid in a fairly even way
that ignores the information given to them about latitude
landmarks, such as the equator and the arctic circle. We
will return to this possibility in Experiments 3 and 4, after
examining the generality and replicability of the data pattern in Experiment 2.
EXPERIMENT 2
Friedman, Kerkman, and Brown (2002) found that Albertans from Canada and Texans from the United States had
similar subjective representations of North American geography. That is, they divided North America into the same
number of regions and had similar biased patterns for cities
in those regions, regardless of where they lived (except that
the Canadians did not show a bias for Canadian cities). This
study indicates that judgment biases do not generally increase with increasing distance from people’s home city, as
a simple familiarity or proximity hypothesis would predict.
Friedman, Kerkman, and Brown (2002) argued that Albertans and Texans may share similar geographical beliefs
based on common social or cultural knowledge. However,
recently, Friedman et al. (2005) have reported that Mexicans show a categorical organization of North America that
is different from that of Canadians or Americans.
In Experiment 2, our aim was to replicate the basic
findings of Experiment 1 and to evaluate whether initial
geographical learning from text and photos is affected by
one’s point of departure. Thus, we added groups of people
who began learning with the capital city of the lower or the
upper country and imagined they lived there.
Learning Geographical Information 901
Adults‘ Mean Estimated Latitudes in Experiment 1
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Figure 4. Adults’ mean estimated latitudes and longitudes in Experiment 1. For
latitude estimates, the cities are ordered on the x-axis, beginning with the three cities in the lower country, followed by the six cities in the middle country, and then the
three cities in the upper country. Cities within a country are ordered by their actual
latitudes. For longitude estimates, the cities are ordered on the x-axis by their actual
longitudes.
Method
Participants. Thirty-six undergraduate students from Temple
University participated in this experiment for partial fulfillment of
a course requirement.
Materials and Design. The same stimuli as those in Experiment 1 were used. However, half of the participants pretended that
they lived in the capital city of the lower country and started the geographical tour from there, whereas the other half pretended that they
lived in the capital city of the upper country and started the tour from
there. For the participants who started the tour from the lower country, half of them traveled to the upper country as their second country
in the tour, whereas the other half traveled to the middle country as
their second country in the tour. The same situation also applied to
the participants who started the tour from the upper country. Half
of them went to the lower country as their second country, whereas
the other half went to the middle country as their second country.
The same procedure as that in Experiment 1 was used, except for
changes in the order in which triads of cities were learned.
Results and Discussion
On the basis of box plots, one outlier for longitudes in
the group who started the tour from the lower country was
deleted, as were two outliers for longitudes and one outlier
for latitudes in the group who started the tour from the
upper country. As in Experiment 1, these extreme outliers may have been caused by the fact that the participants
sometimes totally forgot where the cities were and simply
guessed.
902 Newcombe and Chiang
Adults‘ Mean Estimated Latitudes in Experiment 2
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Adults‘ Mean Estimated Longitudes in Experiment 2
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Figure 5. Adults’ mean estimated latitudes and longitudes in Experiment 2. md,
middle country; lw, lower country; up, upper country.
The results for Experiment 2 are presented in Figure 5.
The Spearman rho correlation between actual latitudes
and estimated latitudes for the group who was pretending
to live in the lower country was .972, and the correlation
for this group between actual longitudes and estimated
longitudes was .958. Confidence intervals for latitude estimates across all participants pretending to live in the lower
country indicated that all three cities in the upper country
were placed significantly north of the actual latitudes and
that the mean estimated latitude for one of the three cities (Frasca) in the lower country was significantly south
of the actual latitudes. The latitudes for the northern cities of the middle country (including Ciron, ­Oldham, and
Tuscan) were biased to the north of the actual latitudes.
The southern cities of the middle country were not biased,
except that Limerick was placed north of the actual lati-
tude. Confidence intervals for longitude estimates across
all participants for this group indicated that the deviation
cities were Frasca, Krefeld, Matterhorn, and Roscommon.
However, there were no predicted patterns for biases in
longitude estimates.
The Spearman rho correlation for the group who was
pretending to live in the upper country between actual
latitudes and estimated latitudes was .993, and the correlation for this group between actual longitudes and estimated longitudes was 1.00. Confidence intervals across
all participants pretending to live in the upper country indicated that latitudes for two of the three cities (including
­Hamersley and Weimar) in the upper country were significantly north of the actual latitudes and that the mean
estimated latitudes for two of the three cities (including
Frasca and Armidale) in the lower country were signifi-
Learning Geographical Information 903
cantly south of the actual latitudes. The mean estimated
latitudes for cities in the middle country were not different
from the actual latitudes, except for the northernmost city
of Tuscan. In addition, confidence intervals for longitude
estimates indicated that the deviation cities were Armidale
and Hamersley.
Thus, the pattern for both groups in Experiment 2 was
very similar to that shown in the data from Experiment 1,
although fewer of the contrasts with actual latitudes were
individually significant. When the results from this experiment were combined with the results from Experiment 1,
the patterns of performance for the three groups were
similar, as Figure 5 shows. An ANOVA for latitude estimates showed no differences depending on home country
[F(2,45) 5 1.159, MSe 5 333.715, p 5 .323]. In addition,
there were no interactions between the three groups and
the specific cities, suggesting that there was no more or
less bias in one group than in another.
In sum, Experiment 2 replicated Experiment 1, suggesting that which country was considered the home country
was irrelevant to learning. The similar patterns of data also
suggest that the amount of overlearning did not affect the
results, because the groups differed in how often the various sets of cities were practiced. In addition, because the
participants in Experiment 2 were entirely undergraduates
receiving credit for participation, the data indicate that the
results of Experiment 1 were not specific to participants
(such as graduate students) who approach the learning
task with motivation and accomplished study skills.
Across the three groups, it seems that people tended to
have more substantial biases for the northern cities than
for the southern cities. Quantifying this comparison by
calculating effect sizes showed that effect sizes (using a
d statistic) for the three southernmost cities ranged from
0.6 to 1.06 with a mean of 0.8, whereas the effect sizes for
the three northernmost cities ranged from 0.7 to 1.81 with
a mean of 1.3.
Although these patterns of bias suggest the possible operation of categorical processes, as in Experiment 1, there
were no pronounced breaks across country borders, suggesting that the biases may have arisen more from shallow
learning and the use of perceptual heuristics than from categorical learning. Also, as in Experiment 1, there were no
consistent differences between adjacent cities in separate
countries that would support the operation of categorical
processing; one pair, but not the other, showed an exaggeration in degree of separation. We again examined whether
there were latitude differentiations among cities within a
country by computing regression slopes, using actual latitudes to predict estimated latitudes for the middle country.
For the participants who started from the lower country,
slopes were significantly larger than zero [t(17) 5 7.09,
p 5 .000], and the same was true for those who started
from the upper country [t(17) 5 8.82, p 5 .000]. The
results again indicated that latitude estimates for cities
within a country were significantly differentiated.
It may be argued that simply analyzing latitude estimates is not the most powerful way of examining these
data. Absolute and signed errors might provide a more
sensitive index of the participants’ judgments. For ab-
solute errors in Experiment 1 and for the two groups in
Experiment 2, a mixed two-way ANOVA (3 countries
3 3 groups) showed a significant effect for countries
[F(2,102) 5 55.137, MSe 5 1,088.541, p 5 .000], no effect for groups [F(2,51) 5 1.155, MSe 5 35.082, p 5 .323],
and no interaction [F(4,102) 5 0.592, p 5 .669]. Post hoc
comparisons indicated that there was a significant difference between the upper (M 5 14.12) and the middle (M 5
8.14) countries and a significant significance between the
middle (M 5 8.14) and the lower (M 5 5.33) countries.
This analysis basically shows that the northward bias is
more pronounced than the southward bias, as was also
shown by the effect sizes already reported.
For signed errors, there was also a significant effect
for countries [F(2,102) 5 98.419, MSe 5 3,133.736,
p 5 .000] no effect for groups [F(2,51) 5 0.708, MSe 5
76.479, p 5 .498], and no interaction [F(4,102) 5 2.164,
p 5 .078]. Post hoc comparisons indicated a significant difference between the upper (M 5 12.00) and the
middle (M 5 4.88) countries and a significant difference between the middle (M 5 4.88) and the lower (M 5
23.22) countries. This analysis supports the conclusion
that there is a substantial northward bias for the upper
country and a smaller but reliable southward bias for the
lower country.
To characterize the consistency of the distortions across
participants in Experiments 1 and 2, each participant’s
signed errors were predicted from actual latitudes, using
regression. The results showed that 51 of 54 total participants in the three groups showed positive regression
slopes. The range of slope coefficients was from 20.161
to 1.4. These results suggested that the results for individual participants were generally consistent in their patterns
of distortion with those for the group data.
EXPERIMENT 3
Experiments 1 and 2 showed bias patterns reminiscent
of those observed with North America by Friedman and
Brown (2000a, 2000b), but with a more even overall pattern of estimates, lacking the between-country differentiation and the within-country homogeneity that they found.
In Experiment 3, we sought to assess whether simple
perceptual heuristics might be producing the biases observed in Experiments 1 and 2. Specifically, we situated
our countries further north overall (see Figure 6) in order
to assess whether learning and responding are primarily
affected by figurative factors. Participants learning geography from texts and pictures such as ours might focus
primarily on learning ordinal information and then simply
spread their ordinal estimates over the available response
space. If so, in Experiment 3, they should show a weaker
northward bias and a stronger southward bias, because
the response space offers more room for northward migration than was previously available and more room for
southward migration. Essentially, the participants may be
neglecting the landmark information in their responses,
failing to relate what they learn to landmarks such as the
equator or the arctic circle.
904 Newcombe and Chiang
Figure 6. The original second map was moved up to a new position in Experiment 3.
Method
Participants. Eighteen undergraduate students from Temple University participated in this study for partial fulfillment of a course
requirement.
Materials and Design. The same stimuli were used, except that
the second map used to illustrate latitude information was changed
as shown in Figure 6. In this new map, the arctic circle was located
just above the capital city of the upper country. All of the participants
pretended that they lived in the capital city of the middle country
and started the tour from there. Half of the participants received the
lower country as their second country for the tour, whereas the other
half received the upper country as their second country for the tour.
Procedure. The same procedure as that in the previous experiments was used.
Results and Discussion
On the basis of the box plots, one extreme outlier for
latitudes and two extreme outliers for longitudes were
deleted. The Spearman rho correlations for this experiment between actual latitudes and estimated latitudes was
.979, and the correlation between actual longitudes and
estimated longitudes was .951. Confidence intervals for
longitude estimates indicated that the deviation cities were
Hamersley and Matterhorn.
Because the participants’ mean estimated longitudes
remained accurate, only mean estimated latitudes are
shown in Figure 7, which reveals a pattern very different
from that seen in Experiments 1 and 2. Confidence intervals across all participants indicated that almost all the
estimates were significantly more south than they should
have been. The only exceptions were the mean estimate
for Roscommon, the mean estimate for Hamersley, which
had the arctic circle just above it and was located accurately, and the mean estimate for Weimar, the northernmost city, which was estimated as significantly north of its
actual latitude. In fact, the mean latitude estimates for Experiments 1 and 3 did not significantly differ [F(1,27) 5
0.044, MSe 5 252.303, p 5 .835], as they should have if
Learning Geographical Information 905
Adults‘ Mean Estimated Latitudes With the Second Map Moved
Up to the New Position in Experiments 3 & 4
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Figure 7. Adults’ mean estimated latitudes in Experiments 3 and 4 (with the second
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the participants were using the second map to place their
geographic learning in a global context.
This data pattern suggests that the participants might
simply have evened out the space shown on the grid and
then placed some cities at the north, some cities in the
middle, and some cities at the south. That is, they might
simply have used their figurative memory of the first map
as a base for the grid task, without taking the subsequent
information provided about placement on the globe adequately into account. This interpretation is supported by
the fact that, yet again, as in Experiments 1 and 2, there
were no pronounced breaks across country borders, also
suggesting that biases may have arisen more from perceptual factors than from categorical learning.
We again examined latitude differentiation among cities
within a country by computing regression slope as in Experiments 1 and 2. The results indicated that the slope was
significantly larger than zero [t(17) 5 12.648, p 5 .000].
Therefore, across experiments, it was consistent that there
was differentiation among cities within a country.
EXPERIMENT 4
Because Experiment 3 suggested that geographic learning in the circumstances of these experiments is basically
shallow, in Experiment 4 we made several changes to
our procedure, in an effort to induce categorical coding.
First, we changed the map so that the three countries were
906 Newcombe and Chiang
shown in distinctively different colors. Second, we added
material to our narratives. Friedman & Brown (2000a,
2000b; Friedman, Brown, & McGaffey, 2002; Friedman,
Kerkman, & Brown, 2002) have pointed out several factors that cause people to associate or “align” distant geographical regions with one another—namely, climate, political or cultural similarity, or physical attributes, such as
mountains. We emphasized climate, adding material to the
text that the participants read in which the middle country
was in the temperate zone, the lower country had hotter
weather, and the upper country had a colder climate. Quizzes on the climate information were also added to ensure
that the participants attended to this information.
Method
Participants. Two groups with 18 undergraduate students each participated in this study for partial fulfillment of a course requirement.
Materials and Design. The same basic stimuli as those in Experiment 1 were used for one group (with the second map in the
original position), and stimuli from Experiment 3 were used for the
other group (with the second map moved up to a more northerly
position). However, countries were shown with backgrounds of a
different color, material was added to the narratives to emphasize
climate differences among the countries and cities in line with their
latitudes, and three quizzes regarding climate information were
added, for which the participants received feedback. All the participants pretended that they lived in the middle country and started the
tour from there. As in the previous experiments, half of them traveled to the lower country as their second country, and the other half
traveled to the upper country as their second country.
Procedure. The same procedure as that in the previous experiments was used.
Results and Discussion
On the basis of box plots, three extreme outliers for
latitudes and two extreme outliers for longitudes in the
group with the second map in the original position were
deleted, and three extreme outliers for latitudes and two
extreme outliers for longitudes in the group with the second map moved up to the new position were also deleted.
The results for Experiment 4 are shown in Figure 7. The
Spearman rho correlation between actual latitudes and estimated latitudes for the northerly group with the second
map moved up to the new position was .986, and the correlation between actual longitudes and estimated longitudes
for this group was .972. The correlation between actual
latitudes and estimated latitudes for the southerly group
with the second map in the original position was .986, and
the correlation for this group between actual longitudes
and estimated longitudes was .972. Confidence intervals
for longitude estimates of the northerly group indicated
that the deviation cities were Hamersley and Roscommon;
the deviation cities were Armidale, Krefeld, Limerick, and
Oldham for the southerly group.
As Figure 7 shows, the data for latitude estimates for
the group using the materials of Experiments 1 and 2
are analogous to the data from those experiments, and
the latitude estimates for the group using materials from
Experiment 3 are similar to those seen in Experiment 3.
Although biases seemed somewhat smaller than those observed previously, this effect was not reliable [F(1,26) 5
0.075, MSe 5 401.506, p 5 .169, for the comparison of
the data for the southerly placed map with the data from
Experiment 1, and F(1,29) 5 0.075, MSe 5 127.773, p 5
.787, for the comparison of people seeing the northerly
placed map with those in Experiment 3]. Confidence intervals for the southerly group indicated that mean latitude estimates were shifted significantly southward for
the cities of Frasca and Matterhorn in the lower country,
significantly northward for the cities of Ciron and Tuscan in the middle country, and significantly northward
for the cities of Roscommon, Hamersley, and Weimar in
the upper country. For the northerly group, confidence
intervals showed that mean latitude estimates were significantly shifted north for all the cities except three cities
in the upper country.
We again saw no consistent pattern of between-­country
breaks and within-country homogeneity. Therefore, overall, it appears that the efforts to increase conceptual processing and categorical organization by the use of color
coding and requiring attention to climate information
were not effective. Using a regression slope to examine the differentiation among cities within a country, we
found that across participants, the regression slope was
significantly larger than zero [t(17) 5 19.19, p 5 .000,
for the northerly group; t(17) 5 17.459, p 5 .000, for the
southerly group].
EXPERIMENT 5
Friedman and Brown (2000a, 2000b) found that people’s overall knowledge of geography was profoundly
improved by learning the locations of several seed cities.
Seeds not only improved people’s geographical knowledge in physically adjacent regions, but also advanced
people’s knowledge in conceptually coordinated regions.
Kerkman, Friedman, Brown, Stea, and Carmichael (2003)
also found that children benefited from seeing seeds on
a two-dimensional grid map of a continent. Brown and
Siegler (2001) argued that “seeds are not anchors,”—that
is, that the additional information acts by affecting the
categorical structure of people’s knowledge, rather than
by simply providing a few correct reference points with
respect to which other values are estimated.
In our learning situation, we did not find much evidence of categorical organization. An applied question
then is whether providing some reference information can
still work to improve spatial location estimates, perhaps
by simply providing anchors by which to organize the
ordinal-level information that the participants apparently
focused on. That is, perhaps reference cities need not be
seeds to work; they can also be anchors. Theoretically, the
issue is whether effects of reference information are diagnostic of categorical organization. In this experiment,
we explored whether incorrect latitude estimates of cities
could be corrected and updated when people were offered
correct placements for two cities on the grid.
Method
Participants. Eighteen undergraduate students from Temple University participated in this study for partial fulfillment of a course
requirement.
Learning Geographical Information 907
Materials and Design. The same stimuli were used, except that
in the grid task, two chosen seed cities, Frasca (the capital city of the
lower country) and Hamersley (the capital city of the upper country), were presented with the grid in every trial. All the participants
pretended that they lived in the capital city of the middle country
and started the tour from there. Half of them traveled to the lower
country as their second country, whereas the other half traveled to
the upper country as their second country.
Procedure. The same procedure as that in the previous experiments was used.
Results and Discussion
The Spearman rho correlation between actual latitudes
and estimated latitudes in this experiment was .988, and
the correlation between actual longitudes and estimated
longitudes was .976. Confidence intervals for longitude
estimates indicated that the deviation cities were Krefeld,
Limerick, Mycenae, and Oldham.
The latitude results for Experiment 5 are presented in
Figure 8. The participants’ latitude estimates were much
improved over those seen in Experiments 1 and 2 and were
close to the actual latitudes. Confidence intervals across
participants indicated that their mean latitude estimates
were not different from actual latitudes for most cities,
except for the existence of small biases for the cities of
Krefeld, Mycenae, and Weimar. There was again the differentiation among cities within a country: The results
indicated a regression slope significantly larger than zero
[t(17) 5 17.459, p 5 .000].
Thus, the seeding paradigm is indeed a powerful mechanism with which people may improve their performance
in this situation. However, given the fact that people were
likely using perceptual heuristics to organize their location recall, it is probable that providing two correct cities acted to improve performance more as anchors than
as seeds. The effectiveness of the anchors reinforces the
conclusion that the participants in these experiments were
not attending closely to latitude information and were, in-
stead, simply spreading their ordinal knowledge across
the available response space.
Future study might explore whether the improvement
created by such anchors endures over time. Brown and
Siegler (1996) did find such a long-term effect in their
work on people’s estimates of population sizes, with benefits apparent even after 4 months. An additional question
for future research might be the effectiveness of anchors
taken from less extreme ends of the continuum than were
the two cities we used as anchors in this study. Two cities from the middle country would establish a metric that
might be useful but might not anchor the distribution of
cities overall as effectively if it is vital for participants to
receive information regarding endpoints.
GENERAL DISCUSSION
This article reports a first attempt to use hypothetical
geography to study individuals’ mental representations of
geographical spaces. Experiments 1 and 2 initially suggested some parallels to findings with real geography.
First, people’s estimates for cities in the upper country
were biased to the north, and their estimates for cities
in the lower country were biased to the south. Second,
people’s geographical representations did not depend on
which area they were trained on first and were asked to
consider as their home. However, the data were inconsistent with the real-geography findings in that there were
no consistent categorical breaks between countries, and
there was also evidence of reliable within-country differentiation. Although not definitive, these observations
suggested that the students in our learning situation might
not be forming strong categorical representations of the
kind observed with real-world locations. Experiments
3 and 4 provided clearer support for the conclusion that
the participants in this learning situation relied primarily
on figurative memory and perceptual heuristics. In Ex-
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Figure 8. Adults’ mean estimated latitudes after seeding in Experiment 5.
908 Newcombe and Chiang
periment 3, shifting our continent northward markedly
affected the nature of the biases we observed, in a fashion consistent with the idea that people concentrate on
ordinal ranking of cities along the north–south dimension
but do not integrate their figurative memory of the first
map with the location information available only on the
second map. In Experiment 4, manipulations that should
have strengthened the participants’ categorical organization had no effect on estimates, which showed the same
patterns as those observed in the previous experiments.
Finally, despite the lack of categorically based organization, Experiment 5 showed that the provision of two correctly placed locations allowed people to place other cities
with excellent accuracy, likely because the information
provided anchored the ordinal information that people had
encoded.
The data from these experiments are not inconsistent
with those from prior work. In past research implicating
categorical organization of locations, either knowledge of
real-world geography has been examined (the Friedman
& Brown studies; Hirtle & Jonides, 1985; Newcombe &
Liben, 1982; Stevens & Coupe, 1978, Experiment 1), or
simple small-scale spaces organized implicitly or explicitly by horizontal and vertical axes have been dealt with
(Huttenlocher et al., 1991; Stevens & Coupe 1978, Experiments 2 and 3). We see our work as opening up a new
array of questions concerning the nature of the learning
of complex spatial material interwoven with nonspatial
facts. Overall, these experiments suggest that “book learning” of geography is likely to be much more figurative and
much less categorical than knowledge of real geography,
which is gained partly from text read and thought about
over many years, as well as from film, TV shows, conversation, and actual travel.
What are the crucial differences between initial exposure to geographical information and the knowledge we
have of the real world? One obvious candidate is travel,
which might be expected to provide vivid experiences
that lead to more robust categorization of countries and
regions. Unfortunately, however, there is no definitive
evidence that travel improves the accuracy or organization of geographical knowledge independently of other
factors with which it is naturally correlated, such as age,
interest, or socioeconomic class. Correlational analyses
have sometimes shown that there are relations of travel
with other factors controlled (Rutland, 1998), but contrary results have also been reported (Bourchier, Barrett,
& Lyons, 2002).
A second possibility for why real-world geographic
knowledge is more categorical than the learning that the
participants showed in the present experiments is that formation of geographical categories may require the slow accumulation of more facts and stereotypes about countries
and regions than we were able to provide in our materials.
For example, Americans likely learn about Mexico from a
variety of movies, music, and newspaper articles as much
as they learn about the country in more formal schoolbased geography classes. In fact, the differences between
Mexicans and Americans in regional organization of their
respective countries found by Friedman et al. (2005) sug-
gest the possible importance of such processes. The fact
that children begin to show categorical organization of geography around the middle school years ­(Kerkman et al.,
2003) is consistent with the hypothesis that learning a rich
array of facts and stereotypes supports the development of
this kind of representation.
The present data have implications for the effective
teaching of geography. The pessimistic conclusion is that
it is very difficult to support learners in building wellcalibrated representations of the physical world, because
people are prone to forming figurative memories that do
not deeply integrate across two mapping representations.
Although it is possible that children or adolescents learning in school are more motivated to deep processing than
were the participants in our experiments, the relatively
low level of geographical knowledge found in surveys of
the American public would argue that shallow processing may be common. If so, our data stand as a challenge
to geography educators to devise methods for inducing
deeper processing. Our materials could possibly provide a
technique for evaluating proposed methods in a way that
would be independent of confounds from varying preexisting knowledge of the real world. In addition, future
work could examine children’s acquisition of geographical knowledge in the course of school-based exposure.
Overall, relatively little research in cognitive psychology and cognitive development has examined the acquisition of geographical information, especially under
well-controlled conditions. Given the importance of such
knowledge to being a well-prepared citizen of the modern
world, understanding how to help support spatial learning
and reasoning in this context should be an important goal
of future research.
Author Note
This research was supported by grants from the National Science
Foundation (EHR/ROLE 0087516 and 0337360). Address all correspondence to N. S. Newcombe, Department of Psychology, Temple University, 1701 N. 13th Street, Philadelphia, PA 19122 (e-mail: newcombe@
temple.edu).
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