Data Visualization: Preference and Use of
Two-Dimensional and Three-Dimensional Graphs
SAMUEL H. FISHER III
JOHN V. DEMPSEY
ROBERT T. MAROUSKY
University of South Alabama
study considered the interplay of simple versus perspective graphical information on aesthetic
preference, instructional effectiveness, and retention. Students in an introductory U.S. government
course were presented with examples of 2-D and 3-D graphs and asked to choose which was pleasing
to the eye and which was most useful in answering questions about the graph’s content. The results of
this study indicated that when visual appeal was the only criterion, subject choices overall were
approximately evenly matched. When subjects were required to extract information from graphs, they
used simple graphs almost 3 times more often than elaborate graphs. Information drawn from bar and
circle graphs was extracted more accurately than the other three types of graphs.
This
Keywords: data visualization, graphing, charts, datagraphics
that
11 of us, students and teachers,
inundated with so much information in printed form
and retention are becoming a hectic exercise in separating the substantive from the decorative. Just the increase in information itself has
contributed to what Wurman (1990) has referred to as &dquo;information anxiety.&dquo; For example,
more than a decade ago, famed data/graphic designer Edward Tufte (1983, p. 10) estimated
that each year, 900 billion images of statistical graphics are printed. Given the enormous
increase in technological wherewithal in that period, that estimate should have increased
exponentially. This trend is surely accelerating with the popularity of Web sites on the
Internet. And not surprisingly, the use of statistical graphs has become common in introductory U.S. government texts.
In spite of the magnitude of this graphical activity, few research-based guidelines exist
concerning ways to present graphical information to learners other than to assert unequivocally that 2-D graphs should be used. A manual for the popular statistical analysis program
SYSTAT, for instance, states that, &dquo;We cannot think of a single instance in which a
perspective [3-D] bar graph should be used.&dquo; Later the authors of this manual concede, &dquo;You
may have noticed that SYSTAT has a full assortment of 3-D graphs. We had to make some
[their italics] concession to the marketplace. Nevertheless, before you use them, please
consider 2-D alternatives&dquo; (SYSTAT, Inc., 1992, p. 19).
One fascinating designation in SYSTAT’s clear recommendation is the phrase, &dquo;concession to the marketplace.&dquo; An underlying assumption in the use of 3-D graphs for students in
are
comprehension, learning,
AUTHORS’ NOTE: Research for this article
Research Council.
was
supported by a grant from the Umversity of South Alabama
Social Science Computer Review, Vol 15 No 3, Fall 1997 256-263
© 1997 Sage Publications, Inc
256
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science courses is that the graphs’ visual appeal will generate increased student
interest and retention of course material. The unanswered question in this process, however,
is do students, who presumably are the reason graphical displays are made in the first place,
really like 3-D graphs, and will they use them to respond to questions about quantitative
data?
In essence, the controversy regarding whether or not to use 3-D graphs, then, seems to
be between the advocates of the &dquo;less is more&dquo; dictum and those who look for more
&dquo;prominence&dquo; or projection in their graphical displays. As with other areas of instructional
technology, designers, given more powerful tools and capabilities, are faced with the basic
paradox-embellishment versus embodiment.
With respect to graphical displays, Cleveland (1985), for example, would place the
elements of volume and color hue or density (distinguishing features of perspective graphs)
along the &dquo;worse&dquo; end of the graphical elements hierarchy. Several questions arise in regard
to this argument. Are simple graphs always better? Does it really matter if learners use
perspective graphs? What do learners prefer to use? Do their preferences change based on
their need to use the information contained in the graphical displays? How do the graphical
display types interact with recall and retention? The ideal of instruction using graphical
displays is to present or have the student construct information in such a way that the learner
will most easily be able to use and remember the data. Answers to the questions above will
help in the construction of graphs that more closely and consistently reach the ideal.
It is generally agreed from an information processing perspective that graphical displays
are passed through the visual receptors of the retina and briefly stored in the iconic memory.
From there it is passed to the short-term memory, which Miller (1956), in his classic article,
suggests is limited to a modest number of &dquo;chunks&dquo; of information. The short-term memory
allows time for encoding into long-term memory (in the form of schemata), where it is
thought to be4’permanently&dquo; stored assuming no physiological damage takes place in the
brain.
On the surface, it would appear that information should be presented in such a way that
it is most simply assimilated into short-term memory. Perspective, or 3-D, graphs have more
nonessentials and logically should require a more involved chunking process. In addition, it
is to be expected that an increase in visual illusions (Coren & Girgus, 1978; Gregory, 1969;
Jahnel, 1952) entering the iconic memory would arise with the use of perspective graphs.
Some knowledgeable theorists and practitioners see value in perspective graphs and
charts. For example, C. F. Schmidt (1983), a highly respected authority on the design of
statistical graphics, challenges those who would abandon 3-D charts. &dquo;Such a view is
shortsighted and self-defeating since 3-D charts, when properly designed and executed, do
have a significant role to play in statistical graphics.&dquo; Although admitting that an increase in
skill and experience is necessary to prepare acceptable 3-D charts, he protests that inferior
3-D charts &dquo;are basically attributable to the ignorance and incompetence of the chartmaker,
not the type or character of the chart per se&dquo; (p. 154).
Undeniably, there are innate differences among different types of graphical displays. As
long ago as the 1930s, for example, Croxton and Stein (1932) found that comparative
judgments regarding size were more accurate for bar charts than circles and squares. Even
so, all types of graphs and charts are used daily in such a way that perception is distorted
because of unskillful design or, worse, purposely deceptive graphing. Many of these
misrepresentations are the result of violations of what Norman (1993) refers to as the
appropriateness principle, that is, &dquo;The representation used by the artifact should provide
exactly the information acceptable to the task ... neither more nor less&dquo; (p. 97). The ready
availability of 3-D graphical displays in off-the-shelf statistical programs and the increasing
political
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258
visual
sophistication of learners only serve to confound designers’ efforts to follow the
appropriateness principle. In the present study, our goal was to provide some practical
information that may be of use to those faced with the thorny question of which tool to
employ in order to show numerical comparisons or illustrate trends.
SPECIFIC AIMS
Specifically, we wish to consider the interplay of simple versus perspective graphical
information (in essence, embodiment versus embellishment) on aesthetic preference, instructional effectiveness, and retention. Consistent with common usage, the terms &dquo;graphs&dquo; and
&dquo;charts&dquo; are used interchangeably in this study (e.g., a pie chart is also referred to as a circle
graph). The five types of graphical displays used in this study were chosen because they are
among those commonly available microcomputer-based statistical software packages.
Accordingly, this study addressed five major questions using five types of graphs.
1.Are 2-D or 3-D graphs preferred when it is not required that the viewer extract information from
the graph? [visual preference]
2. Are 2-D or 3-D graphs used when the viewer must extract information from the graph to answer
content-related questions? [use preference]
3. Do students answer content questions better when using one type of graphical display rather
than another type?
4. Was there a difference between students who used simple graphs versus elaborate ones?
5. Which graphical displays promote retention?
METHODS
Undergraduate students taking an introductory U.S. government course, primarily freshand sophomores, were subjects in this experiment. Most of the students were not
political science majors but were taking the course to fulfill a college core requirement.
Participation in the experiment was voluntary; however, subjects did receive extra credit for
participation. Sixty students participated in the first part of the experiment concerning
preference and instructional effectiveness. Forty-six of these subjects chose to take the
retention test (administered at a later time).’1
The graphical information, an analysis of the voting behavior of Congress’s Conservative
Coalition, used in this study was taken from material that was normally presented in this
course. Data on the Conservative Coalition’s voting behavior between 1976 and 1984 is used
to present different graph styles. The fact that the data was not current or well-known to firstand second-year students meant that whatever they recall is from the charts and not a guess
based on previous knowledge of the Conservative Coalition.
Five types of common graphical displays were used to present the voting patterns over
time. These were mixed bar/line, floating line, layered line, pie (circle graph), and bar.
Consistent with what message design theorists (Wertheimer, 1938; Winn, 1992) consider to
be good practice, materials presented by line graphs, illustrated trends, and bar and circle
graphs showed comparisons. (To limit overload in the short-term memory, information was
chunked in such a way that all graphs had five main parts or features, for example, five pieces
of the pie in a circle graph.) As much as possible, the printed graphical displays were
presented so that both simple and perspective charts were as clear as possible. All materials
were displayed with black ink on opaque white paper (see Figure 1).
men
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259
Figure 1: Graph Examples
First, we asked students to view 40 matched charts (20 simple/20 elaborate) (e.g., 2-D
bar graph and 3-D bar graph) and indicate which of each pair they liked the most (or
which was most pleasing to them). After the students answered these questions, the
materials were collected. Next, we passed out a packet with the same 40 charts in a
different order. Underneath each pair of charts were two questions. The first question
concerned the substantive content of the charts. The second question asked which chart the
students used to answer the content question. Then, these materials were collected. Four days
later, a retention test, on the same content, but without the use of graphical displays, was
administered.
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260
RESULTS
When visual appeal or preference was the only criterion, subject choices overall were
rather evenly matched. Slightly more than 50% of the subjects in this study (51.8%) chose
2-D charts, whereas 48.2% chose 3-D charts. This was somewhat counter to our expectations
based on the pilot study where we found the opposite.
Looking at specific chart types (each was presented four times), layered line charts
(50.8%, 2-D), pie charts (52.1%, 2-D), and bar graphs (52.9%, 2-D) closely followed this
pattern. Subjects’ preference for simpler (2-D) floating line charts was stronger (72.4%, 2-D).
On the other hand, a strong preference for 3-D mixed bar and line charts was observed.
Specifically, only 30.8% of the subjects preferred 2-D mixed bar/line chart.
Our second question was whether students would use simple (2-D) or elaborate (3-D)
graphs in answering content questions. Overall, when it was actually necessary to extract
information from the graphs to answer questions, students used simple graphs almost 3 times
more often (73.6%) than elaborate graphs (25.7%). As Table 1 indicates, the partiality for
2-D graphs in this respect was very strong for all graph types except circle (pie) graphs. A
Chi-square test of relationship among graphical displays and forms of graphs (2-D or 3-D)
was significant (xz = 77.80, p < .000) but indicated a weak relationship (Lambda = .05, p <
.05).
question was concerned with which types of graphs helped students
questions better. Overall, students in this study responded to 68.3% of the
content-based questions correctly. As Table 2 indicates, information from bar graphs (82.5%
correct) and pie charts (80% correct) was extracted more effectively than the other types of
graphs. A Chi-square test of relationship among the type of graphs used to answer content
questions and whether the correct answer was given was significant (x2 68.40, p < .000)
but indicated a weak relationship (Lambda .05, p < .05).
We were also interested to see if the percentage of correct answers from simple graphs
was greater than that for elaborate graphs. Overall, students using simple graphs answered
questions more correctly (69.9% correct) than those who answered using elaborate graphs
(64.9%), although the difference was not significant. As Table 3 indicates, the lowest
percentage of correct answers was rendered from the 3-D versions of floating line charts
(45.2% correct) and the layered line chart (46.3% correct). There were no significant
differences in any of the 2-D or 3-D comparisons for any of the graphical displays.
Finally, we wished to know which graphical displays were best for retention. Unfortunately, even though the content was related to class material, the overall retention was only
31.5% correct. The best retention score (40.2% correct) resulted from information originally
extracted from circle graphs. The worst retention resulted from information obtained through
Our third research
answer
content
=
=
bar charts
(28.8% correct).
IMPLICATIONS AND DISCUSSION
Most of the students did not like 3-D floating line graphs. They did like 3-D mixed bar
and line graphs more frequently. They were fairly even in preference of the other three types
of 2-D and 3-D graphs. Based on this study, there appears to be little reason to use floating
line charts where preference is a concern. Few individuals seem to like them for any reason.
It is no surprise, however, that a reasonable percentage of individuals of college age do have
a visual preference for other types of 3-D charts. Video games and stupendous television
graphical effects are the stuff of everyday life for most young people. This study was
purposely limited to black-and-white graphical displays to see if volume and shading alone,
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261
TABLE 1
Form of
Graph, 2-D or 3-D, Used to Answer Content Questions (percentages)
TABLE 2
Percentage of Correct Answers to Content Questions by Graph Type
TABLE 3
Percentage of Correct Answers to Content Questions
by Graph Type and Form of Graph, 2-D or 3-D
without full color, were sufficient to contribute to visual appeal. For almost half of the
subjects in this study, they were.
Students tended to use simpler (2-D) graphs much more frequently when it was necessary
to extract information from the graph. A preference for 2-D charts as a more efficient form
for answering questions about the content was in line with expectations. When it came to
actually using the graphs to extract information, subjects tended to look for the clearest
information giver, the 2-D graphs. The implication here is that, at least in the absence of
color, simple graphs are preferred much more frequently than perspective graphs when the
subjects had to actually use the information. Therefore, one would have to question why
designers should use black-and-white perspective graphs for instructional purposes. This is
not to suggest that they should never be employed for instruction, but, like a strong spice,
they should be used sparingly for most individuals.
Students tended to extract quantitative information more effectively from bar graphs and
circle graphs. The use of bar graphs for effective representation of data has been promoted
from many sources for some time (e.g., Hartley, 1987, p. 95). The finding of this study that
circle graphs (or pie charts) were also effective was surprising. Some experts have long
suggested that pie charts are less desirable because, among other reasons, they do not order
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262
the data and numbers
along a visual dimension (Bertin, 1983). Tufte (1983), never given to
understatement, sums up this opinion when he states, &dquo;The only worse design than a pie chart
is several of them&dquo; (p. 178). MacDonald-Ross (1977) is less skeptical yet still cautious about
the use of pie charts, &dquo;Grouped bars seem the safest bet with range-graded keyed circles and
pie charts as possibilities; but we still know too little about pie charts to feel entirely
comfortable at their widespread use&dquo; (p. 375). Perhaps, in this decade when abominations
such as 3-D floating line charts are not uncommon, circle graphs are comprehended more
easily by visually sophisticated young adults.
There was a larger percentage of correct answers from information obtained using 2-D
graphs than from 3-D graphs. When it came to abstracting information from a graph, the
results of this study support the notion that embellishment, in this case placing the chart in
three-dimensional form, does not more accurately or more effectively convey the visual
display’s data. Although there was a greater percentage of correct answers for simple than
for perspective graphs for all types of graphical displays, the differences were not significant.
CONCLUSIONS
indicate that simple or 2-D graphs are more effective for
information
than are 3-D graphs when using black ink on white
transmitting quantitative
results
of
the
retention
test were poor, this may be in part the consequence
the
paper. Although
of the experimental procedure and not lack of impact by the graph.
What is especially pertinent to the presentation of the graphical information, however, is
the broader issue of what questions graphs, charts, and other visual displays may be used to
answer. Bertin (1983) and Wainer (1992) have proposed a three-level model of graphicity:
(a) elementary questions involving data extraction, (b) intermediate questions involving
trends seen in parts of the data, and (c) overall-level questions involving an understanding
of the data’s deep structure. Another perspective would be to consider the types of information extracted from data to be rote, rule-driven, or evaluative. The poor retention of graphical
information in this study may be due in part to the level of graphicity, which in this and most
cases, was level one and two only.
Another explanation for the poor retention evident in this study when graphic displays
were used alone is information density. Graphs are a very information-dense system
compared with the verbal language of text (Brasell, 1990). Although much time and effort
can be saved viewing masses of data represented in graphical displays, the sheer amount of
data absorbed through this process may reduce the ability to retain the information without
the assistance of other media or symbol systems.
Political science has a wealth of quantitative information that is useful for describing and
explaining a wide range of concepts. It is important, therefore, to consider the potential
shortcomings that translation of text into graphs has on the success of learners’ comprehension and retention.
The results of this
study
NOTE
1. A pilot study was conducted with 19 students in an introductory U.S. government course. Results from this
study suggested that 2-D graphs are preferred over 3-D graphs. However, the pilot study did not include a retention
test.
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Samuel H. Fisher III is an associate professor of political science. Address: Department of Political
Science and Criminal Justice, University of South Alabama, Mobile, AL 36688. E-mail:
[email protected].
John V. Dempsey is an associate professor of behavioral studies and education technology at the University
of South Alabama. Address: College of Education, 3100 UCOMM, University of South Alabama, Mobile,
AL36688.E-mail:[email protected].
Marousky is a Ph.D. student in the Department of Behavioral Studies and Education Technology
of South Alabama. Address: College of Education, 3100 UCOMM, University of South Alabama,
Mobile, AL 36688. E-mail: [email protected].
Robert T.
at
the U.
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