A Critical Look at Graphics in Digital Environments 1

A Critical Look at Data Visualization in Digital Environments

Jennifer L. Steplowski

Purdue University

EDCI 51300

A Critical Look at Graphics in Digital Environments 2

Abstract

Forms of data visualization have been around since 1890, charting everything from traveled

paths to mortality rates. The recent rise of the “infographic” has turned topics of interest into

creative, clear, and beautiful depictions of data. But what does this mean for educational

technology and how do infographics impact the learner? Common uses for visuals include

making connections, simplifying complex methods that cannot be explained through text alone,

and inducing higher-level thinking. Yet, if done incorrectly, visuals can derail learning. Poorly

designed graphics can increase the burden of working memory onto the learner as explained by

John Sweller’s Cognitive Load Theory. This paper will examine the history and importance of

data visualizations, educational theories behind their creation, and examine their optimal use in

e-learning.

Keywords: e-learning, data visualization infographics, education

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Defining data visualization for education

Data visualization is a modern branch of descriptive statistics (Tufte, 1983), in which

information is communicated through graphic means. Common examples include bar or line

graphs, charts, scatter plots. While these methods can be helpful in understanding complex

quantitative information, not all learning incorporates data as its lone source. Understanding

concepts and their relationships is typically a goal of modern data visualization as well,

particularly in e-learning, where instruction is done remotely. Outside of data visualization,

related areas of study encompass information design, information architecture, and information

graphics, and are often used interchangeably. But how do they differ and does it matter?

Information graphics, or the more commonly referred to term, “infographics” first

appeared in Edward Tufte’s publication, The Visual Display of Quantitative Information. Tufte

explains “graphical displays” to serve many purposes, including:

• Showing the data

• Comparing different pieces of data

• Encouraging the viewer to think about the substance rather than about

methodology, graphic design, technology of graphic production, or something

else

• Serving a clear focus: description, exploration, tabulation or decoration (Tufte,

1983)

Alternatively, “information design” can be defined, according to the RIT Libraries Graphic

Design Archive as:

...understanding reader and user responses to written and visually presented information.

The kinds of problems addressed include legal documents, business forms, diagrams,

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transportation maps, charts, tables, instructional materials, wayfinding systems and

computerized information systems. The ability to understand and simplify complex

relationships is highly important. (Beardslee, 2014, p.1).

This term is more commonly used in the field of graphic design, and should not be discounted,

even when discussing within an educational-context. Each of these specialized areas has its own

set of nuances, but for the purposes of this paper, “data visualization" will be used as the general

term to describe them all.

Purpose

There is another key concept that is becoming more important in today’s culture and in

describing the 21st century learner—visual literacy. With the increasing availability of

technology and the ease with which graphics can be produced and accessed, visual literacy is a

new critical skill that is becoming progressively more necessary. Visual literacy is used in many

contexts, so the definition can vary. The most universal explanation can be found in a white

paper from January 2004, in which it is defined as "understanding how people perceive objects,

interpret what they see, and what they learn from them" (Elkins, 2010, p.2).

The abundance of graphics has made visual literacy more important. Historically, visual aids

would assist literacy as a form of storytelling or identification, but what about the more technical

infographic of today, where the audience has moved beyond those former interpretations-what is

their purpose? Scholarly reading points to a couple of key areas. Data visualization is used to:

• Clarify meaning

• Recognize patterns

• Reason qualitatively about physical processes

• Motivate the learner

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• Recall past knowledge

• Bridge experience and abstraction, and most importantly to

• Prompt higher-order thinking

These goals are attainable and several educational theories used in instructional design recognize

that. It is important to understand visual literacy as well as the history of data visualization as

they continue to play an important role for instructional designers.

The modern history of data visualization

Early forms of data visualization include diagrams, charts, graphs, and symbols as

pioneered by William Playfair and Otto Neurath (The History of Symbols: Isotype, 2012).

Modern mediums like animations, collaborative environments, and dynamic visualizations are

also being explored along with their impact on learning. Edward Tufte, the father of modern data

visualization, began his career in infographics as a statistician and has written numerous books

about information design. Tufte finds inspiration from old books and diagrams; he explains their

significance:

...their design, the beauty of their thinking—and I thought of them as a museum of

cognitive art where I looked for ideas exemplified, thinking exemplified, showing

exemplified. It’s general theory extended from books written over the past 1,200 years.

And in writing I am interested in conveying that forever knowledge…

(Tufte, "COMMENT> EDWARD TUFTE Eyes With a Mind of Their Own", 2011)

Though Tufte gained inspiration from older works, he’s also credited with bringing the term

“sparklines” into the mainstream. Sparklines are “design-simple, word-sized graphics” (Tufte,

2006, p. 54), but represent a departure from the purpose of a typical infographic. While this

easily digestible data visualization is useful for the information age (see Figure 1), they lack the

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breadth inherent in larger visualizations. Tufte believes that “The point of an infographic isn’t to

gain understanding at a glance. It’s to learn something,” (Johnston, 2011, p.4), but sp arklines

aren’t an infographic—they’re a means of educating the learner with an eye on the concept and

space at hand.

Another contemporary, Dr. Richard Mayer, mirrors this focus on education. Mayer

teaches at the University of California, Santa Barbara and has notably contributed the Cognitive

Theory of Multimedia Learning. According to UC, Santa Barbara’s website (2014), Mayer’s

“research is motivated by the question, ‘How can we help people learn in ways that allow them

to use what they have learned to solve new problems that they have never seen before?’" His

theory takes a practical look at the use of graphics in e-learning. When considering these key

players one may see the significance of their contributions to data visualization, but what is it

for? How are they tied together and what is the purpose of pictorial representation?

Placing data visualization within instructional design

David Merrill’s First Principles aim to enhance the quality of instruction and improve

student learning. The Activation Principle states that “instruction should have learners recall or

acquire a structure for organizing knowledge” and “instruction should activate relevant cognitive

structures in learners by having them recall… prior knowledge or experience”. (Reigeluth, 2012,

p. 76) This aligns with the context and symbolism in which infographics are used. For example,

if someone has not seen a Venn diagram, they will not understand that the overlap area of two

intersecting circles represents a shared set of characteristics. Similarly, if someone does not

know what the state of New York looks like, they may not understand the significance of a color-

code, which identifies it as a split-party state, as seen in Figure 2. Merrill’s Demonstration

Principle states that instruction should “provide a demonstration of the skill ...guidance that

A Critical Look at Graphics in Digital Environments 7

relates to the demonstration to generalities …[and] allow learners to observe the demonstration

through media that [is] appropriate to the content” (Reigeluth, 2012, p. 76). Demonstration can

happen in person, but is common to visualize using diagrams or video. This form of interactivity

and drawing on past knowledge allows the student to follow along with the instruction to

facilitate better cognition and understanding.

A common thread within current research is the focus on cognition and memory, and

their relevance in terms of the effectiveness of graphics in instruction. Defining Schema and

Cognitive Load Theory is critical to understanding this impact. Driscoll (2012) describes Schema

Theory as the storage of knowledge “packets” in long-term memory which then organize that

information into related categories.

More sophisticated and automatic schemas free a learner’s working memory capacity,

allowing processes such as comprehension and reasoning to occur… a high cognitive

load is put on learners when they do not have the appropriate or automated schemas to

access, or when the learning task imposes a heavy demand on working memory processes

(Driscoll, 2012, p. 38).

Chandler (2004) addresses this in his article “The Crucial Role of Cognitive Processes in the

Design of Dynamic Visualizations”. There has been extensive and consistent research showing

how the interaction between working and long term memory play a crucial role in learning.

Working memory has severe limitations in processing information so it can be stored and

transferred to long-term memory.

Intrinsic cognitive load is a function of the complexity of a [visualization] as well as a

learner’s prior knowledge. Extraneous cognitive load is determined by how a

[visualization] is presented to learners or the activities required of learners that are not

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directly related to learning. Germane cognitive load is generated by mental activities that

are directly relevant to the construction and automation of knowledge in long-term

memory (Chandler, 2004, p.354).

This research suggests that using visuals to clarify information in your instruction may not be

enough. These graphics must be well-designed, with the intention of supporting the instructional

goal and, more importantly, to lessen the burden of working memory on the learner.

Current best practices: Applying theory

As always, the challenge lies in integrating these unique principles into a concise and

effective learning practice. Ruth Clark and Chopeta Lyons use their experience and research to

uncover best practices in their two-part journal article from 2003 for The e-Learning Developers’

Journal- More Than Just Eye Candy: Graphics for e-learning. Overly complicated visuals can

depress learning by increasing the cognitive processes in working memory. There are three

factors that shape the effectiveness of graphics— the instructional goal, the learning landscape,

and features of the graphic itself. This is elaborated upon in Figure 3. Clark iterates that “it’s the

functionality of the graphic -- both its communication and its psychological functionality” that

determine their effectiveness. Lyons later quotes Robert Rankin that reports “92% of learner’

comprehension mistakes about graphics were caused by four reasons: 1) layout-related

difficulties; 2) lack of caption/picture correspondence; 3) unfamiliarity of the graphic

convention; and 4) misinterpretation of the graphical layout” (Lyons, p.1).

Clark and Lyons create a phased visual design model to conquer these challenges. Their

approach is unique in that very few practical models based on sound research exist. In More

Than Just Eye Candy: Graphics for e-learning: Part II also from 2003, the five-part model is

explained. They stress the importance of defining instructional goals, using that information to

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inform the visual content, and then editing those objects using psychological principles. This

assessment ensures graphic content“…supports the six key instructional events of learning.

These include ways to use graphics and graphic treatments to help learners: focus attention,

activate prior knowledge in memory, minimize cognitive load, build new mental models,

maximize transfer of learning, support motivation…” (Lyons, p.7). This model can be seen in

more detail in Figure 4 (Lyons 3-8).

A relatively new direction in e-learning includes the use of dynamic or active

visualizations like video. This is yet another form of multimedia that can engage the learner and

give them more control over instruction. Dynamic and interactive media can help non-native

English speakers manipulate symbolism for better understanding, or allow the learner to alter

data sets in order to observe change to an end goal. This can clarify complex concepts

centralized around interconnectivity, and cause and effect. These modern developments do not

come without reservations, however. According to Lowe (2004), dynamic and interactive

visualizations can have “greater processing requirements… than static visualisations” (Lowe,

2004, p. 235). Unfortunately, there has not been significant research to determine their

effectiveness.

Critical Analysis

In order for data visualization to be effective, it must simplify information whilst

lessening the burden of working memory of the learner. There are two pillars one must consider

before using an infographic for e-learning. The first is choosing the correct information to

display.

One of the purposes of data visualization is to clarify, but it can only do so if the learner

is familiar with some of the introductory concepts referenced. In choosing a subject to reimagine

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graphically, choosing the proper scope is key. A topic too complex or too simple can defeat the

purpose of using an infographic or data visualization. The instructor must consider the learner’s

prior knowledge and use that to illustrate something deeper such as a relationship, comparison,

or process. Finally, they must curate the information and arrange the knowledge packets for the

reader. As Driscoll points out, failing to do so can depress working memory and inhibit the

learning process. To fully optimize this process via infographics, the second pillar to balance is

design.

With the abundance of digital media and authoring platforms, creating visual content has

never been simpler, but it can be easy to get caught up in color or font choice. Avoiding the four

visual pitfalls Rankin mentions earlier is crucial to enhancing the learning process. The layout

must be intuitive and easily understood—cognitive effort spent interpreting layout is effort not

spent grasping the concept depicted. Properly labeling the data or picture is also key in

optimizing working memory—the goal is to allow the learner to draw connections effortlessly.

Finally, the instructor must view the finished product through the lens of the learner, and ensure

that there’s little room for misinterpretation. When using other digital media such as video or

motivational imagery, remember the first pillar: purpose. Information comes first.

These pillars should always be considered, especially with the ever-changing landscape

of the digital sphere and e-learning. Animation, collaborative environments, and dynamic

visualizations are a few modern forms of data visualization and will continue to evolve. It is

important to consider the learner and initial purpose of the object, rather than inserting

technology for technology’s sake. Interactive visualizations that give the learner too many

options (playback, for example), “provides learner control over the visualization’s dynamics,

[but] may demand the application of additional cognitive process such as planning and decision-

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making” ( Lowe, 2004, p. 236). Balancing the tensions between enhanced functionality and

simplifying the subject will be a constant challenge in the information age.

Conclusion

Data visualization has been around for centuries, yet a modern focus on visual literacy

and the prevalence of graphic content has sparked a conversation about its effectiveness,

especially in an e-learning context. Several educational theories endorse the use of data

visualization to enhance learning as a way to engage and help the learner make connections.

However, Sweller’s Cognitive Load Theory explains its potentially damaging effect if used

incorrectly. If visual content is to be effective, it must lessen the burden of working memory on

the learner and apply known psychological principles to meet instructional goals.

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References

Beardslee, D. (2014, January 1). Information Design Definitions. Home. Retrieved June 1, 2014, from http://library.rit.edu/gda/node/280 Chandler, P. The crucial role of cognitive processes in the design of dynamic visualizations. Learning and Instruction, 353-357. Clark, R. More Than Just Eye Candy: Graphics for e-Learning: Part I. The eLearning Developers' Journal. Dede, C. Emerging Influences Of Information Technology On School Curriculum. Journal of Curriculum Studies, 32, 281-303. Elkins, James 2010. The concept of visual literacy, and its limitations, In: Visual Literacy, ed. James Elkins. Routledge, New York. pgs 217. Johnston, L., & Holloway, D. (2011, December 5). MCJ Edward Tufte Notes.MCJ Edward Tufte Notes. Retrieved June 9, 2014, from http://www.slideshare.net/mcgarrahjessee/mcjedward-tuftenotes Lowe, R. Dynamic visualisations and learning. Learning and Instruction, 14, 235-240. Lyons, C. More Than Just Eye Candy: Graphics for e-Learning: Part II. The eLearning Developers' Journal. Patton, P. (2009, October 20). Neurath, Bliss and the Language of the Pictogram. AIGA. Retrieved June 6, 2014, from http://www.aiga.org/neurath-bliss-and-the-language-of-the-pictogram Psychological & Brain Science. (2014, January 1). . Retrieved June 6, 2014, from (https://www.psych.ucsb.edu/people/faculty/mayer) Reigeluth C. (2012). Instructional Theory and Technology for a Postindustrial World. In R.A. Reiser & J.V. Dempsey (Eds.), Trends and Issues in Instructional Design and Technology (pp. 35-44). Boston: Pearson State Legislatures: Party Split. (2012, August 9). State Legislatures: Party Split. Retrieved June 9, 2014, from http://visual.ly/state-legislatures-party-split Tufte, E. R. (1983). The visual display of quantitative information. Cheshire, Conn.: Graphics Press. Tufte, E. R. (2006). Beautiful evidence. Cheshire, Conn.: Graphics Press.

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Tufte, E. (2011, February 8). Comment> Edward Tufte - The Architect's Newspaper. Comment> Edward Tufte - The Architect's Newspaper. Retrieved June 1, 2014, from http://archpaper.com/news/articles.asp?id=5127 The History of Symbols : Isotype. (2012, January 1). The History of Symbols : Isotype. Retrieved June 6, 2014, from http://www.designhistory.org/Symbols_pages/isotype.html Tweet from the Wall Street Journal (2011, May 6). . Retrieved June 6, 2014, from (http://kottke.org/11/05/twitter-sparklines)

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Figures

Figure 1,Tweet from the Wall Street Journal (2011). Sparkline used to depict change in

unemployment rate.

Figure 2. US State Legislature Party Division by State (2012) This figure shows how prior

knowledge is engaged when exploring new concepts.

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Figure 3. Three factors that shape design of effective visuals (2003). Principles used in choosing

the correct graphics for e-learning.

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Figure 4. A visual design model from Ruth Clark and Chopeta Lyons (2003) This model uses

known psychology research to guide the effective use of data visualization in e-learning.