Following the Narrative: Using Data Visualization in the Composition Classroom

Contributer: Shannon N. Fanning
Affiliation:Farmingdale State College
Email: Shannon.Fanning at farmingdale.edu
Released: 15 August 2020
Published: Fall 2020 (Issue 25.1)

Despite the growing popularity of multimodality and visual rhetoric in the composition classroom, “data visualization" and “composition classroom” are not phrases that we are used to seeing together in the same sentence. Conversely, many instructors use narrative when teaching composition classes—for some, the composition classroom would cease to function without narrative. This wiki highlights that data visualizations often function as narratives and argues that, by understanding them as such, their place as a productive part of the composition classroom becomes significantly clearer. Specifically, this wiki will address the utility of data visualizations in the composition classroom, paying particular attention to how data visualizations can help students to comprehend information more quickly, aid in improving recall, and assist students in recognizing relationships and making sense of difficult concepts. It will also highlight the importance of multimodal pedagogy and assignments. Sample assignments will be provided throughout to demonstrate how data visualization can help instructors to achieve these goals in the composition classroom.

As I worked to finish my doctoral dissertation that examined the different rhetorical genres of the images, particularly the data visualizations, utilized in the reporting of the 2015 Zika virus epidemic, I also found myself teaching four sections of first-year composition. It was a job I had held for a few years and one that I loved, but I often found myself struck by the seeming disparity between my research interests and my teaching goals. As I collected and analyzed more and more visualizations and began to focus on the stories the data and their corresponding visualizations were telling me, I was struck by how much they seemed to be carrying out a narrative function. Further research revealed that this was not a novel observation, both confirming my notion and leading me to explore the topic further. As a result, I turned to thinking about how I could leverage this “discovery,” blending my once seemingly disparate worlds together and harnessing the story-telling power and rhetorical effectiveness I knew data visualizations to have in ways that would help my composition, and later communication, students.

 

Data Displays as Narrative

Narrative has frequently found a home in the composition classroom. Whether reading fiction or contemporary articles on social issues, students are exposed to a variety of stories and re-tellings of events that serve as starting points for discussion and critical thinking. Students are also asked to compose in narrative genres, among them personal and literacy narratives. After composing, we often ask students to reflect on their experiences, again composing narratives—this time of their writing processes. While data visualizations may not be commonly thought of as narratives, several prominent visualization scholars have recognized data displays as effective story-telling tools. Howard Wainer’s work, for example, draws heavily on the narrative function of data displays, focusing on the stories that can be told through data and using phrases like “visual adventures” and “a series of episodes” to describe the stories told by data visualizations. Edward Tufte (1983) also addressed the narrative power of data displays. He described Charles Joseph Minard’s well-known graphic of Napoleon’s invasion of Russia as telling “a rich, coherent story with its multivariate data,” before going on to offer its praise, stating “it may well be the best statistical graphic ever drawn” (p. 40), essentially equating effective storytelling with the success of the data display. Tufte (1990) even titled a chapter from his work Envisioning Information “Narrative of Space and Time,” again emphasizing the narrative quality of data displays.

Edward Segel and Jeffrey Heer (2010) addressed the connection between data visualization and narrative directly, noting that data visualization evokes comparisons to storytelling. Nahum Gershon and Ward Page (2001) claimed that stories and visualization design share a common goal: to communicate information in a psychologically-effective format. Kwan-Liu Ma, Isaac Liao, Jennifer Frazier, Helwig Hauser, and Helen-Nicole Kostis (2012) explained that visualizations can tap into episodic memory and establish themselves as cohesive entities, thus making them more memorable. To do so, the authors instruct technical communicators to remember the fundamentals of good storytelling. Thus, while many may not conceive of data displays as telling stories the way that traditional texts do, the power of data displays as narrative tools has indeed been recognized by prominent visualization scholars. While my notion of data visualizations as narrative proved to be not especially unique, it did serve as an entry point for further research on the topic and helped me to recognize the place data visualization has in the composition classroom. What I hope to offer through this wiki is a look at the ways in which this new understanding of data visualization as narrative helped me to integrate its use into my composition, and later communication, classrooms. In understanding data visualizations as narratives, we not only begin to become aware of the ways we can use them in the classroom, we also begin to see the place—the belonging—they have there.

More than Visuals; Not all Data

Visuals have also found a home in the composition classroom as more and more instructors, myself included, turn to multimodal pedagogy as a way to engage students and help them to leverage their communicative strengths. The use of visuals in the composition classroom is not new, though, as scholars have been using visuals in the composition classroom for decades—at least since 1970, the year in which Sonja Foss (2004) notes the first formal call was made to include visual images in the study of rhetoric as the result of a recommendation that grew out of the National Conference on Rhetoric convened by the Speech Communication Association. Jason Palmeri (2012) traces the history of multimodal composition back even further to the 1960s, asserting that multimodality has long been a part of the composition classroom; though, our attention to multimodal practices in the classroom has waxed and waned over time. 

Others have addressed data visualization as it relates to the composition classroom, particularly those scholars in the area of computers and writing (e.g., Muller and Laurer), but much of this work has been focused on research and analysis as opposed to pedagogy like Derek Muller’s (2017) work on methods for visualizing the discipline and Claire Laurer’s (2013) analysis of composing technologies mentioned in Modern Language Association job advertisements. Joanna Wolfe (2015) addresses the classroom specifically, calling for a broadened perspective on how both instructors and students view rhetoric that includes quantitative writing. She argues that alongside the various types of literacy instruction, including visual and alphabetic literacy, there is a place for quantitative literacy instruction. She contends that the textbooks and other instructional material of our field fail to adequately address quantitative literacy and instead reinforce the view that numbers are facts. Wolfe instead calls for more attention to be paid to help students rhetorically analyze quantitative information. Futher, Madeleine Sorapure (2010) advocates incorporating information visualization assignments into composition classes to encourage students to think critically about the software they use and to offer alternative means of production. While I support and hope to continue the important work of these two scholars, my own work takes a different approach, focusing on how incorporating data visualization into the composition classroom can benefit our students in many ways; when used strategically, it has the ability to improve comprehension, retention, and recall.

By drawing on both the strengths of narrative and multimodal composition, it not only becomes easier to see the place for data visualization in the composition classroom but also the opportunities it presents for students. It’s important to note here that in discussing data visualization, I am working with a broad definition that understands data visualization to be the presentation of information in graphical or pictorial format. While there is certainly a place for the representation of purely quantitative information in the study of composition and communication, working with this expanded definition allows for more variety of use of data visualization in the classroom. While my broad definition here may lead to some blurred lines between data visualization and the use of visuals more generally, an important distinction remains. Teaching visuals in the writing classroom is focused on different modes through which to make and interpret meaning. In focusing on data visualization, that focus shifts to relationships, particularly relationships between things that are measurable or defined. In short, it’s the visual representation of information. Scholars have grappled with this distinction between visuals and visualization before. Matthew B. Miles and A. Michael Huberman (1994) initially defined a visual display as “an organized, compressed assembly of information that permits conclusion drawing and action” (p. 11). Ralph Lengler and Martin J. Eppler (2007) define it as "an elaborate understanding, or communicating experiences” (p. 1). Even more recently Susan Verdinelli and Norma I. Scandollio (2013) set out to study “Qualitative data display” in its own right, defining nine different types of qualitative data displays in an effort to expand the use and capability of visual displays of qualitative data. By embracing this expanded understanding of both data and of visualization, we open up additional ways to leverage it in our composition—and communication—classrooms.

Comprehension

Before students can analyze and synthesize texts, they need to be able to process and understand them. Reading comprehension is a skill that I have seen my own students struggle with, students ranging from my first-semester composition students to my communication students in upper division courses. Bringing data visualization into the composition classroom offers another technique to help students with comprehension. In fact, comprehension has always been a goal of data visualization. Jason P. Fritz and Kenneth E. Barner (1999) even defined data visualization in these terms, stating “Data visualization is a technique used to explore real or simulated data by representing it in a form more suitable for comprehension.” The authors continue to explain that vision has the highest bandwidth of the senses, meaning it is the sense through which we can take in the most types and largest quantity of information. Visualizations, therefore, are an ideal way to present information for quick and easy comprehension. This bandwidth gives visualizations an important shared goal with the composition classroom—comprehension.

Data visualization also makes it easier to see important information in one glance. A study by W. Horn, C. Popow and L. Unterasinger (2001) found support for the use of visualizations in supporting fast comprehension of ICU data in hospitals. Stable patients could be recognized at first sight, while the improving or worsening conditions of other patients were easy to analyze and drastic changes in patient status elicited immediate attention. Tufte (1990) explained this micro/macro design as a technique that allows visualizations to communicate both overarching ideas and more specific, detailed information at once. He uses the Vietnam Memorial as an example, arguing that its visual and emotional depth are derived by means of its micro/macro design; the 58,000 names serve to express the magnitude of loss of life, while coming closer allows you to see each name, something more specific and more personal. Similarly, Ben F. Barton and Marthalee S. Barton (1993) explained synoptic and panoptic views of visualizations, ultimately arguing that composing in both modes simultaneously provides the most powerful images. In thinking about visualizations this way, students, too, can harness their narrative power and benefit from increased comprehension of new material, especially readings or lessons with lots of moving parts.

A couple of semesters ago, I found myself teaching several science-themed composition courses. In part because of my own interest in germ theory and, of course, data visualization, students read The Ghost Map by Steven Johnson. While Jon Snow’s use of data visualization to solve the cholera epidemic didn’t play quite as prominent a role as I had expected based on my previous visual-focused readings of the events, the story is nevertheless compelling. Students were pretty quickly interested in the cholera epidemic and what was going to be done to keep it from spreading further. But, there were a lot of details to keep track of. Because I knew that the geography was going to play a pivotal role in the story’s outcome, I had them map the details. Students drew important events and findings on paper in order to both keep track of the events and to begin looking for connections. Visually mapping sequences and other relationships, though, doesn’t have to be tied to geographically-based material. More recently, in my advanced technical communications course, I assigned students Clay Spinuzzi’s well-known article “Who Killed Rex?” I knew this would be a challenging article for them, but it’s certainly a worthwhile read. Before helping students untangle the communicative networks and issues Spinuzzi describes, I asked students to try to make sense of it themselves—by visualizing it. By seeing the paths of communication as opposed to merely reading about them or even attempting to organize them in their notes, students were better able to see the places in which the message got confused, and most importantly, the places where communicators would have found themselves most able to intervene in order to save Rex from his untimely demise. 

Mapping the communication allowed for both a micro and macro look at the information. In one glance, it’s clear the networks are complex and overlap. Further examination reveals the more specific aspects of the networks’ relationships. Both the product and process play a role here for the student, as not only must she study the information in order to represent it accurately and put forth time and effort in that representation, but the finished product also serves as both a panoptic and synoptic visual that reinforces these same relationships between networks.

Assignment: Following the Networks in “Who Killed Rex?”

This article involves a complex communication network in which the important message about Rex being in the yard gets lost. Trace the message—draw the path it takes from the time Rex’s owner calls Telecorp about service disruption to when Rex escapes from the yard. Label your drawing and account for all of the possible routes Spinuzzi discusses in his article. You may draw your network map by hand or use any computer program you are comfortable with. When you’re done, write a paragraph in which you answer the following: Where does the message end up? What does this tell us about who is at fault? Submit both the visual and the paragraph via Blackboard.

Assignment: Student Response

"The article by Spinuzzi involves a complex communication network in which the important message about the dog, Rex, being in the backyard of the consumer. The message about Rex being in the yard gets lost in translation between the time the customer called the company, and when the technician arrived at the residence." Through the image map, I traced the path in which the important detail about Rex's whereabouts went. So where did the message end up exactly? As we gather from the story and from the image map, Spinuzzi implies that the message very well could have taken three possible routes, but ultimately the message ends up at the Network Control Center (NCC). Overall, the company as a whole is to blame due to negligence. They were neglectful in making sure the message was passed along through all inter-company communication." 

Retention & Recall 

It has already been well documented that narratives help with reader performance and information retention functions (e.g., Grasseur, Olde, & Klettke, 2002; Williams, 2000; Zabrucky & Moore, 1999), and literature on the inclusion of visuals shows similar results. William G. Holliday (1976) studied 207 high school biology students to see if diagrams were more effective in communicating instructional meaning than texts. Each student was randomly assigned one of five treatments: block-word diagram, picture-word diagram, text alone, text and block-word diagram, or text and picture-word diagram. Students were given 30 multiple-choice questions to assess their recall. Holliday found that students with either diagram type recalled information better than those who received the text alone. Similarly, Becky K. Peterson’s (1983) study of 625 students from seven universities, representing all regions of the country, showed a significant relationship between method of presentation and information retention. Students were given narratives about finding job opportunities with the text accompanied by a table, a graph, or both. Performance was clearly linked to the visuals included, as students given only the text took the most time to read the information despite it having fewer elements (no graph, no table). Students presented with the text and the table required the least amount of reading time; students with the text and graph used only slightly more time than those with the text and table. Peterson (1983) also looked at the relationship between method of presentation and reader reaction. Readers reacted most positively to the text accompanied by graphs, followed by the combination of text, graph, and table; however, a significant difference was noted between the two conditions with considerable preference for the graph. The poorest reaction, though, came from the text with neither table nor graph.   

More recently, Nathan S. Pratt, Brenna Ellison, Aaron S Benjamin, and Manabu T. Nakamura (2016) found that the inclusion of graphs in nutritional information improved recall of that information by university students by up to 43%, demonstrating “that graphically presenting nutrition information makes that information more available for decision making” (Pratt et al., 2016 p. 44). Pratt et al. also investigated the result of graphical signposting of nutritional information in a cafeteria setting and found that university students purchased meals with decreased calories and increased protein per calories, while posting the numerical information alone had no effect on the calories of the students’ purchases.

Final Assignment Strategically Designed With Visuals

Student Response

When I asked students for their opinions on the inclusion of the visualizations in this assignment, the response was overwhelmingly positive. They said the inclusion of the visuals “improves understanding” and “makes it more clear what is expected of us.” One described the pie chart as a “motivator” for putting in a lot of effort on this final project, at a time in the semester when that motivation sometimes seems to fade. The calendar seemed to help students organize the various due dates in their mind, one commenting “It reminded me to recheck the dates that I had previously written down. This also leaves very little room for a student to have the excuse of not completing the assignment on time.” The visualizations, then, helped students to feel more confident in their ability to recall information, much like Holliday (1976) experienced with his biology students, and helped to improve recall by making the information available for decision-making as Pratt and colleagues (2016) described.

Finding Relationships

Data visualizations can also be used to help students make sense of difficult concepts and to find relationships between different sets of information. Experimenting with data visualization can help students to find relationships in both data sets and in interrelated concepts. Visualization also helps students to make sense of difficult processes and helps to concretize concepts that are difficult to picture. Anne R. Richards (2003) claimed that visual representations may appear to describe nature more accurately and fully than words can. In her study of visuals contained in the American Journal of Botany over an 80-year period from 1914 to 1994, Richards found that visuals based on raw data were by far the most prevalent type of visuals in the journal. She explains that this type of data visualization fulfills the important rhetorical function of seemingly reproducing reality for the viewer. Stephen M. Kosslyn (2006), among others, has pointed to graphs, such as line and bar graphs, as the most appropriate visual type for showing relationships among data. Alan G. Gross and Joseph E. Harmon (2013) reminded us that graphs “do not merely arrange data for viewers to easily derive a large set of propositions” (p. 56), but that they mainly answer implied questions about the trends. Graphs and charts, Stephen Few (2007) argued, are intended to be used when a picture of the data makes meaningful relationships visible.

Visualizations also help to show and explain things that words cannot. Ma et al. (2012) urge the use of good story-telling fundamentals in creating data visualizations. As we create visualizations, we should assess the audience’s level of knowledge and familiarity with conventions, introduce the characters or visual elements and what they represent, arrange visual events in a way that tells an interesting and compelling story, and leave the audience with a lasting impression of how the story relates to them.

The use of tables allows readers to understand something quickly, as tables were found to promote the quickest reading time and a high level of retention in Peterson’s (1983) study. While tables are not always considered as data displays, several have noted their explanatory power and rhetorical effectiveness (e.g., Brassuer, 2003; Myers, 1988), suggesting they may be more powerful and complex visual genres than they appear and warranting their inclusion here. Because knowledge is made through the process of visualization, creating visualizations is not only useful to readers, but to the students or instructors themselves. Students can visualize elements of their own papers and compare them to expert papers or corpus data, learning to recognize expert patterns and incorporate these into their own work. Mapping out readings at the end of a unit, as the next assignment tasks students to do, can also help students to find the relationships between different authors, chapters, and contexts. In doing so, it uses tables to make meaningful relationships more visible.

It is clear from this student’s reflection, that visualizing the important points of each chapter helped him to not only locate and organize those key ideas but also to find relationships between these concepts and discussions of similar concepts in other chapters. Here, this assignment works especially well for writing, as each chapter discussed a different type of writing. While there were differences in each genre, of course, each chapter also highlighted the importance of audience, clarity, and writing as a process—elements the student successfully identified and described here.

Assignment 

Unit two consisted of three chapters: Chapter 6 on electronics news writing, Chapter 9 on writing for social media, and Chapter 10 on web copywriting. Revisit each chapter and your notes and make a list of 10 key concepts or takeaways from each chapter. Arrange your lists in a table with a column for each chapter. Highlight and color code any key ideas that appear in more than one chapter’s list. For example:

Student Response 

Below is the student's chart composed in response to the prompt, as well as his written explanation for this first of four relationships he observed. 

The chapters address the importance of focusing on audience needs and directing messages towards an audience. Chapter 6: It is important to do this because news writers consider who is watching to effectively report a news story. The story could have an impact on people listening. If something happens in the audience's town they will want to hear it. It is crucial to use a delayed lead to prepare the audience for the information they want to know. The news teaser gives the audience a reason to stay tuned and listen for a story coming up. Chapter 9: The target audience determines who will see a social media post or is interested in purchasing a product. This is important because each post should be directed towards a certain age group, income, and more. It is also essential to consider how the audience will react to each social media post. If something is posted they want to know, it might generate more likes and comments which can help a news organization or a business. Chapter 10: the residual message says what you want the audience to believe or do after reading. After reading a blog, someone should feel a certain way. They might be informed and persuaded to do something and it should be clearly represented. The headline formula makes a story stand out to the audience. This is important because it makes someone interested and read a story they might have not read.

The importance of focusing on audience needs and directing messages towards an audience may be understood differently in each chapter. In chapter 6, news writers are interested in understanding the audience watching the news. If it happened a few hours before, people will be interested in seeing it on the news. If people are in the car, they might be more affected by breaking news on the radio because they are still outside and driving home. The delayed lead and news teaser keep the audience engaged in the program and aware of what is coming up. In chapter 9, social media writers are concerned about the target audience.

These are the individuals that are interested in reading the posts or buying a product based on a post. It can be narrowed down to gender, income interests, and more. Social media writers also consider if they need to engage/inform, be friendly, or personal in their posts to the certain audience. Chapter 10 says in web copywriting, the reader should feel something after reading a blog. They might want to understand more about a certain topic. So, blogs might go into more detail than news writing and social media writing and have a clear message for the audience. The headline will intrigue the audience while browsing through stories as opposed to hearing a tease for an upcoming news story to stay tuned.

Conclusion 

We have been using narrative in the composition classroom for a long time, and the proliferation of multimodal pedagogy provides a way to engage and encourage students’ different communicative strengths and allows us to draw on our own various communicative strengths as well. By utilizing data visualization in our classroom, we are taking the next step; we can work to promote comprehension, recall, and understanding in new and effective ways. Visualizing information for our students and asking them to do the same supports these teaching goals. It also encourages our students—and ourselves—to experiment with different communicative forms as well as new programs and technologies.

Understanding data visualization as narrative underscores its belonging in the writing classroom. Additionally, it helps students to improve their comprehensions, recall, and relational understanding. These improvements, though, do not and should not end in the composition classroom. Much like the writing skills we hope our students will transfer into their future courses and careers, the type of visual literacy we are fostering by introducing students to data visualization in the composition classroom—an introduction that depending on their major they might not get elsewhere—is a transferable skill and understanding that will serve them well in their futures. 

While the composition classroom may still be relatively new territory for data visualization, it shares many of its goals with the strengths for which data visualization has been recognized, making data visualization an ideal strategic addition to our classrooms. Understanding the narrative function of these visualizations and recognizing them as tools that allow us to tell stories underscores their belonging in our composition classrooms. 

References

Barton, Ben. F., & Barton, Marthalee S. (1993). Modes of power in technical and professional visuals. Journal of Business and Technical Communication, 7 (1), 138-62.

Brasseur, Lee. (2003). Visualizing technical information: A cultural critique. Amityville, NY: Baywood.

Few, Stephen. (2007). Save the pies for dessert. Visual Business Intelligence Newsletter, 1-14. 

Foss, S. K. (2005). Theory of visual rhetoric. In Ken Smith et al. (Eds), Handbook of visual communication: Theory, methods, and media  (pp. 141-152). Mahwah. NJ. Lawrence Erlbaum.

Fritz, Jason P., & Barner, Kenneth E. (1999). Design of a haptic data visualization system for people with visual impairments. IEEE Transactions on rehabilitation engineering, 7(3), 372-384.

Gershon, Nahum, & Page, Ward (2001). What storytelling can do for information visualization. Communications of the ACM, 44(8), 31-37.

Graesser Arthur C., Olde Brent, & Klettke, Bianca. (2002) How does the mind construct and represent stories? In M.C. Green, J. J. Strange, & T. C. Brock Narrative Impact: Social and Cognitive Foundations (pp. 229-262). Mahwah, NJ: Lawrence Erlbaum.

Gross, Alan G., & Harmon, Joseph E. (2013). Science from sight to insight: How scientists illustrate meaning. Chicago, Illinois: University of Chicago Press.

Horn, W., Popow, C., & Unterasinger, L. (2001). Support for fast comprehension of ICU data: Visualization using metaphor graphics. Methods of information in medicine, 40(05), 421-424.

Holliday, William G. (1976). Teaching verbal chains using flow diagrams and texts. Educational Technology Research and Development, 24(1), 63-78.

Johnson, Steven. (2006). The ghost map: The story of London's most terrifying epidemic--and how it changed science, cities, and the modern world. New York, NY: Penguin.

Kosslyn, Stephen M. (2006). Graph design for the eye and mind. New York, NY: Oxford UP. 

Lauer, Claire. (2013). Technology and technical communication through the lens of the MLA job information list, 1990–2011. Programmatic Perspectives, 5(1), 4-33.

Lengler, Ralph, & Eppler, Martin J. (2007). Towards a periodic table of visualization methods for management. IASTED Proceedings of the Conference on Graphics and Visualization in Engineering, Clearwater, FL, USA. 

Ma, Kwan-Liu, Liao, Isaac, Frazier, Jennifer, Hauser, Helwig, & Kostis, Helen- Nicole. (2012). Scientific storytelling using visualization. Computer Graphics and Applications, IEEE, 32(1), 12-19.

Miles, Matthew B., & Huberman, A. Michael. (1994). Qualitative data analysis. Thousand Oaks, CA: Sage.

Mueller, Derek. N. (2017). Network sense: methods for visualizing a discipline. Fort Collins, Colorado: The WAC Clearinghouse and University Press of Colorado. 

Myers, Greg. (1988). Every picture tells a story: Illustrations in EO Wilson's Sociobiology. Human Studies, 11(2-3), 235-269.

Palmeri, Jason. (2012). Remixing composition: A history of multimodal writing pedagogy.  Carbondale, Illinois: SIU Press.

Peterson, Becky K. (1983). Tables and graphs improve reader performance and reader reaction. The Journal of Business Communication, 2(2), 47-55.

Pratt, Nathan S., Ellison, Brenna D., Benjamin, Aaron S., & Nakamura, Manabu T. (2016). Improvements in recall and food choices using a graphical method to deliver information of select nutrients. Nutrition Research, 36(1), 44-56.

Richards, Anne, R. (2003). Argument and authority in the visual representations of science. Technical Communication Quarterly, 12(2), 183-206.

Segel, Edward, & Heer, Jeffrey. (2010). Narrative visualization: Telling stories with data.Visualization and Computer Graphics, IEEE Transactions on, 16(6), 1139-1148.

Spinuzzi, Clay (2007). Who killed Rex? Tracing a message through three kinds of networks. In Mark Zachry and Charlotte Thralls (Eds), Communicative practices in workplaces and the professions: Cultural perspectives on the regulation of discourse and organizations pp. (45-66). Farmingdale, NY: Baywood.  

Sorapure, Madeleine (2010). Information visualization, Web 2.0, and the teaching of writing. Computers and Composition, 27(1), 59-70.

Tufte, Edward R. (1983). The visual display of quantitative information. Cheshire, CT:  Graphics Press.

Tufte, Edward R. (1990). Envisioning information.  Cheshire, CT: Graphics Press.

Verdinelli, Susan., & Scagnoli, Norma. I. (2013). Data display in qualitative research. International Journal of Qualitative Methods, 12(1), 359-381.

Wainer, Howard (1997). Visual revelations: Graphical tales of fate and deception from Napoleon Bonaparte to Ross Perot.  New York: Copernicus / Springer-Verlag.

Wainer, Howard. (2005). Graphic discovery: A trout in the milk and other visual adventures.  Princeton, NJ:  Princeton UP.

Williams, Joanna P. (2000). Strategic processing of text: Improving reading comprehension for students with learning disabilities. ERIC Clearinghouse on Disabilities and Gifted Education.

Wolfe, Joanna (2015). Teaching students to focus on the data in data visualization. Journal of Business and Technical Communication, 29(3), 344-359.

Zabrucky KM and Moore D (1999). Influence of text genre on adults’ monitoring of understanding and recall. Educational Gerontology, 25(8), 691–710.

 

Thank you to two of my exceptional students—Johnny Campbell and Frankie Wolf—for allowing me to use their work here.