In a previous blog post, Paula Rosinski detailed steps for coding visuals in writing beyond the university research. We take up Rosinki’s guidance in this post and detail how we coded participant drawing in our writing beyond the university research.

We write as participants of the 2019-2021 research seminar on Writing Beyond the University: Fostering Writers’ Lifelong Learning and Agency. In our study, we examined how professionals draw on their undergraduate writing experiences to complete workplace writing tasks. During one-on-one interviews with participants, we invited participants to draw their workplace writing processes.

Our invitation to draw one’s writing process was inspired by similar data collection techniques within writing studies. For example, Paul Prior and Jody Shipka asked participants to draw their own writing processes (Prior and Shipka 2003). One of us (Michael) invited college athletes to visually map the kinds of writing asked of them in their various academic classes (Rifenburg 2020).

Prompting Participant Drawing

During the interview, we prompted participants to draw the process they used to complete a recent piece of workplace writing. Once they finished, we asked them to talk through their drawing. They explained what they drew and why, and they often added additional information to their drawing after reflecting. All participants digitally sent their drawings to us. We offer one example below, created by Donovan (a pseudonym), who works for a telecommunications company in the United States.

Coding Participant Drawing

We collaboratively developed a code—just as researchers do when coding non-numerical data like talk. Drawing on document design concepts and what we collaboratively saw as the main parts of Donovan’s drawing, we developed six categories:

• Alphabetic text: While the specific words were important, we focused primarily on the type of word, such as verbs, descriptors, and names. These categories of text allowed us to understand the concepts and ideas rather than the specifics of what each participant included.
• Iconic and symbolic signs: We initially divided the use of signs into iconic or symbolic. Icons are pictorial representations of objects, and symbols are images more abstracted from their meanings. We coded arrows here to discuss symbolic meaning, though we focused on how they indicated directionality in the movement section.
• Enclosure: Enclosure has two levels—the first is the enclosure of the page or screen and how that affects what it contains. The second refers to how text or other elements are enclosed through boxes, circles, or bubbles as a way of separating or elevating. We focused primarily on the second use of enclosure.
• Chunking: Chunking refers to the ways information can be divided meaningfully to help a user navigate key ideas or skim a document more effectively. Under this code, we looked for how information was divided and also how the participants used proximity to indicate related concepts (close proximity) or separated content to indicate distinct concepts.
• Movement: Since we asked participants to draw their process, movement was an essential category to code so we could capture their thinking around whether they saw a linear process, a cycle, a cycle within a linear process, as well as how they moved from phase to phase.
• Material: Here, we coded for the materials the participants used to draw, from paper to pen colors to choices about orientation of their paper and other elements.

We collaboratively coded Donovan’s drawing together to refine our categories. In the image above, we redacted the name of Donovan’s company found in the top right.

Under the alphabetic text category, we observed that Donovan opts for action verbs and gerunds, like “repeat” and “meeting,” and his co-workers, like Greg and John. Iconic and symbolic signs are the square and circles in the top right that represent a desk and the cloud-like symbolic sign that represents a thought bubble or brainstorming session.

Enclosure helped us notice how Donovan visually captured part of the writing process that involved others. Chunking allowed us to characterize the proximity of phases to the writing process and understand why the initial “meeting” and “rinse and repeat” were visually separate from the linear chunk of “begin each section,” “submit draft,” “suggestions,” and “meeting again.”

Finally, movement showed us the arrows and the direction of the writing process. The process appears linear but ends in a curious whirlpool shape that simultaneously represents a linear point in the process as well as a cycle, and his process seems to have no clearly demarcated endpoint. For material, we observed Donovan’s decision to use the landscape orientation for his drawing despite only using part of that sheet to write on.

Once we agreed upon these six categories and placed content into these categories, we collaboratively coded the twelve other drawings. We then came together and identified themes across our coded visuals. These drawings allowed us to make observations about writers in context that may have been not possible with only a writing sample and an interview. In addition, we examined the individual writer’s representation of their process and how the drawings functioned as a full data set, noting similarities and differences, as well as unusual or surprising elements.

Implications for Writing Beyond the University Research

We plan to place our findings from these drawings in conversation with interview transcripts and sample writing artifacts to capture a rich picture of people writing beyond the university.

Ultimately, coding participant drawing in writing beyond the university research offered us another method to capture writers’ thinking about their process and their writing in context. By eliciting drawings and coding the responses, writing beyond the university researchers can expand their data collection methods to capture more nuanced understanding of writing development. 

References

Prior, Paul, and Jody Shipka. 2003. “Chronotopic Lamination: Tracing the Contours of Literate Activity.” In Writing Selves / Writing Societies: Research from Activity Perspectives, edited by Charles Bazerman and David R. Russell, WAC Clearinghouse, 180-238. https://wac.colostate.edu/books/selves_societies/prior/prior.pdf.

Rosinski, Paula. 2021. “Coding Visuals in Writing Beyond the University Research.” Center for Engaged Learning (blog), Elon University. March 11, 2021. http://www.centerforengagedlearning.org/coding-visuals-in-writing-beyond-the-university-research

Rifenburg, J. Michael. 2020. “Student-Athletes’ Metacognitive Strategy Knowledge.” Composition Forum 43. https://compositionforum.com/issue/43/student-athletes.php.

Jenn Mallette is an associate professor in the Department of Writing Studies at Boise State University. J. Michael Rifenburg is an associate professor in the Department of English at the University of North Georgia.

How to Cite This Post

Mallette, Jenn, and J. Michael Rifenburg. 2022. “Coding Participant Drawing in Writing Beyond the University Research.” Center for Engaged Learning (blog), Elon University. July 13, 2022. https://www.centerforengagedlearning.org/coding-participant-drawing-in-writing-beyond-the-university-research.