H.19 "Collecting, Analyzing, and Talking about Data"
Reviewed by Jill Parrott (firstname.lastname@example.org)
Chair: Jason Swarts, North Carolina State University, Raleigh
Karen Lunsford, University of California-Santa Barbara, “Building a Research Tradition”
Rebecca Rickly, Texas Tech University, Lubbock, “What to Do with What You’ve Got: Representing Research”
Jo Mackiewicz, Auburn University, AL, “Stats a Good Idea: A Brief Introduction to Useful Statistics for Mixed-Methods Research”
Jason Swarts, North Carolina State University, Raleigh, “The Order in Method: How the Messy World of Writers Becomes Tidy”
I have been explaining to students in my graduate classes recently that our field walks a fine line between the humanities and the social sciences and that is one thing about writing studies I find particularly compelling. In addition, as a WPA at my institution, I am often called upon to find and create data sets to assess our program or suggest ways our program can move forward based on the findings of others. In those situations, I’m that person. You know the one—getting really excited about percentages, correlations and causations, and finding ways to visually represent findings in a meaningful way. For these reasons, and many others, I was drawn to this session on collecting, analyzing, and talking about data, and I was pleased to find the presenters meeting me where I am, at the intersection of the humanities and the social sciences, interested in finding ways to represent and define our discipline for ourselves and others. And I wasn’t the only one because our small room was packed out!
As a whole, I enjoyed how this panel was organized and how each served a specific purpose in the greater conversation. One syncretic part led naturally to the next, which kept the audience moving through the conversation. In addition, each presenter was a confident and easy speaker and none relied too heavily on notes to present information, which lent to the feeling that the time was more an extended conversation than awkward paper reading. While the first three speakers (Swarts, Mackiewicz, and Rickly) used presentation software to show relevant quotes or data sets, Karen Lunsford ended by just speaking to us—compositionist to compositionist, teacher to teacher, person to person—which was a nice way to wrap up the conversation. While there wasn’t much time for questions, the presenters were clearly open to extending the conversation beyond that small room and many attendees stayed for a bit afterwards to make some connections.
Swarts opened the session by asking the audience to consider why we should bother with research methodology. According to him, the short answer to that question is that rhetorical work is being done in the way we approach our research methodology, the disciplined ways of looking at the world that leads us from an esoteric understanding to an exoteric understanding. Methods bridge theory and analysis in four ways: by providing clarity, trust, and confidence; by exposing sources and techniques; by showing data reduction; and by implementing data coding. Overall, Swarts argued that we should take our research methodologies seriously because they are serious rhetoric that communicates information to our audience.
Jo Mackiewicz continued the conversation with a focus on statistics including ways to use them and why they are important. Trying to convince a roomful of English academics that math is fun is no small feat, but Mackiewicz’s energy and genuine enthusiasm drew the audience into her conversation. To help us better understand, she explained the difference between descriptive statistics and inferential statistics. As she explained it, descriptive statistics are relatively easily described for folks who may not be familiar with statistics and, therefore, may be useful for what would be our normal audience in writing studies. These include central tendency ideas such as mode, median, and mean and measures of dispersement such as range, variance, and standard deviation. On the other hand, inferential statistics involve elements such as Chi-Square, which help statisticians to explain why their data are significant. Mackiewicz used her time not to do a math lesson but to convince the crowd that while we may not be statisticians or mathematicians by trade, being at least familiar with these terms and having a basic competency at using them could come in very handy.
Rebecca Rickly addressed “What to Do with What You’ve Got,” which encouraged attendees to think about the presentation of their data as a rhetorical situation all the time in the same way we would any other information. We start with a research question and should follow that with methods that help to address that research question directly. In addition, though, we must also consider the representation of that research and what types must be most appropriate. She argued that raw data often is not that meaningful to an audience. Therefore, we must integrate text and images; visual representations help us understand the data and then should be followed by explanations. If we make these representations readable by considering the rhetorical situation and reacting with appropriate design, our audience may see things in a new way and so may we.
Karen Lunsford finished the panel by asking the audience to consider what infrastructures our discipline needs to build our foundational knowledge. She claims that while we have a growing interest in data-supported studies, we don’t yet have the culture in our discipline to back it up. She argued three approaches to build that culture:
- We must develop a tradition of working with shared research questions.
- We must reintroduce the idea of meta-analysis.
- We must create a better publication infrastructure to report data and to make our methodology more transparent.
As a comparison, Lunsford shared information about what writing researchers in other countries are doing, most significantly that they replicate one another’s research to make sure a phenomenon exists and to achieve nuance. In addition, these processes become a rite of passage in graduate programs and create a common ground for all professionals in the field. In the end, Lunsford rallied the crowd by saying that if anyone is interested in building this type of tradition in our American culture of writing studies that she has things she could put us to work doing (I’m sure she would like for anyone reading this who might be interested to contact her).
With a few minutes left for questions, one member of the audience asked “What do we gain and what do we lose in those spaces?”—something that seems to hit right at the heart of our disciplinary discussion on the role of research. The panelists each weighed in on this overarching question, and left us overall with the idea that adding more robust, data-driven research into our field allows a more holistic story to be told by balancing the important, small stories provided by qualitative data with larger claims that can be substantiated in numbers. Our field does not have to be either a humanities field or a social science, either lore-driven or numbers driven; we can be both, and this panel provided its own methodology for how.