I’ve been thinking a lot lately about how I can use everything we’ve been discussing about DH in my own writing classes. We’ve covered a lot of DH related topics this semester – some readings that I’ve loved some that, frankly, I have no interest in. But when I reflect on the articles that seem important to me, they all had the common thread of expanding traditional teaching pedagogy to reflect the writing and composing that is happening outside of academia. This week, too, the readings that stand out to me are those that I can imagine incorporating into my own teaching practice because they challenge traditional ways of teaching and thinking about writing.
Jenny and Jeff Rice’s “Pop-Up Archives” is an example of an interesting DH project that I can imagine incorporating into my FYW classes. When I first read the article, I questioned the idea of a temporary archive that could disappear at any moment. It seemed to me that this was not necessarily an archive if it existed only in the short term. Furthermore, why go to the trouble of archiving something that is so unimportant that no one cares if it’s deleted? That seems contrary to the idea of having archives; however, the example the Rices offer of Pinterest as temporary archiving convinces me that not all collections necessarily need to be archived for posterity.
When the Rices discuss these pop-up archives as an opportunity to explore the process of archiving, I begin to think about opportunities for using this in my FYW class. Geoffrey Sirc has done work on writing about collections and Jody Shipka talks about composing through collections of objects. It seems to me that these ideas about collections and composing work well with the Rices’ thoughts on temporary archives. The Rices’ article explains that these pop-up archives offer the opportunity to practice the process of archiving. For them, process is just as important as the actual product that is archived. This matches what we do in FYW: compose for practice and work on process. Creating temporary archives seems to fit well within a pedagogy focusing on collections, process, and the act of composing.
Liza Potts’ article, “Archive Experiences: A Vision for User-Centered Design in the Humanities,” explores the unique position that DH is in to study and improve UCD. I love that she claims there has been a tendency in DH to “fetishize the concept of coding” (257) because that is exactly the feeling I get when I read articles on whether or not coding is a literacy. Scholars focusing on coding do seem to fetishize the act in their enthusiastic attempts to convince us that coding falls into DH studies. While I don’t consider coding an essential literacy for every individual in society, I recognize its importance and am more than happy that there are people writing code to make my life easier. However, all of the code writing is somewhat meaningless if the interface impedes use. Potts argues that in Rhet/Comp we are uniquely skilled at issues of audience, content, and purpose, making DH a perfect match for work on UCD. Analyzing a site, a program, or an app for UCD would actually be a great exercise for FYW students.
The final article I am thinking about is Liz Losh’s “Nowcasting/Futurecasting: Big Data, Prognostication, and the Rhetorics of Scale.” Losh’s concern with whether humanities scholars are equipped to handle big data and the interpretive problems associated with all this data is something I’ve been thinking about more lately. Much of what we have discussed in this class is out of the realm of my background. While I want to embrace what is new and meaningful, I feel unprepared. When Losh mentions that “our current methods of disciplinary indoctrination” (287) do not prepare us to work with new methods, I wonder where exactly teaching and using big data would fit within the Rhet/Comp discipline. I think that Losh’s larger interest is on whether our projects should look to predict the future or focus on the present. I think she is advocating for using big data to observe the “now,” but I’m not really sure. And this still doesn’t address our ill-preparation for working with big data. I’m not sure what the answer is.