Elizabeth Losh, University of California, San Diego
The central concept of this panel “Program or Be Programmed” might immediately bring up performance anxiety issues for many composition professionals in the audience. As Stephen Ramsay put it recently, the very notion of the tech-savvy digital humanities as the newest “hot thing” tends to bring up “terrible, soul-crushing anxiety about peoples’ place in the world.” For those in composition, the anxiety might be even more acutely soul-crushing in light of existing labor politics. Every time the subject of learning code comes up, one can almost see the thought balloons appearing: “How can I learn Python in my spare time when I can’t even see over the top of the stack of first-year papers that I have to grade?”
And for those who care about inclusion, what does it mean to choose the paradigm of computer programming culture, where women and people of color so frequently feel marginalized?
Furthermore, if all these powerful feelings are being stirred up, what questions should we be asking about ideology as an object of study. For example, at the 2010 Critical Code Studies conference, Wendy Chun argued that a desire for mastery over blackboxed systems or access to originary source code shows how a particular dialectic of freedom and control makes it difficult for us to have meaningful discussions about technology and to acknowledge our own limited access to totalizing understanding, even if one might be a software engineer.
Fortunately, after reading the arguments above, our audience should feel a little less anxious as they think about teaching writing as an information art. They should know that doing-it-yourself means doing-it-with-others, whether it is imagining Picasso and Braque building a flying machine, as David Rieder suggests, or installing Ubuntu with the help of a neighbor, as Alexandria Lockett describes. The message to instructors is ultimately comforting: relax, be confident in your own abilities to learn new things, ask questions, facilitate the questions of others, and network in ways that help you make new friends.
However, if you are an administrator as well as an instructor, don’t get too relaxed just yet. These talks also bring up some very thorny questions about disciplinary turf. After all, who defines how digital literacy should be taught and who will teach it? Computer scientists? Media artists? Librarians? Writing studies people?
Although he uses the word “craft,” Karl Stolley asserts that “source literacy” doesn’t require an elaborate apprenticeship. All it takes is moving toward a set of everyday common-sense practices involving taking control of command lines and file structures. Mark Sample suggests the term “code competency” as an alternative to “code literacy,” because of all the cultural baggage associated with the word “literacy” itself. Trebor Scholz has suggested “fluency” as a better characterization of what we are trying to teach, but Sample notes the limitations of that term.
In a 2010 essay called “Whose Literacy Is It Anyway?” Jonathan Alexander and I pointed to Michael Mateas’s work on “procedural literacy” as a way for compositionists to begin to engage with these issues. Mateas worries that universities are often too eager to adopt the training regimes of computer science departments, which is great for graduating computer science majors but not so great for teaching students in other majors or with other passions to use code. Mateas also argues that programming languages like Processing are needed in these curricula, because they can be customized by advanced users outside of technical fields while provide scaffolding for beginners to learn languages like Java and C++. (For more on Processing, see my my “DIY Coding” interview with the language’s co-creator Casey Reas.)
So what should be the relationship between writing studies and computer science in the academy? The collegiality common between computer science and computers and writing only gets us so far in our responsibility to teach computational literacy.
Both Sample and Vee mention Edsger Dijkstra, who was also the author of “On the Cruelty of Really Teaching Computer Science,” a decidedly anti-humanistic diatribe on the superiority of formal logic and mathematics as the keys to supposedly real knowledge. Dijkstra’s legacy still lives on in many computer science departments, and it is often difficult to have rhetoric taken seriously by stakeholders in many other STEM disciplines. The core curriculum in the Culture, Art, and Technology program that I direct has a digital literacy requirement that generally involves taking a programming course in the computer science department, but not every student feels comfortable crossing those bridges between disciplinary norms.
If there are answers to the questions of who should teach computational literacy, then we have not yet found them. But I’ll put in my own GOTO command for writing studies to keep this spaghetti-like discussion going.