My original goal for the Digital Scholarship and Publishing Studio’s Fellowship was to learn how to code in Python, with the end goal of using machine learning in my scholarship. However, one question that’s emerged during the summer is: how do you teach humanities majors to code? At first, I was asking this in more of a “meta” way—  since I am, in fact, a humanities PhD student teaching myself how to code. Pedagogy wasn’t initially at the forefront of my mind, but after reading Nick Montfort’s “Exploratory Programming in Digital Humanities Pedagogy and Research,” I realized that it would be a missed opportunity not to consider the benefits and potential roadblocks to implementing coding (among other specialized technology) in an English major classroom.

Unfortunately, the high barrier to entry in the Digital Humanities—or, more accurately, the perception of needing hard skills such as IT or coding—deters many humanities researchers away from engaging with digital methodologies in their research. This is especially prevalent at the PhD level, since graduate studies mainly focus on intensely honing skills previously acquired in undergrad (such as critical thinking, reading, and writing) rather than learning new ones. However, what appears to be a stark dichotomy between the quantitative and qualitative fields lie two faulty assumptions that 1. it’s too late/difficult to learn these skills and 2. these skills are only for aggregating hard data rather than evaluating artistic merit and historical significance.

While quantitative methodologies in literary studies such as distant reading do offer a novel approach to an otherwise subjective field, this is only one potential use of coding. In “Exploratory Programming in Digital Humanities Pedagogy and Research,” Montfort advocates for an alternative view towards coding, seeing it as an enlightening process rather than a means to an end. Interestingly, this aligns well with the learning objectives in my classroom. Yes, you probably won’t ever use your rhetorical analysis on a Taylor Swift song or publish your essay on how monstrosity is depicted in Frankenstein, but these papers are just outcomes of practicing critical thinking and arguing persuasively. Similarly, Montfort purports the use of computation as “a way of inquiring about and constructively thinking about important issues” and to develop an “appreciation of how complex ideas can be imagined and expressed as a set of formal procedures—rules, models, algorithm—in the virtual space.” And most importantly—learning to code is fun, and offers a break from the fantastically murky realm of challenging literature that requires full-throttle brainpower.