Course Description
This is a research course. You will learn to use computational methods to pursue your own independent research in the humanities: history, literature, philosophy, linguistics, and more. How can coding help you see things in a text that might otherwise be invisible? The course is not tied to any one topic, or even to any one discipline: the research questions come from you, and the methods we use range just as widely. By the end of one semester, students with no prior coding experience (our target constituency) will be seasoned researchers in the digital humanities.
The field has recently gone through a transformative and exciting development. AI puts within reach all sorts of things that, until very recently, a beginner could not have attempted in a single semester, and we are going to take full advantage of that. AI is one of the major tools of this course, and learning to use it well is one of the things you will take away from it. (For how and when we use it, see AI Policies for an AI Course.)
“Digital humanities” is a capacious rubric, and “coding” does not narrow it down much either. One thing we will spend a lot of time thinking about is texts. That does not mean we study texts exclusively, but a great deal of humanistic research works with texts in one way or another. A major goal of this course is to figure out how to model a text, so that a computer can work with it in ways that matter to a humanist, and then how to extract information from it. Much of that modeling happens in XML and its related technologies, which let you make explicit, structured claims about what a text is and what is in it.
Even though you will spend a lot of time coding (and directing AI to code), this is a humanities research course before it is a coding course: the computer is the means, not the end. It is fitting, then, that the centerpiece of the course is a research project, the topic of which is entirely driven by your interests, and to which you will begin applying your new skills immediately.
Legacy
This course is modeled on one pioneered by emeritus Pitt Professor David Birnbaum, and we draw extensively on the material on his website, Obdurodon. (What is an “Obdurodon,” you ask? An extinct platypus with molars, apparently… don’t worry about it.)
That course took shape before the age of AI, so we do not follow it to the letter. Its key insights, though, are as valid as ever, and Obdurodon remains an encyclopedia of information essential for this course. Just bear in mind that course-specific information on Obdurodon (due dates, classroom assignments, and the like) may relate to a previous semester.
Dr. Birnbaum summed up the impetus for this course as follows:
Humanities students often do not realize (or even imagine) that 1) they are capable of learning to write useful and practical computer programs within the course of a semester even if they have no prior background in programming; 2) the ability to write one’s own programs can be valuable for scholars in the humanities, especially because commercial software often does not address research needs in the humanities; and 3) practical computer programming, no less than reading, writing, and arithmetic, is a useful skill that is within the reach of any educated person regardless of academic specialization.
AI has only strengthened the case: what a humanities student can build in one semester is far greater now than when he wrote those words.