About

Or, what did I get myself into?

As the title indicates, this course has two parts: media theory and media practice.

Media theory: This side of the course meets the mandate of 7000-level courses in the English department: this is not a topics course, but rather a general course. This half of the course will give you, to the best of my ability, a high-level preparation in the state of the field of media theory. This will emphatically not only mean new media theory, or theories of digital media (although that will be a major theme of the course). Instead, this “seminar” portion of the course will provide an in-depth overview of the theories of mediation that are structurally important to the contemporary state of the field of media studies.

Media practice: This half of the course will entail a substantial preparation in computer programming, what I am calling critical coding. This half of the course is adapted from new media art pedagogy, especially in first-year “foundations” coursework. However, it differs a bit from this curriculum in the particulars. In place of focusing on foundations for creative practice, our curriculum will emphasize instead some of the conceptual foundations of contemporary computer programming. More to the point, despite the practice-based structure of this part of the curriculum, the desired outcome here is emphatically not getting you ready to make new media art or even digital humanities projects. Instead, the coding curriculum exists primarily for two reasons. The first of these is to foster a humanistic and conceptual understanding of the operation of digital technologies that is grounded in practical knowhow.

The second of these is closely related: the coding curriculum will also provide the experiential data we will think with in the seminar portion of the course. Typically, in literature, film studies, or art history courses, students undergo an encounter with an aesthetic object (a novel, a poem, a film, a painting, etc.) and use the aesthetic experience that arises from this encounter as data to think with (historically, theoretically, critically). in this course, we will encounter some aesthetic objects, but the primary mode of encounter will be that of making: of learning to program, of programming, of designing.

What you can expect to do.

Concretely, this means that we will pursue two activities alongside one another. We will read media theory, talk about it, try to understand it on its own terms, and ask it to help us understand the effects the operation of media has on various domains: politics, history, aesthetics, experience, affect, and so on. We will also learn to code, asking what several actual practices of making with digital media can help us understand about the claims of media theory, especially but not only when it makes claims about the operation of digital media.

To be a bit more concrete about it: you will read media theory and you will write blogs and you will write code.

You will do these on an ongoing basis. What this means is that, unlike a great many other graduate courses, the work for this course won’t be backloaded, with a huge final project coming at the end. Rather, this course is designed to engage you at a consistent (if consistently high) level throughout the semester.

A large reason for this is that learning a computer language is, in many ways, like learning a language. (Funny, that.) And while I am hoping that you will do the work of projecting your newly-won skills of thinking and coding into a larger (hopefully collaborative) final project, you’ll only win those skills if you do them consistently or often, in small chunks. By the same token, much of the writing you will be doing over the course of the semester will be done in small, frequent chunks on course blogs. This is all very clearly described in the coursework part of the website.

What you can expect to learn.

Here is where my real “learning outcomes” go. But really, these aren’t contractually-based items that tell you what you will do by the end of the semester. Rather, they name clusters of experiments and questions that we’ll be working through together: