This is an unconventional methods course, because we’ll be looking at two very different kinds of methods; literature and code
You must attend class each week having completed the assigned readings and ready to discuss them. Note that the schedule also includes a number of optional explorations of the algorithms; these are for your edification only.
To help consolidate your programming abilities, there will be weekly problem sets. The first can be completed in any form you like; later ones should be mailed to me as R Markdown Documents. (This is the format I’ll be sending them to you as.)
They should be completed weekly, and e-mailed to me before the start of class. Problem sets are required but ungraded–I understand that you may not be able to complete them every week.
They also
Once we get our feet wet, I’ll ask you to post results of data explorations online. If I were you, I’d do this on a blog or straight to social media. Also keep them coming to class. This can be on one of the large unstructured sets I provide, or another data source you work out with me in class.
After break, we’ll be exploring a series of specific algorithms. Some we’ll go over in depth in class; others we’ll only touch on obliquely. Based on the data from class you find most interesting (or data of your own, we’ll work to determine which of those algorithms may make sense as a transformation. You’ll then write up a short version of the exploration for the course blog, present it briefly in class, and then revise your post in response to comments.
If you are taking this under the guise of a research seminar with your own materials, you should produce a multifaceted analysis with a reflective, methodological take on the data you bring to the class. This could either take the form of an explicit journal article for a digital humanities audience (I would mirror those in what used to be called Literary and Linguistic Computing) or a 10-20 methodological appendix to a larger work (such as a dissertation) giving the details of an analysis that may take only a few pages in a more traditional work. You’ll consult with me over the semester about how best to integrate your sources with materials from class
If you are taking it as a readings course, you still should create something. As we move into the later weeks of the semester, you should figure out which of the the various data sets we’ve used may be particularly interesting and find a way to build out on the techniques and strategies to create something novel. Most likely, this will be an experiment along the lines of the “Quantitative Formalism” pamphlet we read later. In it, you will take the fundamental advantages of a programming environemnt combine some of the various methods and strategies we’ve learned in a programming environment, or build out some new ones. Appropriate products might include a large-format print map, a set of blog posts exploring generic distances, or
This is an advanced graduate seminar; I hope that the syllabus will change in response to your own interests and readings. The last week, in particular, will be decided by vote.
This flexibility may cause problems of “versioning”: what version of the syllabus should you believe? So for the record, the priority for what to do consists of:
Grading in this course is thorny. As graduate students, you should be starting to get a sense of what is important to you; I’m not going to quiz you on the parts of books that you find interesting.
At the same time, a small seminar requires focused engagement from all students (and from the faculty member, it should go without saying). So we can’t just go all loosy-goosey here.
Instead, we’ll use a form of ‘contract grading.’ That means: you tell me affirmatively what you want to accomplish in this class and for what grade, and I’ll contract with you to allow that.
Example Template
I will:
- Attend every class
- Read all of the assigned texts to the point and come with established opinions about them.
- Work to complete all of each distributed workset before class.
- Support my peers in the class in the way that best supports their learning (which sometimes entails giving ‘the answer,’ and sometimes does not, but always entails treating them respectully).
- Work to develop my own data source, and find 4 jumping off points where I apply methods from class to it.
- Read and review one book or article not on the syllabus and present in one week.
- Produce a web-based final project looking at data intended for my dissertation, improving the jumping-off points.
You shouldn’t use precisely this template! It might be too much for you. Or you might want to move in slightly a different direction. You might not have a dissertation data, say. But conversely, you can’t remove the bit about treating your peers respectfully.
You can also demand additional things out of me. Generally I’ll give a once-over to the problem sets–but let me know if you want detailed comments on your code.
E-mail a proposed contract to me by Wednesday in the second week of classes.