Instructor: Daniel Carter, Ph.D.

Week of April 2

For this week I’d like you to read two article-length pieces that will ground our discussion of computational data analysis as both a research process and also as something we teach students. I give a quick introduction to myself and the readings in the video below.

Read

I recommend you read these in this order:

• Big Data, new epistemologies and paradigm shifts by Rob Kitchin
• Teaching Quantitative Methods: What Makes It Hard (in Literary Studies) by Andrew Goldstone

There are additional readings on the Resources page under Data Analysis.

Discussion

Over the week, I’d like us to have a discussion on Slack about these two articles. I’m particularly interested in how you see issues around methodology, epistemology and institutional resources playing out in your own fields. Are you familiar with the kinds of research that Kitchin talks about? What does it look like in your field? What role does programming play in your field, both in research and in doctoral training? To what extent do you see the effort to learn these skills matching with the payoff? What institutional challenges and/or barriers do you experience or foresee in your current situation? I’m looking forward to learning more about you, where you’re coming from and what your experience is as I plan our in-person activities. Use the #dataanalysis channel.

Also, please provide feedback in the Mid-Workshop Evaluation. This will help us as we tweak the curriculum for the in-person session.