Optimistic Applications of Data

Earlier this week two articles appeared almost side-by-side in my Google Reader feed: David Brooks’s New York Times op-ed “The Philosophy of Data” and Rob Kelly’s “A Data-Driven Approach to Student Retention and Success,” in the Faculty Focus newsletter. Like anyone at all involved in digital humanities, I’m used to reading about how big data is changing our research methods and opening up new kinds of questions. (This New York Times piece, widely promoted on Twitter, is just the most recent of many articles that talk about “big humanistic data” in the popular press.) But these two articles together got me thinking about how what Brooks calls “the rising philosophy of the day” might be affecting other aspects of our professional lives.

Brooks confesses himself initially skeptical of “data-ism,” reducing everything to the quantifiable, but argues that there are two things data does really well:

  1. Data tells us when our intuitions are wrong (Brooks give the examples of purported “hot streaks” in basketball, which don’t exist, and campaign TV ads, which aren’t as influential as we think they are).
  2. Data illuminates patterns we might not otherwise see. (Brooks cites James Pennebaker’s work on first-person pronouns in The Secret Life of Pronouns)

Kelly speaks to a specific application of collected data: retaining students. Colleges collect a lot of data, mostly about admissions. There’s a lot at stake, since this data determines schools’ ranking on lists like U.S. News and World Report. News stories about universities’ data collection often focus on schools fudging the numbers, but Kelly’s article is more optimistic about the ways in which this data can be used to actually help students. He quotes Margaret Martin of Eastern Connecticut State University, who notes that “it’s hard for the general faculty population or administrator population to really have a handle on the data that is really driving decisions.” Kelly continues:

Faculty involvement in this initiative is essential, and there have been two things that have motivated faculty to participate: the desire to better serve the students and the potential to engage in activities that employ their skills (and could potentially produce publishable research).

If data can tell us where our intuitions are wrong, or help us see patterns otherwise invisible, how can faculty access that information in a way that’s usable? Surely we all want to better serve our students, and employ our skills, and Kelly’s article hints at a contributions DH scholars in particular can make. Historically at least, humanities scholars have been well-represented in the upper levels of university administrations. As humanities professors develop skills to work with “big data,” I wonder whether these skills will transfer to administrative tasks as well.

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