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Learning to Do Research the Hard Way
August 6, 2014 - 8:22pm

One of the issues that came up as librarians on Twitter kicked around the pros and cons of tenure for academic librarians (a conversation started in a blog post by Meredith Farkas and followed up by Maura Smale, Anne-Marie Deitering, and Wayne Bivens-Tatum, among others) was that we lack research training. That may seem odd for people who so often provide undergraduates with . . .  well, a kind of research training, but our fairly short and generally practice-focused graduate programs don’t typically include much training in research methodology. I don’t blame the programs. There’s only so much time and few librarians would argue that we should spend more years and money getting credentialed as librarians. Many academic librarians have advanced degrees in other fields that may have immersed them in research methodologies, and LIS programs often offer or even require some sort of methods course. (For me it was statistics, taught by a professor who seemed a little weary after years of facing so much resistance from proto-librarians who were convinced they were bad at math, would never need to use statistical analysis, or simply found it disconnected from their idea of what librarians did for a living.) But we don’t typically get the kind of immersion in the methods and practice of research found in other fields, and our interdisciplinary leanings mean we don’t really have a well-established methodological framework for conducting research or an apprenticeship doing it.

A conference on assessment methods for librarians generated another intriguing Twitter conversation, this one partly about research ethics. Librarians are exploring the potential for using learning analytics to study how libraries contribute to student learning, both to fulfill assessment mandates and to actually do what assessment supposedly is for – to improve student learning. This potential for gathering and querying large data sets is a hot topic in education right now, and the promise that we can use data to pinpoint problems and intervene at the individual level is pretty thrilling – and harmful to my knees. Because these conversations make them jerk a lot. Being advised that librarians shouldn't be afraid of privacy concerns makes me toss some words around - because I think we should be concerned about privacy fears. 

I’ve weighed in on why privacy matters elsewhere and I won’t critique the ways that data mining for education has the potential to replace human judgment and one-to-one interactions with algorithms. Other people have done that better than I can. But I was struck by an interesting intersection of these two conversations. Scholars who receive extensive training in research methods are schooled not just in how to gather and interpret data. They learn how and why it must be done ethically. They know how complex it is to conduct research involving human beings without putting them at risk – and they know why privacy matters.

Librarians who are largely DIY researchers have two models in front of them: the scholar’s way and the corporate way. We’re used to learning how to improve web designs from tech blogs. We’ve designed surveys based on the advice of marketing gurus. We know that Google and Amazon and Facebook violate privacy in troubling ways, but since they set the standard for UX we sometimes think it is time we stopped being so fussy about privacy. So knee-jerk. So cautious.

For some, the pushback against the recent PNAS article describing how Facebook manipulated people's timelines to influence emotions was overblown because it happens constantly. Some argued "that's just how the Internet works," confusing the companies that currently dominate the Internet with the Internet, which actually doesn't work that way. Others felt a prestigious journal should have higher standards for research ethics (and PNAS itself issued a "statement of concern.") There's clearly a different set of rules for scholars than for corporations, and I favor those followed by scholars. 

The conversations on Twitter were especially intriguing to me in the way researchers trained in anthropology methods pushed back on some librarians’ enthusiasm for learning analytics and the ways privacy concerns were sometimes described as "knee-jerk" obstacles to progress. They know how much work it is to use student data ethically. They know it can be done. They have been trained in how to design research that doesn’t make IRBs flinch, that doesn't abuse the trust of research subjects. Although some assessment projects are exempt from IRB oversight, that doesn't mean they should be exempt from ethical practices.

As DIY librarian researchers like me learn to do cool things with data, we need to learn how to gather and analyze it according to scholarly, not just industrial, standards. I hope when we look for ways to improve our research skills and methods we learn from scholars like these. Maybe it’s the hard way, but it’s the right way.

 

 

 

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