As a graduate student, I studied education policy. However, I approached the study of education policy through the concepts and methods of a unique subfield, comparative and international education. I call this subfield unique because it was (and is) remarkably diverse, including scholars and practitioners from all over the world. This may explain the vast array of concepts and methods employed to study education policy. The research I read and conducted as a graduate student tended to be highly theoretical and critically-inclined. Much of the research involved emergent theories, discourse analysis, and qualitative methods. There was, of course, quantitative research that drew upon more “traditional” theories happening. Yet, this research often seemed peripheral and treated with a good deal of skepticism.
Four years ago, I started teaching in a higher education administration program whose focus was much more domestic. I was hired to teach many of our law, policy, and finance courses, with a focus on U.S. higher education. In order to effectively teach, I needed to get acquainted with the education policy research that focused on U.S. higher education. I started reading and paying attention to higher education policy scholars and the type of research they were doing. Soon enough, I was doing my own research that focused on U.S. higher education management, administration, and finance. One of the things that has become clear to me in transitioning into the world of U.S. higher education policy research as something of an outsider is the dominance of quantitative methods and, more specifically, statistical analyses commonly associated with economics (i.e., econometrics). Far from peripheral, economic analyses in U.S. higher education policy research is very much centerstage.
Over the past year, I’ve developed a sensitivity to the influence of economics and economic approaches in U.S. higher education policy research. Many of the most influential U.S. higher education policy researchers seem to have backgrounds in economics, or they trained under economists housed in an education department. Many of the conferences, think-tanks, and journals that focus on U.S. higher education policy often feature the work of economists and publish economic analyses. These analyses are often based upon large datasets spanning many years, and they increasingly use quasi-experimental designs and randomized control trials. In the last year or so, I’ve seen a number of job ads for faculty positions specifically related to higher education policy that list knowledge of advanced quantitative methods and econometrics as desired qualities. There was even an invite-only higher education policy event in which all of the speakers were economists.
It’s possible that what I’m observing has long been true: U.S. higher education policy research consists, by and large, of economic analyses. However, my contention is that, in the current era of accountability, efficiency, market-competition, and big data, the influence of economics in U.S. higher education policy research has increased. Assuming this contention is at least partially true, the rest of this blog explores some possible implications. I’d like to emphatically state that I’m not opposed to quantitative research or econometrics. Some of my best scholar-friends are economists! I’ve even dabbled in some finance research (with talented, more experienced colleagues) that uses econometrics. I’ll also readily admit that the sophistication of many analyses coming out these days far outstrips my abilities. So, my sensitivity to this topic partially stems from a feeling of inadequacy and a desire to carve out space for the kind of work that I generally do in the midst of increasing economification (not a word, but I’m making it a thing).
Possible Implication #1 - Historical and Qualitative Work as a Nice Complement
I know there are many people out there who, like me, do historical, qualitative, and mixed-methods projects that inform or intersect with policy discussions. I’m not suggesting that these studies are ignored in the policy world, or that more quantitatively-inclined scholars don’t read/trust them. Nevertheless, I think one possible implication of the influence of economics in U.S. higher education policy research is a faith in quantitative research producing truth/knowledge, while qualitative research is a nice complement--something to attach a story or “face” to quantitative results. That faith in quantitative research, even with all of its variables and controls, could create blindspots, and the marginalization of qualitative research could yield major holes in our understanding.
Possible Implication #2 - Faculty Members Trained Outside of Education
It’s possible that education departments won’t be able to keep up with the methodological sophistication of higher education policy research and, therefore, won’t be able to train/graduate PhDs with skills to compete on the job market. On the other hand, disciplines with strong traditions in quantitative research, particularly economics and sociology, will produce people with these skills (though they may be lacking experience in education settings as teachers and practitioners). So, we might see an increasing number of higher education policy scholars that have PhDs in economics or sociology. And more graduate students may opt to enter those programs instead of pursuing education degrees in the hopes that it helps them stand out on the job market.
Possible Implication #3 - Problems of Access/Exclusion
The trend of higher education policy research involving increasingly sophisticated quantitative methods raises some questions about access and exclusion. Having a strong educational background in statistics will be an advantage, and it strikes me that exposure to statistics early might be privilege available only to a select few. Only certain types of graduate programs at certain types of institutions will be able to provide the methodological training for doctoral students to be successful on the job market. In short, it’s not easy to just jump into higher education policy research these days. Just learning how to code in a statistical analysis program is akin to learning a second language. The end result could be that the circle of higher education policy experts is a small and exclusive club and, like many exclusive clubs, lacking in diversity.
Possible Implication #4 - Policy Gets Better (If It’s Understandable)
Okay, so this post can’t be all doom and gloom. One positive implication is that our research is gets better--it can more effectively identify causes and measure effects. We may be able to more persuasively argue which interventions work and which policies are harmful. We can put all of this good research to use in reversing inequities. Of course, this is predicated on policymakers reading and using research to shape policy. There is probably a negative association between advanced quantitative analyses and policymakers understanding and using the results of said analyses. Which brings up another implication…
Possible Implication #5 - Data Visualization Becomes More Important
Being able to explain or translate higher education policy research becomes more challenging as the analysis becomes more complicated. Another implication of this process I’m calling the economification of higher education policy research is that scholars have to not just be able to run analyses but also create easy-to-read graphics and visualizations. It’s easy to foresee a whole range of new course offerings and conference presentations dedicated to data visualization.
Possible Implication #6 - Quantitative Skills as Professional Legitimacy/Currency
Finally, because I’m running out of writing time and running out of mental steam, we may increasingly see that scholarly legitimacy in higher education policy research is based upon one’s abilities to conduct advanced statistical analyses. As a primarily qualitative researcher, I can certainly produce research and engage in policy conversations. But invitations, grant money, and opportunities will mainly flow to more legitimate policy scholars.
All six of these possible implications will likely drive some of my colleagues nuts because they aren’t really based on data. I’m simply watching, listening, reflecting, and writing. So, there’s a good chance my biases have entered my reflections and I’ve fudged a few things. However, in the event that a few of these implications come to pass, I think there’s some cause for concern. There may be costs and unintended consequences of the economification of higher education policy research. I think there’s value in re-calibrating some and approximating what I experienced as a graduate student in comparative and international education by welcome a more diverse mix of people employing a wider variety of concepts and methods.