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.
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