Open Data for Higher Education: The Road to Democratizing University Metrics


When institutions are gaming national and global rankings with rampant internal citation, indulging in “manipulation around the edges” of experience, or spending huge amounts on crazy golf courses to increase applications by “pander[ing] to the fantasies of 18 year olds”, does it really benefit the students whose applications the institution is seeking? Or the faculty it hopes to allure? How free (and how creative) is research when it’s directed towards institutional citation? How much does the steady increase in tuition fees to support the rankings arms race benefit the students who bear the brunt of the costs? The answer, which should be quite obvious, is very little.

Like every good problem, we need to start with a “why”. What are rankings trying to offer, and how we might go about doing that a little better in this, “The Age of Information”?

Why Rank?

There’s a simple answer: consumerism. Higher education, far from offering students ‘a clear, conscious view of their own opinions and judgements, a truth in developing them, an eloquence in expressing them, and a force in urging them’ (the wish of John Henry Newman), is now a commodity in the labour force—the lowest common denominator for entering many professions. As the demand for graduates increased, the premium on the degree itself increased — and with it, the price for participation.

When an 18 year old is essentially taking out a mini-mortgage to pay for their education, the need to make the right decision weighs heavier. Choosing well and aiming high is the mark of a great investment.

It’s not that data – or its friendlier relative that I like to term “information” – isn’t valuable in this context: it’s more valuable than ever. But if higher education is going to play the consumer game (and whether it should is another question entirely), the data provided to students needs to be transparent, and reliable in answering a range of questions driven by individual needs.

A forced order ranking is by no means awful, but it does homogenize the higher education landscape, forcing colleges and universities to compete on the same metrics (and to compete using the same tactics). In reality, institutions should be focusing on their key differentiators — the things that will actually appeal to students. And that’s rarely a like-for-like comparison.

“Compare and Contrast…”: Or, A Humanities Approach to College Rankings

In literary studies there is, more or less, a Canon. And there are lists and lists and lists of the “100 Best Novels” – no two completely alike, of course, and most provoking indignant disbelief from critics. But we don’t simply tell our students to read those works — or those authors — to understand their machinations and grammatical habits, their quirks and idiosyncrasies. And we certainly don’t try to formalize and model something so qualitative with quantitative measures. Well, very few of us do.

But in the study of literature, one of the first things students are taught is to “compare and contrast”. We bring our own questions — our own preferences and pet-peeves — to our explorations, and determine not only what’s similar and comparable between greats, but also what’s different and differentiating. It’s this key second aspect that’s missing from the presentations of rankings – and one that would better serve institutions and their stakeholders when it comes to analyzing data.

But that kind of analysis – qualitative consideration over quantitative forced-order ranking – demands a much different approach to the underlying data that’s driving decision making.

The Road Ahead: Open Education Data and Increased Data Fluency

But the data isn’t always there for the diving. Sure, it’s compiled in bits and pieces by various studies (with a helpful “Best Of” available here). Institutions taking part in certain ranking systems and professional services can take advantage of some individual benchmarking. Would-be analysts variously have access to increasing portions of data: the U.S. Government’s Obama Administration made headway into affording students more personalized analysis options with their Open Data initiative; and South Africa, too, is making headway, with the Centre for Higher Education Trust’s Open Data publishing 26 key indicator metrics for the country’s public institutions along with in-depth guides for use. These are great beginnings, for a data commons, but they are by no means as textured and far-reaching as we might hope to accomplish.

And the journey doesn’t stop there. Not only are we missing a data commons, but access is far from the lowest hurdle; meaningful analysis demands adept statisticians and mathematical modellers moving through the available data to provide insight into its trends, both at large and with regards to the situation and questions at hand. Whether for students looking for the right-fit institution, administrators and faculty members looking to compare spending, or deans looking to promote a more diverse approach to hiring, way-stations are needed on the journey to digital empowerment.

Complicated privacy laws, siloed data, and institutional lethargy all contribute to stalling the start. But, luckily for institutions, Universities UK has gone some of the way to illuminate the promise and perils of Open Data for higher education with An Introductory Guide (2015). And for the digital natives filling the pipeline to University, there are a wealth of data manipulation courses seeping into pre-college curricula and enrichment activities.

With Open Higher Education Data, all of education’s many stakeholders will increasingly be able to answer a range of different questions and access reams of relevant data on a daily basis. But for this to come to pass, Universities need to stop thinking about data-driven rankings, and instead pool their data not in competition, but for mutual edification — thinking along the way about how best to bring their faculty, staff, and students along for the ride.

*Image: Mclek/Shutterstock.


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