The third year of the CoinDesk Blockchain University Rankings is still, at heart, an attempt to both recognize the role that academic research has played in the development of blockchain technology as well as quantify the impact of individual schools. Our goal has not wavered in these three years: offer the most rigorous and nuanced window into universities’ impact on the blockchain field. Again this year, we’ve ranked schools across the globe with a final total of 240 universities, 15 of which came from outside nominations.
This piece is part of CoinDesk's Education Week
Above all, we want to ensure that these rankings do what they’re intended to do: offer a holistic snapshot of the intersection between this transformative technology and institutions of higher education. It is our hope that, rather than being seen as canonical, a transparent, intellectually defensible ranking can help condense what ends up being an incredible amount of difficult-to-find information (with innumerable factors) down into a more manageable format.
Our official sample size for these rankings, at 240 individual schools, is not nearly the total number of universities that exist around the world. To determine which institutions to focus on, we added schools to the list according to their ability to meet any one of three criteria.
First, we included any school that was listed in the top 150 of any one of the U.S. News and World Reports (USNWR) Best Global Universities (2022), the QS World University Rankings (2022), the ShanghaiRanking's Academic Ranking of World Universities (2022), or THE World University Rankings (2022). This gave us a large initial sample.
Read More: The Best Universities for Blockchain 2022
This setup, however, if limited to just this criteria, could pose a problem: What if a lower-ranked school (as judged by USNWR, QS, ARWU or THE) is doing amazing work, but fails to be considered simply because a few outside sources happened to overlook them in their global rankings? This is far from a desirable outcome. On the other hand, we simply don’t have the resources to closely examine every school in existence, especially when relatively few of them are engaged in the kind of impactful blockchain work that is likely to lead to a place on our rankings.
This might be a good time to give a nod to schools that are vocational in nature, that aim to prepare their students for job skills including blockchain operational ability that are intended to enable a solid middle class life. These schools may not rank high in scholarly impact or global reputation, which likely prevents them from being captured by our initial screening process, but they are doing a great service to their students and society, and their existence should not go unmentioned.
To balance these considerations, similar to last year we added an additional criteria: We also included a call for any school, anywhere in the world, to request inclusion/consideration in our rankings. By opening up our criteria but placing the burden of requesting to be included on the schools themselves, we were able to remove artificial limitations on which schools were considered, while simultaneously maintaining a high level of confidence that any school that took the affirmative step of asking to be evaluated would ultimately be worth our time and resources to examine closely.
The 240 institutions that constituted our sample this year represent some of the best schools in existence today, including a mix of large, traditionally “elite” research institutions and smaller schools, from public to private, from free to expensive, with every continent (with the exception of Antarctica) represented.
To determine final scores, we looked at four primary categories: (1) an institution’s strength in research and academic contributions to advancing the field; (2) the existing blockchain offerings on campus, whether in the form of classes, educational centers, clubs, etc.; (3) employment and industry outcomes; and (4) overall academic reputation.
Each category comprises multiple sub-categories, offering a holistic picture of a university’s presence in the blockchain space. For a final score, we assigned points to each institution proportional to their performance in each category, and normalized their final point totals on a scale from 0-100.
To determine a school’s scholarly impact score, we relied primarily on the Clarivate Web of Science database. We took the total number of publications (all subjects) from each school, and narrowed them to include only blockchain- or cryptocurrency-related papers published between 2018-2022 (including forthcoming papers slated for 2023). From this set we generated citation reports and created subsets in which the first author of the publication was affiliated with the university in question.
The resulting data gave us the key metrics of (1) total blockchain research papers published by university affiliates, (2) how often these papers were cited, and rough numbers on (3) how often the primary researcher on a paper comes from a given institution (the “first author” convention being, of course, discipline-dependent).
Raw numbers, however, don’t always tell the full story. A bigger school with a larger faculty and a hefty endowment, may be putting out more blockchain research overall (while still managing to devote a relatively small percentage of its resources to the field), while a tiny school that dedicates a much more impressive percentage of its overall resources to blockchain research may end up with fewer papers simply due to a smaller overall headcount.
To account for this, we also normalized each data point (where applicable) against the total institutional output. When normalized in this way, a smaller university that is devoting a larger proportion of its research to blockchain will be rewarded relative to a more massive university who is able to pump out a greater quantity of research with less investment. In recognition of the fact that both raw output and targeted output are valuable metrics, both are factored into our rankings, along with the aggregated H-Index of a school’s blockchain publications. For anyone interested in reproducing our dataset, please ensure that a) you have full access to the Web of Knowledge and all Clarivate subscriptions; and b) use our query to filter the results: “cryptocurrenc* OR ‘smart contrac*’ OR blockchai* OR bitcoi* OR ethereum OR stablecoi*”
Campus blockchain offerings
To arrive at a school’s blockchain offerings score we examined multiple facets of their existing campus infrastructure. Campus course offerings are the largest single subcategory that we looked at. The number of available classes (especially when spread over multiple departments, providing an opportunity for a more robust education) shows a deep investment into the space both in the present and for the future. Faculty must be hired, curricula must be developed and administrative buy-in must be achieved. These are not done on a whim, and are usually quite permanent.
The second-largest factor in our rankings is the presence of a dedicated blockchain research center, although we also separately considered smaller initiatives and student-run clubs. Research centers and initiatives often offer unique opportunities for students to get involved in academic work or obtain hands-on experience, and can serve as a gravity well for novel ideas and thinkers (especially when these entities take the additional step of organizing conferences, summits, or other educational events). Research centers, initiatives and clubs all allow students, faculty and the larger community to connect with other enthusiasts, and tend to provide a crucial tether between academia and industry.
Lastly, to round out this category, we gathered data on the nascent but ever-growing set of universities who offer blockchain-related degrees, whether at the graduate or undergraduate level, and sometimes as a concentration within another degree. As a whole, the Campus Blockchain Offerings category is the most consequential component of our methodology.
Employment and industry outcomes
A university’s ability to place students into relevant jobs is an important metric for two reasons: One, it says something about an institution’s cache in the industry, either due to name recognition, personal connections, or institutional pipelines; and two, this is of particular importance to current and incoming students.
A student’s primary goal in obtaining a college education is, after all, often to secure a job in industry. To discover which schools are placing the most graduates in the blockchain field, we looked at the LinkedIn footprint of the largest and most influential companies in the space, as well as their thousands and thousands of employees. To mitigate biases we factored in both raw and normalized numbers wherever possible. Raw numbers are useful for highlighting schools that are placing a high number of graduates into jobs, but larger schools in larger countries will tend to have an advantage simply because of sheer size.
To gather qualitative data, we also surveyed industry stakeholders and other non-students, non-academics to get a sense of how institutions are (subjectively) viewed by those who consider themselves to be outside of academia. This data was quantified numerically, as was information about the number of active industry partnerships (including sponsored research) maintained by each university.
In a perfect world, rankings would emphasize merit, and anonymized, quantifiable data would be sufficient to judge a university's impact in the blockchain space. Realistically, however, the intangibles of a school have an outsized impact on everything from a student’s job prospects, to their ability to get a foot in the door of an internship, to the caliber of speaker that will spend their limited time giving a talk at any given school.
To pretend that reputation doesn’t matter, that history is insignificant, is to do a disservice to our rankings. The effect of a school’s academic reputation on our methodology, however, is dwarfed by every other category except for cost, reflecting both the recent shift away from credentialism and the greater weight that we assign to more tangible, productive metrics.
To determine an institution’s reputation score, we looked at two criteria: (a) existing, overall reputation as calculated by USNWR, THE, ARWU, and QS; and (b) reputation as determined by our own qualitative surveys, which asked both practicing academics and current students to evaluate schools. This data was split according to whether it came from a student or an academic, and quantified numerically.
Similar to last year, there are two common threads in our methodology. First, in keeping with our goal of rigor, defensibility and reproducibility, we used externally verified, quantitative data (e.g., Web of Science) whenever such data was available and normalized this data where appropriate to add as much nuance into our rankings as possible. When we required qualitative data, we sent out open, public, shareable surveys through all available channels and did our best not to limit participation in any way, constructive or otherwise.
Second, we made every attempt to examine each data point from as many angles as possible. As is often the case, any given data point can be seen as a positive in some situations but a negative when seen through a different lens. Normalization is one tool to combat this, but so are things like common sense and a dispassionate analysis of the landscape. Data tells a story, and our goal was to let our data tell as complete a story as we could.
Help us improve our data
In important ways, rankings are incredibly useful for showing very specific data or reducing large amounts of information down into a digestible format, but are also both narrow and inherently malleable (yet another flaw, but perhaps one that can be discussed down here as it’s slightly, but only slightly, less panic-inducing).
Even small changes to the methodology can have outsized effects on the final result, as can outlier data or even researcher-introduced errors. To state that rankings are vulnerable to criticisms of subjectivity and malleability is not intended to marginalize our data or the larger project at hand; rather, we hope that by highlighting the limitations of our output, these rankings will be more useful to a greater number of individuals.
In the open-source spirit, we’d also like to reiterate our commitment to integrity and data transparency. We are more than happy to discuss our methodology, share data, answer questions and address concerns. Interested readers are encouraged to contact Jeanhee Kim.
We hope that these rankings serve as the foundation for a living, breathing resource that goes well beyond an ordered list of schools. We have started and will continue to do this research, but we’re not naive enough to hold the impression that we can build this particular monument alone.
But we believe this resource illuminating one small corner of the blockchain universe has tremendous value – for students seeking a more traditional path into the industry, for academics hoping to collaborate with like-minded individuals, for companies wondering where specific research is being done. As a first step, we’ve started filling out profiles for some of the top universities, but we’d eventually like to have every school represented.
Students can contribute to this by checking their school(s) and having an authorized university representative (e.g., a member of the media/communications/etc. team) contact us if any information is outdated or missing, or if their school does not yet have a profile. Individuals can help by highlighting important research and projects or novel approaches to blockchain education. Schools can help by examining these rankings and using them as a signal for how to improve. Ultimately, what we can all do to help the space as a whole is simple: devote resources to educating students, faculty, and the community about blockchain technology.
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