Implementing Generative AI in Higher Education
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University rankings play a big part in where a prospective student chooses to go to school.
Although most university rankings focus on prestige, is that really what prospective students care about?
Or better yet, is that the only thing prospective students care about?
This is an important question—especially if your school isn’t always featured on well-known university rankings lists!
How can you make your case to prospective students who’re looking to these lists for guidance that your school is actually a better fit for them?
What can you do to cut through the noise generated by these university rankings to get top of mind with your target audiences?
Dr. Jed Macosko is the President and Research Director at Academicinfluence.com and a professor of Physics at Wake Forest University.
At Academic Influence, they use a ranking engine that assesses influence in the academic world by ingesting, analyzing, and evaluating huge amounts of data. Because of this, the data is less prone to bias and manipulation, giving accurate rankings to universities.
In this episode of The Higher Ed Marketer podcast, we spoke with Dr. Macosko about his insights and resources into how higher ed marketers can use rankings to tell their stories and show the value of their institution.
Standard university rankings like US News and World Report have been active for decades.
Obviously, if you’re on the list, you love to tell your audience about it.
But for the vast majority of schools—really important schools that make a difference in student lives—they never show up on the list.
These kinds of lists tend to be very “one dimensional.” Dr. Macosko explains the overall way university rankings are done:
This ranking that everybody has heard about and has been going since the 1980’s is a fairly one-dimensional kind of ranking.
Certainly, if you go to the US News website, you will see that there are lots of different variables that go into the ranking. But the lion’s share of the ranking that you see is due to prestige. It comes in many forms.
The first and foremost is they do surveys of people at other institutions, and they ask those people to rank each institution that they can. So, if you’re a well-known school, people are going to rank you higher.
Typically, they [survey] the President, the provost, and the admissions deans at all the different schools. So, if you can get to those three individuals and make your case that you’re a great school, great! But most people are going to be thinking about Harvard, Princeton, Yale, Stanford—all those typical schools—when they start filling out their survey.
So [prestige] is where it starts. Now, again, there are other variables, but they don’t change that dimension. If you were to plot the amount of endowment a school has versus their US News ranking, it would be a pretty good correlation. Again, endowment reflects how much people are willing to give to that school because of how prestigious they think it is. So, it ends up being the same thing.
With a system like this, most schools will never make it on these kinds of university rankings.
Perhaps there could be another, more holistic way to show how a college or university ranks among its competitors.
That’s exactly what Dr. Macosko and his colleagues set out to do.
According to Dr. Macosko’s explanation, current university rankings lists depend highly on subjective information, how survey participants feel about their fellow educational institutions.
But to get out of this rut of only ranking colleges and universities by prestige, we need to look for more objective information.
That’s the basis for Dr. Macosko’s ranking system at academicinfluence.com. During our conversation, he pulled back the curtain a bit so we could see how they do their rankings.
Before I even got involved in this side of the educational venture, other people better at computer science were doing this. They had already latched on to two databases, Wikipedia, and Wikidata, which is a place where you can find all of the back end information that goes into Wikipedia.
Wikidata has your name, your occupation, your age, all these things in a nice tablature format. And then Wikipedia, of course, is what we all use all the time. It has paragraphs of information and all that good stuff.
So those two databases were what they were using in order to rank first individuals and then finding out from Wikidata where those individuals had gone to college or where they were employed as a university professor or an administrator in university. However, there were a lot of schools that didn’t have even a single person listed in Wikipedia or Wikidata—really good small schools. So, we decided [that we needed] better big data.
So we went to all of the papers that have ever been published. [To index all the papers that have published], we used the Crossref database and Semantic Scholar. Between those two databases, we got obviously a lot more information about these smaller schools.
[With this information], we were able to rank people that attended the smaller schools, the big schools, the prestigious ones, the not so prestigious ones, and figure out which schools were churning out the best and most influential people, and which schools were hiring and using the talent of the best and most influential people.
Creating a university rankings system based on which schools are producing and hiring the best minds in their fields is a great way to cut through the bias inherent in other listings that rely mainly on prestige.
From a marketing perspective, we can learn a lot from this approach.
Emphasizing the influence our schools have on the world through telling good stories in our content will mean more to students who are a good mission-fit for you than any university rankings list.
Like all of our blog post reviews of The Higher Ed Marketer podcasts, there’s so much more to learn in the podcasts themselves.
Listen to our interview with Dr. Jed Macosko to get even more insights into:
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Featured image via wfu.edu
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