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Data Points: Netflix-Like Algorithm Drives New College-Finding Tool

Stories, not statistics.

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Netflix-Like Algorithm Drives New College-Finding Tool

By  Jonah Newman
January 23, 2014

As an admissions counselor at Valparaiso University, Daniel Jarratt noticed that few high-school students really knew what they were looking for in a college. For all the talk about the importance of college choice, most students Mr. Jarratt spoke to knew of a few colleges they wanted to attend but couldn’t articulate exactly why they wanted to do so.

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As an admissions counselor at Valparaiso University, Daniel Jarratt noticed that few high-school students really knew what they were looking for in a college. For all the talk about the importance of college choice, most students Mr. Jarratt spoke to knew of a few colleges they wanted to attend but couldn’t articulate exactly why they wanted to do so.

So on his nights and weekends, Mr. Jarratt, now a first-year Ph.D. candidate in computer science at the University of Minnesota-Twin Cities, started working on a tool that would direct students to the right colleges even if they didn’t know what they were looking for.

He began by downloading data from the U.S. Department of Education’s Integrated Postsecondary Education Data System, or Ipeds, and then researched the science of college recommendation to figure out which data points he should use to compare institutions. He settled on 80 variables that together determine the feel of a college—everything from the number of National Merit Scholars to the types of majors.

Mr. Jarratt then created an algorithm that could take several colleges and figure out how similar they are to one another and—more important—in what ways they are similar. Do they have a lower-than-average graduation rate? More than the average number of students living on the campus? Do a higher-than-average number of students study art or engineering?

Using that algorithm, he could explain what the students could not: what was it that a collection of colleges had in common. From there, Mr. Jarratt could highlight other institutions that shared some of the same attributes.

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Mr. Jarratt’s algorithm is now an integral part of PossibilityU, a website that helps high-school students find the right college.

PossibilityU’s data-driven approach to college matching isn’t new, but Mr. Jarratt’s recommendation algorithm is unique. Rather than starting with a list of questions about what students are looking for, PossibilityU asks users to enter up to three colleges that they are interested in. It then spits out a list of 10 other, similar colleges to consider. A premium paid subscription allows students to compare an unlimited number of colleges and provides application deadlines and other advice.

It’s kind of like Netflix’s movie suggestions, says Mr. Jarratt, who studies recommender systems like those used by the movie service and by Amazon.

Do you like Valparaiso and the University of Minnesota? You might also like Marquette University and the University of Iowa, according to PossibilityU. The tool then tells you that those matches are based on a number of characteristics:

PossibilityU Discovery Engine

  • Similar geographic location.
  • Significantly higher-than-average graduation rate.
  • Significantly higher-than-average number of majors and advanced degrees offered.
  • Slightly higher-than-average percentage of students who live on the campus.

“We’re using the characteristics of colleges to get at the nascent preferences of students,” Mr. Jarratt says.

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In addition, PossibilityU asks students to enter some data about themselves, including their grade-point average, class rank, and standardized-test scores, which it uses to calculate the likelihood that the students will get into the colleges they want to attend. Using data about the amount of grant aid a college gives out each year, PossibilityU also estimates the likelihood that the student will receive merit-based financial aid.

“You should always apply to the schools you want to go to,” Mr. Jarratt says. “But we want to maximize the chance that you’ll get into the colleges you apply to.”

PossibilityU doesn’t do everything you might want it to. For example, it shows a student his or her chances of receiving grant aid based solely on academics, and then points to a college’s own net-price calculator for more-detailed financial-aid estimates. If it incorporated some questions about a student’s financial situation, PossibilityU could show much better data about the actual cost of attending college, which many experts say is one of the biggest barriers to enrollment for low-income students.

A feature that allows students to select those attributes that are important to them would also be a welcome addition. Just as Netflix lets you select romantic comedies and filter out horror films, it would be great if a student on PossibilityU could indicate that he or she wants to search only for colleges with engineering programs or campuses no more than 10 miles from a beach.

Mr. Jarratt is the first to admit that the algorithm isn’t perfect, and he’s using his Ph.D. research to improve it. First on his to-do list, he says, is incorporating data that could accurately show students how much need-based aid they might receive at a particular college. Still, PossibilityU is a powerful tool that puts college data in the hands of high-school students and, more important, gives them a smart way to actually use it.

Jonah Newman
Jonah Newman was a database reporter for The Chronicle.
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