Big Data Goes to College

Big data

Colleges receive many more applications than students that they can admit; sometimes 10 times as many applications for especially competitive institutions. Universities want well-balanced freshmen classes, and while not everyone has to be a world-class violin player or a youth ambassador to Ghana, it certainly helps. Now, if you are a high school senior, your big question might be: how can I get into the college of my dreams? Big data cannot answer that, but big data can predict factors such as which students may succeed with the least amount of financial aid, among other things. This can help educational administrators narrow the field of students they have to sift through when looking at applications.

Gathering data

First of all: what is big data, anyway? In simple terms, it is the collection and mining of huge amounts of digital data. It promises to "increase productivity and efficiency since institutions will increasingly make decisions based on data and scientific analysis," according to an article by GeniusRecruiter. Venerable business magazine Forbes went even further, noting that data might be the next oil, which remains to be seen. One thing is certain: as our digital world expands to eight zetabytes (that's a lot) by 2015, what is really valuable is not the sheer amount of data, but the knowledge that can be extracted from it.

In these challenging economic times, colleges are increasingly not only looking for the strongest students, but also for those who do not require financial aid and who may actually enroll after they've applied. Detailed information about students is already available for sale by the College Board, which sells its data to more than 1,000 institutions. RightStudent is another one of these services, with the goal of helping colleges find students with particular characteristics, including families' income. The company obtains its data from its parent company, Scholarships.com, which might be a bit troubling to some. However, the main source of data for colleges are the top standardized test makers: the College Board and ACT. These companies gather high school students' data on an opt-in basis throughout high school, according to Inside Higher Ed. The process of analyzing the data and tailoring offerings is called "predictive analytics."

Are we too voyeuristic?

Some might argue that this use of highly sophisticated data is, well, a bit spooky, and there are plenty of skeptics. For instance, a recent article in the Huffington Post brought up a point about similarities between the National Security Agency and college admissions offices. They both use sophisticated data models to help predict behavior, but colleges admissions offices have no ill intent, as author W. Kent Barnds notes. They keep the data for a short time and use it exclusively to find a good match for students and universities, which benefits both parties.

It does, however, make sense for universities to use whichever tool they have at their disposal to try to predict -- and perhaps ensure -- future student behavior. After all, colleges want students who go on to graduate in a reasonable time, as those facts in turn contribute to universities' rankings. The New York Times reported that only 31 percent of students at public universities complete their degrees in four years. Can big data reverse this trend with predictive analytics? We just have to give it the good old college try to find out.


  1. "Does Big Data Know Best? NSA and College Admissions," W. Kent Barnds, Huffington Post, June 19, 2013, http://www.huffingtonpost.com/w-kent-barnds/does-big-data-know-best-n_b_3460096.html
  2. "What Colleges Can Learn from Big Data," Richard Barrington, Edcetera.com, August 26, 2013, http://edcetera.rafter.com/what-colleges-can-learn-from-big-data/
  3. "Big Day and High Tech Attract (and Keep) More Students," Sebastien Dignard, Forbes.com, September 20, 2013, http://www.forbes.com/sites/xerox/2013/09/20/it-and-big-data-attracts-and-retains-more-students-builds-stronger-alumni-base-for-universities/
  4. "Data is the New Oil," Michael Palmer, ANA (Association of National Advertisers) Marketing Maestros, November 3, 2006, http://ana.blogs.com/maestros/2006/11/data_is_the_new.html
  5. "Big Data on Campus," Marc Parry, The New York Times, July 18, 2012, http://www.nytimes.com/2012/07/22/education/edlife/colleges-awakening-to-the-opportunities-of-data-mining.html?pagewanted=all&_r=2&
  6. "Micro-Targeting Students," Ry Rivard,Inside Higher Ed, October 24, 2013, http://www.insidehighered.com/news/2013/10/24/political-campaign-style-targeting-comes-student-search
  7. "Is Data the New Oil?", Perry Rotella,Forbes.com, April 2, 2012, http://www.forbes.com/sites/perryrotella/2012/04/02/is-data-the-new-oil/
  8. "Colleges Are Using Big Data To Predict Which Students Will Do Well -- Before They Accept Them," Neil Ungerleider,FactCoexist, October 21, 2013, http://www.fastcoexist.com/3019859/futurist-forum/colleges-are-using-big-data-to-predict-which-students-will-do-well-before-the

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