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Big data on campus

Clint Boulton | Oct. 18, 2016
Colleges and universities are sifting through reams of data in search of ways to bolster graduation rates.

Learning analytics has also become a priority for smaller schools, such as Marist College. A private liberal arts school in Poughkeepsie, N.Y., with 6,500 students, 4,800 of them undergraduates, Marist also feels pressure from the government to do a better job at keeping students on track for graduation, says CIO Bill Thirsk.

In 2013, Thirsk began piloting the Open Academic Analytics Initiative, an analytics application that aggregates student GPAs, SAT scores and demographic data, and correlates it with information about how often students submit assignments and engage with instructors online. Like Purdue's Forecast, Marist's application is designed to analyze the click impressions students create as they navigate the school's various software systems.

The software takes stock of such details as how fast students click on assignments to review them, how fast they complete their homework and whether they chat with peers to complete team assignments. "We can see very early on which students are lagging," Thirsk says. However, the data is anonymized until a faculty member decides that a problem warrants some attention. At that time, school officials have the option of staging an intervention for the student.

Thirsk says his algorithms can anticipate whether students are going to earn a minimum of a C or lower in the first two weeks of a class with an 85 percent certainty.

Marist's program has been adopted by North Carolina State University, which has about 40,000 students. Lou Harrison, NC State's director of educational technology services, said Marist's model proved 80 percent accurate despite some false positives. "We didn't tweak their model too much at all, and it turns out it was pretty predictive," Harrison says.

Here are some other examples of schools that are finding success with academic analytics:

  • Austin Peay State University in Clarksville, Tenn., in 2011 built an automated engine to inform students of their likely success in a given class based on their past performances, and on the performances of those who took the class in the past.
  • Georgia State University used predictive models to boost its six-year graduation rate from 48 percent to 51 percent from 2012 through 2014.
  • Baltimore's Johns Hopkins University and several schools in the University System of Maryland are using similar programs.

Morgan, the Gartner analyst, says that 30 percent of higher education institutions worldwide will have adopted analytics strategies by 2018.

Privacy concerns

Collecting reams of data is something that public- and private-sector enterprises do on a daily basis to glean insights that, for example, help hospitals improve healthcare, enable municipalities to build smart cities and help companies develop highly targeted marketing campaigns.

But as useful as those initiatives may be, the efforts to collect the data that make them possible raise privacy concerns, and analytics programs in higher education are giving rise to similar concerns, according to Lee Tien, a senior staff attorney at the Electronic Frontier Foundation. Merely possessing data creates potential ethical challenges for an organization. One of the biggest issues is that, while the current use of the data may be legitimate, in the future it could be used for purposes other than what was originally intended.

 

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