New York Times: Big data shows big promise for revamping student support

How universities are using software to elevate student success

See EAB's take on the New York Times article.

Higher education is in transition, with shifting business models, declining financial support, and a renewed focus on outcomes—but big data is emerging as a bright spot in the struggle to redefine an industry, Goldie Blumenstyk writes in the New York Times.

Harnessing data

Colleges track everything from academic schedules to financial aid information—but data is often "stored in different electronic silos," writes Blumenstyk. However, new tools are now allowing colleges and universities to mine that data for insights, prompting targeted interventions and program changes that benefit students.

One early adopter of higher education analytics is Arizona State University (ASU). Using software, the school keeps tabs on the academic progress of at-risk students—automatically. Students whose academic progress or schedules put them at risk of falling behind are flagged for intervention. The school credits the software with raising its four-year graduation rate for low-income students to 41% from 26% over the past several years.

Blumenstyk also highlights the use of predictive analytics at Georgia State University (GSU) via its "major matcher" tool. The tool steers students towards programs they are most likely to succeed in (based on their academic record and 10 years of historical data). Over the course of 2013, GSU improved its graduation rates by 5.1% using the tool and other initiatives.

In depth: Read how Georgia State partnered with EAB to elevate student success

Blumenstyk acknowledges that while some may be uncomfortable looking so deeply into personal data, she argues that ultimately "the tools could help millions of low-income students navigate the academic and financial hurdles that often derail first-generation college students."

The use of big data in higher education is not without challenges. Blumenstyk mentions the example of The University of Maryland University College, which started using automatic "attendance triggers" to flag students who missed classes. After a short time, the school recognized its active-duty military population would often miss class—but not necessarily because of academic trouble. Ultimately, the alerts were "just annoying" she writes—so they were disabled for those in the military.

A national focus

Challenges aside, the use of big data in higher education is gaining national attention. In September, a group of 11 large public universities announced the University Innovation Alliance, which plans to harness big data to improve graduation rates for at-risk students.

Related: Prospective students increasingly use outcomes data to make their choices

The federal government's focus on educational outcomes and value is also driving the national trend toward data-based decision making in higher education. These topics will likely also be discussed at the "Summit on College Opportunity," scheduled for this Thursday at the White House.

Others say the focus on data in education is less political than it seems. Schools simply "have a moral obligation to help [students] succeed," says William Moses, managing director of education programs at the Kresge Foundation (Schaffhauser, Campus Technology, 4/9; Blumenstyk, New York Times, 12/2).

EAB's take

Ed Venit

Ed Venit, Student Success Collaborative

Goldie Blumenstyk's thoughtful op/ed reinforces what we've been sharing with our members through the Student Success Collaborative: Predictive modeling and data mining can be powerful tools to help students succeed, but only if used correctly. For schools that get this right, the results speak for themselves—early SSC members like Georgia State, Southern Illinois, and Purdue University Calumet are seeing some impressive retention and graduation gains, on average between 3% and 8%.

But as Blumenstyk notes, increasing our use of data to track and monitor students raises some important questions. Some administrators and faculty feel that tracking students in this way seems a bit like Big Brother, or at the very least is an invasion of privacy. What's interesting is that the students themselves don't agree. We've interviewed hundreds of current students as part of our research, and learned these 'digital natives' are quite comfortable with others knowing everything about them (look no further than the prevalence of social media as proof). Many even have the expectation that the school is keeping an eye on things and watching out for them.

This isn't hand-holding to them, it's a safety net helping them get a return on their tuition investment. As Tim Renick at Georgia State points out, many of today's students don't have the financial luxury of making mistakes that their schools could easily help them avoid through an analysis of historical patterns of success and failure.

We've detailed insights like these in our Student Success Insights blog. I'd also encourage you to hear directly from Tim Renick, the vice provost at Georgia State, on how they're using data to more strategically advise students and improve graduation rates.


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