Students Want Their Personal Data to be Used to Improve the College Experience, Survey Says

Authored by Meghan Bogardus Cortez

EdTech

 

Using student data to inform educational decisions has been a hot topic over the past few years. Predictive analytics to improve student success, along with data-informed decision-making, were named by EDUCAUSE as two of their top 10 IT issues for 2017. And, as one study indicates, students don’t mind when their colleges track them.

A whopping 98 percent of respondents to an Ellucian survey conducted by Wakefield Research said they want their schools to use their personal data to create an optimized college experience. Also, a majority of the 1,000 U.S. college students who took the survey believe their schools can create this positive change in the next 10 years.

The students surveyed have a laundry list of improvements they want their schools to make: make it easier to track graduation requirements, assist in joining student organizations, aid in course selection and registration. The good news, however, is some universities are already making strides to do exactly what these students want.

Data Helps Boost Retention and Streamline Advising

In the Ellucian survey, 62 percent of students said they wanted their university to improve academic processes like tracking graduation progress and 53 percent wanted to see an improvement in the system for scheduling advising sessions.

EdTech reported on Middle Tennessee State University, which used predictive analytics to create a new-school method of advising: students deemed “at risk” of not graduating received targeted interventions.

But perhaps one of the first to use predictive analytics was the University of Kentucky. UK partnered with Dell back in 2012 to deploy an SAP platform to analyze and predict student graduation likelihoodCampus Technology reports.

“One problem we wanted to address was how to immediately affect student success in the short term,” says Vince Kellen, UK’s senior vice provost for academic planning, analytics, and technologies in a 2014 Dell video.

“Part of our predictive model was to look at students who weren’t exactly hopeless cases, but they weren’t sure bets. Students that had a 50 percent probability of returning. We did some direct work and saw a 66 percent re-enrollment rate.”