Predictive analytics determines student success

Forty-one percent of universities, including UT–Austin, are using predictive analytics for targeted student advising, adaptive online coursework or forecasting class size and financial aid need, according to a research paper  released by think tank New America.

Manuela Ekowo, one of the paper’s researchers and policy analyst at New America, said when she started working on the paper she was interested in learning more about how universities were using different analytical tools to support students of color, low-income students and first-generation college students.

“Predictive analytics [are used] to recruit students, to offer them financial aid, but also for powering the early alert system that helps identify students who may be at risk of either failing a course or dropping out of school,” Ekowo said. “Advisors intervene before those outcomes pan out.”

Data used by universities to predict success includes current student transcripts, past student transcripts and family income. 

Predictive analytics are also used in adaptive online courseware, which is tailored to a student’s educational needs, Ekowo said.

Approximately 500 entering freshmen who are least likely to graduate are identified using predictive analytics and offered a spot in the University Leadership Network, which aims to help students graduate in four years, said UT-Austin President Gregory Fenves at the Board of Regents meeting Wednesday.

Through advising and leadership training, the program is able to help students graduate on time. Up to $20,000 in scholarships are also offered to students in the program, along with opportunities for on-campus internships, Fenves said in his presentation.