Higher education Turns to Data Analytics to Bolster Student Success
Colleges and universities collect and analyze real-time Student data to identify and support at-risk students.
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Wylie Wong is a freelance journalist who specializes in business, technology and sports. He is a regular contributor to the CDW family of technology magazines.
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In an effort to improve student retention, Gannon University administrators are using data analytics to identify at-risk students — and they’re doing it even before freshmen students set foot on campus.
For example, statistics show a strong correlation between high school GPA and first-year college performance, says Steve Mauro, vice president for strategy and campus operations at Gannon, a private Catholic university based in Erie, Penn.
“We know the threshold that puts them at risk, so when we accepted these new students, we made sure we paired them with advisers and had them sign up for classes that focused on their strengths their first year, and avoided classes where they had weaknesses,” he says. “That way, they can get off to a good start.”
Higher Education institutions are increasingly investing in data analytics to identify students at risk of dropping out, paying particular attention to first-generation students and those who come from low-income backgrounds or historically marginalized communities.
When colleges identify at-risk students, they can intervene with technology, support services and campus resources, such as tutoring and financial aid, to help students succeed academically and flourish on campus.
“Higher education is shifting from expecting students to be ‘college ready,’ and instead, they are increasingly recognizing that they need to become ‘student ready,’” says Kathe Pelletier, director of EDUCAUSE’s teaching and learning program.
In fact, demand for student success analytics increased by 66 percent during the pandemic as most colleges and universities pivoted to remote learning, according to a 2020 EDUCAUSE survey .
DIVE DEEPER: Colleges innovate to support at-risk students, inside and outside the classroom.
Gannon University Fosters Student Success
Gannon, which began using data analytics four years ago, uses a homegrown application with a central database that collects and aggregates more than 100 student data points from applications across campus.
A computer model determines which data points are most important for student success and figures out which students have those risk factors, Mauro says.
Administrators focus on three areas: students’ academic preparation and performance, financial well-being, and engagement, such as whether students have developed a community on campus, he says. More recently, the university has also monitored students’ health and wellness, especially as students dealt with increased anxiety and stress during the pandemic.
“We use technology to identify what risk factors are most present and which students have them so we can form interventions for students even before a problem becomes a problem,” Mauro says.
If students say, ‘I’m thinking about leaving,’ we provide targeted outreach to those students.”
Tadarrayl Starke Associate Vice Provost for Student Success, University of Connecticut
For example, incoming freshmen may struggle with homesickness or feeling as if they don’t belong. Gannon’s data shows that first-year students who do not attend orientation or fill out a college survey are more likely to not engage in campus activities in their first semesters, Mauro says.
To help these students create community, the university proactively pairs them up with advisers and other students to make sure they have connections and people to talk to.
“It really helps them get plugged into the university,” Mauro says.
Gannon staff and administrators check a data dashboard four or five times each semester, including at key grading periods.
