Brockport created an online early warning system to help flag at-risk students with the use of predictive analytics. Student, faculty, and staff surveys performed at certain points early in the year help to identify students who might need extra help adjusting to a college environment.
Jung said that closely analyzing data “really taught me to look beyond the traditional end-of-term data files that institutions use.”
He predicts that analytics will become more instantaneous and more automated in the next five years, with more integration between systems and programs.
Using SPSS, Wichita State University is creating a unified student course system, said David Wright, the university’s assistant vice president of strategic planning and business intelligence.
“The data system gives business analysts comprehensive data on students, course records, prospects, and degree completion,” Wright said. The system also offers data on financial aid, housing, and other relevant information.
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Wright said the university uses SPSS to identify the best and high-yield student prospects, as well as identifying at-risk students based on information ranging from pre-enrollment statistics, standardized test scores, current academic standing, course completion, and changes in academic behavior including a switch from full- to part-time student status.
Wright said the university’s recruitment, enrollment, and administrative practices have changed as a result of insights using predictive analytics.
“We basically have completely revised the way that we do admissions,” he said. “[We are] truly engaged in evidence-based decision-making using data available through SPSS to make decisions about recruitment, personnel, and vendors. It’s really a paradigm shift from where we were several years ago.”
Using predictive analytics, Wright said university leaders are able to identify which prospective students are most likely to attend the school and which geographic enrollment-related events are best to attend.