A handful of companies have sprung up in the last few years, working with perhaps 200 universities. But the approach is in its early stages on campuses. Health care companies and sports teams have been working with predictive analytics for years. Big data is one experiment in how to do that. Such outcomes have led parents and politicians to demand colleges do better. Students who drop out are in even worse shape. That’s no small concern for families shouldering the additional tuition or student debt (an average of more than $28,000 on graduation, according to a 2016 College Board report). Crunching hundreds of thousands and sometimes millions of student academic and personal records, past and present, they are coming up with courses that signal a need for intervention.Ī little less than half of the nation’s students graduate in four years given two more years to get the job done, the percentage rises to only about 60 percent. Georgia State is one of a growing number of colleges and universities using what is known as predictive analytics to spot students in danger of dropping out. Algebra and statistics, it seems, were providing an essential foundation for later classes in biology, microbiology, physiology and pharmacology. The analysis showed that fewer than 10 percent of nursing students with a C in math graduated, compared with about 80 percent of students with at least a B+. “But if you got a low grade in your math courses, by the time you were in your junior and senior years, you were doing very poorly.” “You could get a C or an A in that first nursing class and still be successful,” said Timothy M. So they were surprised, after an analysis of student records stretching back a decade, to discover what really made a difference for nursing students: their performance in introductory math. At Georgia State’s nursing school, the faculty used to believe that students who got a poor grade in “Conceptual Foundations of Nursing” probably wouldn’t go on to graduation.
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