Predictive Analytics and Student Success

Vincent Tinto Speaking at CSUN about factors that influence student retention in 2013 (left). “We are told that we have doctorates and, therefore, we know how to teach.” In 2015 Shaun Harper spoke from same podium and explained that “teaching is an opportunity to engage with the student and affirm that they belong here and that we believe they will succeed.”

In our own research, we are attempting to determine the factors that lead to (or may impede) student success on our own campus utilizing the tools of data mining, machine learning, descriptive statistics, and predictive analytics. Our focus is on the student, not on the mathematics. The ultimate goal is to improve student success, retention at the university, and increase graduation rates. 

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