Mathematics
CoW Retention
Analysis of Student Retention at The College of Wooster
Student Researchers: Glenn Caventer, Ryan Snyder, and Kazuki Kyotani
Faculty Advisors: Drew Pasteur (Mathematics) and Sofia Visa (Computer Science)
The purpose of this project was to analyze data in order to better understand student retention, specifically, students who left The College of Wooster. How can we utilize admissions data to predict the likelihood that a student will leave the College by the end of his or her first year? Using additional information attained during a student’s first semester, how well can we predict the likelihood that a student will leave the College by the end of his or her first year? Which students are most at-risk of not graduating in four years? We attempted to answer those three questions using several methods, such as probit regressions and artificial neural networks.