Experimental Mathematics{a CURE in Machine Learning

Abstract

Efforts to expand the science, technology, engineering and mathematics (STEM) work-force have been topics of United States policy action for more than 50 years (Hira 2010). Unfortunately, among U.S. undergraduate curricula, STEM has one of the highest attrition rates (Tinto 1993) with less than half of students in the U.S. that enroll in an undergraduate STEM program ultimately receiving a degree in a STEM field (Hayes 2009). Naturally, the high rate of attrition is a topic of persisting concern. Many programs have been designed and implemented to model best practices in retaining students in STEM disciplines. One retention strategy is to engage STEM undergraduates in research experiences, and a number of programs have been implemented to provide such experiences. The Towson University Research Enhancement Program (TU REP) is one such program. This cohort-based program supports faculty in the development of course-based undergraduate research experiences (CUREs). In this note we describe a CURE in machine learning offered by the Towson University Department of Mathematics whose development was supported by TU REP. We categorize this course along the spectrum of traditional, inquiry, CURE and internship in each of the five dimensions characteristic of a CURE