WIP: Exploring STEM Students' Enrollment in Entrepreneurship Education Programs: A Binary Logistic Regression Approach

This research WIP paper investigates STEM students' enrollment in entrepreneurship education programs (EEPs). Previous research has suggested that STEM careers are important for the economic and technological development of today's society. To prepare students for STEM careers, a growing body of literature indicates that EEPs allow STEM students to develop skills to be competitive in a wide range of STEM careers and industries. Despite the benefits described above, enrollment of STEM students in EEPs has received less attention among researchers. This lack of research requires attention because it limits the understanding of what STEM students are gaining from these elective EEPs. The objective of this study is to enhance this understanding by exploring the predictive relationship between STEM students' background (i.e., major, undergraduate GPA, socioeconomic status, race/ethnicity, and sex) and their enrollment in EEPs through a binary logistic regression model. Binary logistic regression is commonly used for predicting the probability of the outcome in binary classification tasks (i.e., enrolled or not enrolled in EEPs). The data set included records from 23,411 undergraduate STEM students enrolled at a public research university in the United States. The major distribution is as follows: Science (14%), Technology (23.9%), Engineering (60.3%), and Mathematics (1.8%). The binary logistic regression results identify notable classification patterns. First, when compared to Engineering students, Science and Mathematics students are less likely to enroll in EEPs, but Technology students are more likely. Second, students' GPA is negatively related to their enrolment in EEPs. Third, students coming from low SES are more likely to enroll in EEPs. Finally, students' race and sex seem to be non-significantly related to their enrolment in EEPs. We provide implications of these findings, highlighting key preliminary results and the future steps we intend to perform in this research project.