Retention and graduation rates in science, technology, engineering, and mathematics (STEM) careers are a worldwide concern because of the shortage of professionals in STEM fields. While there is a high need for computer professionals in industry, enrollment in computing programs has not kept pace with that demand. This is further exacerbated when the data is disaggregated on the basis of race and gender. Exploring patterns regarding race/ethnicity and gender can help education researchers and the computing community to reveal the hidden stories that help them provide guidelines, strategies, and/or mechanisms that lead to enhancing the persistence of underrepresented minority students in these fields. This study was conducted using a subset of a longitudinal database - Multiple-Institution Database for Investigating Engineering Longitudinal Development (MIDFIELD) to determine the computing “stickiness” of students in computing fields across multiple U.S. institutions. For the purpose of this study, computing stickiness is defined as the likelihood of graduation (the fraction that “stick” to the program or persist) for students who came into contact with a computing program. Contact is considered any student which declared a major or took a course in a computing discipline, at any time during their studies. Findings confirm variations in disciplinary stickiness by race/ethnicity and gender in computing majors. Results show that not only do White/Asian students dominate the enrollment in these disciplines, but they have the highest stickiness. That means that not only are Black/Latinx students less attracted to these majors but also that when they do explore these majors, they choose not to stay.
