2023 ASEE Annual Conference & Exposition

Although efforts have been made to broaden participation in computing, ongoing reports and counts in the field continue to illustrate the need to improve engagement and retention. There remains a minoritization of Black or African American men and women, Hispanic or Latinx men and women, Indigenous men and women, White women, and Asian women. As such, it is vital to explore trends over time and find new potential avenues to attract students to computing. Developing a better understanding of students’ trajectories, and potentially the variable ways they may enter the major before obtaining their degrees, can offer avenues for recruitment. We conducted a quantitative analysis of switching behaviors using the Multiple-Institution Database for Investigating Engineering Longitudinal Development (MIDFIELD). The theoretical framework of intersectionality guided the inquiry as we examined patterns and disaggregated them by gender, race, and ethnicity. We sought to explore trends in switching behaviors for those entering computing, including potential variations in: 1) the major in which students earn their first undergraduate degree; and 2) different intersectional groups. We focused specifically on students from CIP6 11, Computer and Information Sciences and Support Services. Our analysis of MIDFIELD illustrated that many intersectional populations of students who transferred into computing came from another engineering field. However, several racial and ethnic groups of women primarily entered through non-STEM fields. Among these women, those who identified as Black and those who identified as Hispanic or Latinx most often switched from a Business major, at 31.5% and 29.4%, respectively. Meanwhile, women classified as International and those who identified as White most often transferred from the Liberal Arts/Humanities, at 41.7% and 32.7%, respectively. The findings of this work suggest that women who enter computing may do so through distinctive pathways. Going forward, this provides new opportunities for educators and administrators to consider what may appeal to different intersectional populations of students, particularly for women that identify as Black, Hispanic or Latinx, International, and/or White. This study offers information that could shape what topics may attract students to a computing field and how they could be incorporated into computing lessons or examples.