The United States and other advanced economies face unprecedented challenges in technical areas such as energy, environment, and defense. Solving these challenges requires a diverse, highly educated labor force, with professional expertise in science, technology, engineering, and mathematics (STEM). Contributing to the problem of under-production of STEM professionals in the U.S. is the pronounced gender segregation in some STEM professions, especially in engineering. As a consequence, we have a much smaller population from which to develop the needed engineering expertise. This project seeks to help us understand what causes continued gender segregation in STEM fields.
An earlier study conducted by the PIs surveyed and interviewed a group of men and women for five years, beginning with the first year of their college education. This panel included a disproportionate number of young men and women planning to major in engineering, who had demonstrated exemplary achievement in science and mathematics. Yet, after four years of engineering education, shortly before college graduation and entry into the labor market, a significantly smaller percentage of the women than the men planned to pursue careers in engineering. Analyses showed that more women than men reported lower confidence in their ability to have a career in engineering.
The current project revisits these men and women at the next career stage -- 5 years after their anticipated college graduation, and during their early years in the labor market. At this time, the project will collect data that enables researchers to compare the role of individual (confidence), organizational (workplace-related), and social network factors to explain gender specific career track decisions, especially regarding STEM fields. Methodologically, this study expands a unique longitudinal dataset to explain the critical transition from college and post-graduate training to the professional workforce. The theoretical model used adjudicates among the most important contending explanations for persistent gender stratification in professional employment by testing social psychological theories of causal individual and gender differences, organization-level processes, and social capital theories concerning the efficacy of social networks.
Broader Impacts Findings from this research may help explain patterns of attrition from and persistence in STEM fields, and engineering in particular. This important issue is of interest to private- and public-sector employers, current and future professionals, as well as institutions of higher education. Moreover, persistent gender segregation in STEM could compromise the competitive position of the United States in a global economy. Findings from this study may also contribute to policy developments aimed at improving the nation's scientific competitiveness.
Data collection was completed in 2013, and analyses of these data are ongoing. Initial analysis reveals that women who have engineering internship experiences during college have the same levels of persistence as men (i.e., no gender differences). The gender differences in persistence are driven by women who have never had engineering job experiences during college. These differences are depicted graphically in the included figure. Additional analysis reveals that, contrary to expectations, men and women in engineering jobs appear to have similar levels of social capital as measured by standard social network measures (e.g., network density, network constraint as a measure of structural holes and network brokerage). Further analysis will examine whether these network measures' associations with career outcomes are similar for men and women; factors associated with decisions to leave engineering and STEM careers; the role of mentoring in engineering and STEM career persistence; the nature of work-family conflict for those in STEM and engineering careers; and entrepreneurial activities by recent graduates. Further, these data are a 5th wave of data in a 10-year longitudinal panel study. These data will be integrated with earlier waves to examine how experiences and exposures measured during college are associated with career outcomes five years post-graduation.
