Broadening the Participation of Women and Underrepresented Racial/Ethnic Minorities in STEM: A Mata-Analytic Lens on the Social Cognitive Interest, Choice and PersistenceHypotheses

University Of Maryland, College Park, College Park MD

Investigators

Abstract

There have been numerous calls to expand and diversify the nation's workforce in science, technology, engineering, and mathematics (STEM) fields. In response to these calls, there has been a growing literature on psychological and social variables that might predict and promote engagement in STEM-related educational and career options. Social cognitive career theory (SCCT) has proven to be a useful framework for guiding many studies of STEM engagement and retention, including research focused on women's and underrepresented racial/ethnic minorities' participation in STEM fields. The proposed project will use meta-analytic methods to integrate findings from over 45 individual studies that have tested SCCT's hypotheses in the STEM domain. The findings of this meta-analysis will (a) enhance understanding of theoretical mechanisms that underlie engagement in STEM fields; (b) enable assessment of SCCT's generalizability across gender and race/ethnicity; and (c) provide a robust empirical basis for SCCT-based interventions designed to attract and retain diverse persons within STEM careers. Participating organizations include University of Maryland (primary) and University at Albany, State University of New York (partner). The potential audience for this project includes researchers, practitioners, educators, and policy makers who are interested in broadening the participation of women and underrepresented racial/ethnic minorities in STEM fields. The project will employ a meta-analytic approach to synthesize the findings of individual studies that have been conducted over a period of 32 years (1981 to 2013). The studies to be included in the meta-analysis will be obtained through a comprehensive search of online data bases and a manual search of relevant journals. Both univariate and multivariate (structural equation modeling) statistical techniques will be used to integrate bivariate effect sizes and test SCCT models by gender and race/ethnicity in the context of STEM fields. The meta-analytic findings are intended to provide STEM policy makers, educators, researchers, counselors, and other professionals with a theory-based and empirically-supported understanding of factors that promote the engagement of underrepresented people in STEM fields. This understanding can be used to inform interventions for expanding the diversity of the STEM pipeline. The project will also provide opportunities to train and mentor a diverse group of graduate students and junior faculty members (the team will include women and students of color), fostering their ability to perform theory-driven research and building capacity for future studies on equity in STEM participation. Resources created by the project (e.g., meta-analytic codebooks, a database of SCCT research in STEM fields, correlation matrices) will be made available to other researchers. The research team will disseminate the findings widely to scientific, education, and other communities through such means as conference presentations, journal publications, a project website, and development of evidence-based practice guidelines.