Identifying and Reducing Gender Bias in STEM: Systematically Synthesizing the Experimental Evidence

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This project will integrate high-quality experimental evidence on the existence of, and strategies to reduce, gender bias in science, technology, engineering, and mathematics (STEM) fields, including how gender bias may intersect with other identities such as race and ethnicity. Biases favoring men could thwart women’s training and careers in STEM fields in many ways, but research also suggests promising interventions for changing biased cultures and structures. This project will synthesize four decades of research to understand the postsecondary and workforce contexts in which bias against women in STEM remains especially pernicious and the interventions that can most effectively reduce such biases. The results will inform scholarly debates such as whether biases against women in STEM have reduced over time, persist in nearly all training and career contexts, or vary in more nuanced ways across contexts and STEM fields. The work ultimately aims to help organizations (a) disrupt the culture of peer and mentor discrimination that could directly block women’s entry into STEM fields and (b) mitigate the accumulated experiences of discrimination and exclusion that could drive women out of STEM. Dissemination of project findings will especially focus on actionable insights for higher education institutions, such as bias reduction strategies that male and female STEM faculty can adopt in their teaching, mentoring, and service activities. This project is funded by the EHR Core Research (ECR) program, which supports work that advances fundamental research on STEM learning and learning environments, broadening participation in STEM, and STEM workforce development.The synthesis will include two sets of studies: (a) studies testing for the existence of gender bias in STEM fields (bias identification studies) and (b) studies evaluating interventions to reduce such biases (bias reduction studies). For both, the synthesis will focus on randomized experimental designs, such as changing the name on a résumé from John to Jennifer (bias identification study) or assigning some individuals to receive diversity training or not (bias reduction study). Focusing on experimental designs maximizes the rigor of the evidence to be synthesized because they help rule out potential confounds when testing for bias and evaluating intervention efficacy. All STEM fields will be eligible for review, spanning undergraduate education to the academic and nonacademic workforce, to provide a robust and thorough understanding of where gender biases exist and how interventions can reduce them. Contrasting with traditional literature reviews, the team will use rigorous systematic review and meta-analysis methods to improve transparency of the review process, reduce reviewer bias, and ensure the project’s findings are robust and comprehensive of existing high-quality evidence. Statistical analyses will focus on understanding how specific contextual features (e.g., formal accountability, disciplinary field, intervention design) can explain mixed findings on identifying and reducing gender bias in STEM. This knowledge can help universities, companies, and other organizations pinpoint where targeted intervention is most needed and which strategies will be most effective for mitigating bias.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.