For over 25 years, scientists have studied the impact of children’s gender stereotypes about abilities in science, technology, engineering, and mathematics (STEM) domains. These beliefs—that girls and women are predisposed to perform poorly in STEM—could potentially have a compounding, lifelong impact. They could affect girls’ sense of self-efficacy and belonging in STEM learning environments, lower girls’ interest in STEM from a young age, affect their choice of high school and college coursework, and potentially even influence their professional performance and evaluations.
However, the research on this topic has been inconclusive and even contradictory. Some studies have found evidence of the expected stereotype of superior male ability in math and science, but others have found only in-group bias, or even stereotypes of female superiority. Furthermore, evidence has been mixed about how and when these stereotypes can affect girls’ aspirations to pursue STEM fields. There is also limited understanding of whether and how young girls and boys of different races and ethnicities may differentially experience and be affected by gender stereotypes in these fields.
A new synthesis project for the National Science Foundation aims to clarify these ambiguous results. AIR experts David Miller and Courtney Tanenbaum will conduct a meta-analysis of existing studies across the world, investigating three sets of factors that could potentially explain these heterogeneous results:
- Child demographics such as age, gender, and race/ethnicity
- Contextual features such as country, region, and historical period
- Measurement differences, such as studying implicit vs. explicit bias
Ultimately, this research is designed to inform educational and developmental practices to strengthen student outcomes. For instance, this information could help practitioners target the earliest ages when children begin to subscribe to gender stereotypes about STEM, or maximize contexts in which the stereotypes are weakened. This project builds on AIR’s extensive expertise in systematic review and meta-analysis, such as the What Works Clearinghouse, Latin American Countries READS, and many others.
Read more about our work about increasing women's participation in STEM and in broadening STEM participation by women, racial and ethnic minorities, and persons with disabilities.