Gender stereotypes about science, technology, engineering, and math (STEM) are salient for children and adolescents and contribute to achievement-related disparities and inequalities in STEM participation. However, few studies have used a longitudinal design to examine changes in gender stereotypes across a range of STEM fields. In a large, preregistered study, we examined the developmental trajectories of two gender stereotypes (involving interest and ability) in four STEM fields across three time points within a calendar year, starting in Grades 2-8. The diverse sample included 803 students ages 7-15 years old at the start of the study (50% girls; 8.5% Asian, 6.0% Black, 25.5% Hispanic/Latinx, 43.7% White, and 16.3% other). Multilevel growth modeling was used to examine developmental trajectories in students' stereotypes for four STEM fields (math, science, computer science, and engineering) while considering both gender and grade level. We found that different STEM disciplines displayed different developmental patterns: Math ability and science interest stereotypes more strongly favored girls over the year among elementary school participants, whereas computer science stereotypes less strongly favored boys over time, and engineering stereotypes (which largely favored boys) were stable across time. The results highlight that the development of stereotypes is not the same for all STEM fields as well as the need to understand the complexity and specificity of developmental change across fields and types of stereotypes.
Public Significance StatementThis study tracked changes in children and early adolescents' STEM-gender stereotypes over the course of a calendar year, specifically focusing on gender stereotypes about who is interested and capable in STEM. We found greater stability in stereotypes about engineering than math, science, and computer science, and among middle school students compared to elementary school students. Based on patterns within the present study, we suggest that efforts to reduce gender stereotyping in STEM fields should begin early, before stereotypes take root.