Previous Award Number: R305A180167
Previous Awardee: University of Washington

Co-Principal Investigator: Meltzoff, Andrew

Purpose: The gender gap in STEM (science, technology, engineering, and math) remains a large and persistent problem in the United States. Although many factors influence this gap, research points to gender difference in students' interest and motivation in STEM as a major contributor to later disparities in STEM majors and careers. This difference in interest and motivation is driven, in part, by stereotypes. Stereotypes refer to beliefs that link groups with certain traits or characteristics. Two negative stereotypes characterize STEM as more "for boys" than girls: interest STEM-gender stereotypes (e.g., "Boys are more interested in STEM than girls") and ability STEM-gender stereotypes ("Boys are better at STEM than girls"). This grant supported innovative work to examine the widespread existence and impact of interest stereotypes, especially in computer science and engineering, two fields in which women are particularly underrepresented. The research team explored how and when gender stereotypes about academic fields emerge, the relationship between stereotypes and motivation in STEM fields, and whether teaching a growth mindset (i.e., the belief that intelligence is malleable) can change stereotypes and improve students' sense of belonging, self-efficacy, interest, and outcomes in STEM. Findings from this research have already begun to inform teaching practices and the development of interventions to reduce the impact of gender stereotypes about STEM.

Project Activities: The research team conducted a survey of students in grades 1 through 12 (study 1) and a 3-year longitudinal (study 2) study with students beginning in grades 2 through 8 to examine the developmental trajectory of how gender stereotypes about interest and ability in STEM, sense of belonging, self-perceptions of ability, interest, and academic outcomes were linked. The research team also conducted a study with middle school students (study 3) to explore whether teaching a growth mindset could reduce the effects of stereotypes and increase interest in computer science.

Pre-registration Site: This grant supported multiple pre-registered analyses: Study 1 (a) https://osf.io/8fhv7/, (b) https://osf.io/ds458, (c) https://osf.io/zpa49, (d) https://osf.io/8cmxz Study 1 replication: https://osf.io/djv9f Study 2: https://osf.io/6xb7v Study 3: https://osf.io/y4xfu

Key Outcomes: The main findings of this project are as follows: From Master, A., Meltzoff, A.N., & Cheryan, S., 2021:

• Students as young as age six (first grade) and adolescents across multiple racial/ethnic and gender intersections (Black, Hispanic/Latinx, Asian, and White girls and boys) endorse stereotypes that girls are less interested than boys in computer science and engineering.
• The more that individual girls endorse gender-interest stereotypes favoring boys in computer science and engineering, the lower their own interest and sense of belonging in these fields.
• These gender-interest stereotypes are endorsed even more strongly than gender stereotypes about computer science and engineering abilities.

From Master, A. et al. (2023):

• Young students (grades 1–3) generally endorsed stereotypes about interest and ability for computer coding that favored their own-gender group, although third-grade girls reported gender-egalitarian beliefs about interest in coding.
• For young students (grades 1–3), there were no gender differences in their motivation for computer coding in terms of their own interest, sense of belonging, or ability self-concepts.
• Young students’ (grades 1–3) stereotypes about their own-gender group were significantly positively linked to their own motivation for computer coding.

Structured Abstract

Setting: This study included elementary, middle, and high schools in a suburban area of Rhode Island and a middle school in Texas.

Sample: In year 1, the study had 1,954 students from grades 1 through 12 participate. A subset of those students —803 students in grades 2 through 8 from study 1 —participated in longitudinal study 2. Data collection for study 2 took place during years 1 through 3, so participating students were in grades 4 through 10 by the end of the study. In year 4, approximately 219 6th-grade students and 156 8th-grade students participated in study 3.

Factors: The malleable factor that the research team examined was whether having a growth mindset (i.e., the belief that intelligence is malleable) counteracts students' interest and ability STEM-gender stereotypes. The research team also explored the relation between STEM-gender stereotypes and self-perceptions of ability and sense of belonging.

Research Design and Methods: The research team conducted three studies. In year 1, the research team conducted a cross-sectional correlational study of elementary, middle, and high school students' endorsement and awareness of interest and ability STEM gendered stereotypes, sense of belonging, self-perceptions of ability, and academic outcomes across four STEM fields (study 1). During years 1 through 3, the research team conducted a longitudinal study with students beginning in grades 2 through 8 that measured students' endorsement and awareness of stereotypes, belonging, perceptions of ability, and interest during the fall and spring for 3 consecutive years (study 2), although the COVID-19 pandemic impacted data collection for this study. For studies 1 and 2, students completed online surveys. During year 4, the research team conducted a randomized experiment to examine whether adopting a growth mindset can change stereotypes and improve students' sense of belonging, perceptions of ability, interest, and outcomes in computer science (study 3). Students were randomly assigned to an ability growth mindset treatment group or a control condition. Students completed a brief activity where they watched a video about a girl coping with difficulties in her computer science class and then completed an online survey.

Control Condition: Studies 1 and 2 were survey studies that did not include control conditions. In study 3, students in the control condition engaged in a similar activity as the treatment condition, although they watched a video about a girl have difficulty with her memory rather than her ability in computer science.

Key Measures: Primary measures included students' grades in math and science courses, grade point average, enrollment in optional STEM courses, and researcher-developed surveys of students' endorsement and awareness of interest stereotypes, endorsement and awareness of ability stereotypes, sense of belonging, self-perceptions of ability, and interest in STEM. In addition, in study 3, students took a computer science test and a survey of their growth mindsets about computer science.

Data Analytic Strategy: For study 1, the research team examined correlations and regressions among the variables based on type of stereotype (interest or ability), gender, age, and STEM domain. For study 2, they used multilevel modeling to examine effects of grade and gender on stereotypes in each field in terms of average stereotypes and change over time. For study 3, the research team used Analysis of Variance (ANOVA) to test whether students who learned a growth mindset significantly outperformed the control group on measures of computer science interest and performance.

Products and Publications

ERIC Citations: Find available citations in ERIC for this award here or here.

Publicly Available Data: https://osf.io/ve6n9/

Select Publications

Inside IES Research Blog

Lin, Y. (2021, April 9) Gender Stereotypes in STEM: Emergence and Prevention. Inside IES Research.

Book chapters

Meltzoff, A. N., & Cvencek, D. (2019). How stereotypes shape children’s STEM identity and learning. In P. K. Kuhl, S.-S. Lim, S. Guerriero, & D. van Damme (Eds.), Developing minds in the digital age: Towards a science of learning for 21st century education (pp. 37–47). Paris, France: OECD Publishing.

Journal articles

Master, A., Tang, D., Forsythe, D. H., Alexander, T., Cheryan, S., & Meltzoff, A. N. (2023). Gender equity and motivational readiness for computational thinking in early childhood. Early Childhood Research Quarterly, 64, 242–254.doi.org/10.1016/j.ecresq.2023.03.004

Master, A. (2021).Gender stereotypes influence children’s STEM motivation. Child Development Perspectives, 15, 203–210. doi.org/10.1111/cdep.12424

Zucker, T. A., Montroy, J., Master, A., Assel, M., McCallum, C., & Yeomans-Maldonado, G. (2021). Expectancy-value theory & preschool parental involvement in informal STEM learning. Journal of Applied Developmental Psychology, 76. doi.org/10.1016/j.appdev.2021.101320.

Master, A., & Meltzoff, A. N. (2020). Cultural Stereotypes and Sense of Belonging Contribute to Gender Gaps in STEM. International Journal of Gender, Science and Technology, 12(1), 152–198.

Proceedings

Master, A., Meltzoff, A. N., & Cheryan, S. (2021). Gender stereotypes about interests start early and cause gender disparities in computer science and engineering. Proceedings of the National Academy of Sciences, 118. doi.org/10.1073/pnas.2100030118.