Doctoral Dissertation Research in Economics: The Effects of Gender and Racial Stereotypes on Math Confidence, Effort, and Achievement

There are large, persistent gender and race gaps in STEM participation and achievement, as well as persistent academic stereotypes about race and gender. This project seeks to understand the effects of providing information to elementary and middle school students to counteract the negative stereotypes and social norms surrounding the participation and achievement of under-represented groups in STEM – particularly the effects of this information on students’ confidence, STEM engagement, and achievement. While research show that stereotypes about ability matter for adults’ confidence and participation in STEM, these stereotypes emerge at much younger ages. This study will evaluate the impacts of intervening against these negative stereotypes early in students’ educational trajectory, which may be more effective and more long-lasting than intervening with adults. In addition to increasing diversity in STEM and encouraging more equal opportunities for all students, closing the gender and race gaps in STEM engagement is expected to improve productivity and innovation in the sector and reduce wage gaps, since more than 90 percent of STEM occupations offer wages above the national average. Closing gaps in STEM participation is thus a top priority for the US government as well as business leaders and professional organizations in STEM fields. The results of this research could guide policies to close the racial and gender STEM gaps and thus increase the supply of STEM workforce. This will increase economic growth, decrease poverty as well as decrease income inequality in the US.

This study will provide the first experimental evidence on the role of stereotypes in creating gaps in STEM achievement. It will also provide novel evidence on the mechanisms through which stereotypes cause these effects; specifically, the effects of stereotypes on confidence, engagement with and responsiveness to feedback, and effort. This research uses a randomized intervention – a series of videos and exercises that provide information to counteract prevailing negative academic stereotypes – delivered to students on a leading online learning platform to study these issues. Student behavior on the platform will provide high-frequency measures of student effort, learning strategies, and engagement with feedback. Additional outcomes will be measured in a survey, also integrated into the platform, which will provide psychometric and revealed-preference measures of math interest, confidence, and endorsement of stereotypes. Finally, student achievement will be measured using standardized test scores. Differences in outcomes between treated and control students will deliver the effect of the intervention, and the large set of considered outcomes will be used to test various mechanisms that explain the effect of race and gender stereotypes on math achievement. The results of this research could guide policies to close the racial and gender STEM gaps and thus increase the supply of STEM workforce. This will increase economic growth, decrease poverty as well as decrease income inequality in the US.