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Investigations into fostering gender parity in STEM have proliferated, yet the specific situation of Asian American women has been largely overlooked. Harnessing data from the High School Longitudinal Study of 2009 (HSLS:09), the analysis scrutinizes gender disparities in STEM major selections within distinct Asian American ethnic cohorts, accentuating the pivotal role of math self-efficacy. Pronounced gender disparities were discerned among Vietnamese/Thai and Filipino constituencies, as contrasting with their Chinese, Indian/Sri Lankan, and Japanese/Korean counterparts. For Vietnamese/Thai females, the disparity is partly attributable to diminished math self-efficacy, a dynamic not seen in Filipino disparities. These findings necessitate targeted interventions that foster female interest in STEM, while underscoring the imperative of ethnic specificity. It is paramount that strategies bolster the math confidence of Vietnamese/Thai females, thereby mitigating the deleterious effects of stereotypical expectations and ensuring equitable participation and outcomes. 

Using the High School Longitudinal Study of 2009, the association between high school exit exams and mathematics course-taking patterns is explored. Exit exams are linked to a decreased likelihood of students taking upward-bound mathematics during their four years of high school. Exit exams are also associated with fewer mathematics credits earned. However, exit exams are linked to increased likelihood of students completing Precalculus or higher, but have no discernible association with completing Algebra II or higher. Importantly, significant disparities exist in these associations, with underprivileged, underperforming students often experiencing limited access to advanced math courses due to exit exams.  

The authors examine students’ linear progression histories in mathematics throughout high school years, using the High School Longitudinal Study of 2009. Although scholars have attended to this before, the authors provide a new organizing framework for thousands of heterogenous mathematics course-taking sequences. Using cluster analysis, the authors identify eight distinctive course-taking sequence typologies. Approximately 45 percent of students take a linear sequence of mathematics, whereas others stop taking mathematics altogether, repeat coursework, or regress to lower level courses. Only about 14 percent of students take the expected four-year linear sequence of Algebra 1–Geometry–Algebra II–Advanced Mathematics. Membership into different typologies is related to student characteristics and school settings (e.g., race, socioeconomic status, and high school graduation requirements). The results provide a tool for schools’ self-assessment of mathematics course-taking histories among students, creating intervention opportunities and a foundation for future research on advancing our understanding of stratification in math course-taking patterns, postsecondary access, and science, technology, engineering, and mathematics majors.