Effects of State Policy on High School Science, Technology, Engineering, and Mathematics (STEM) Opportunities and Outcomes for Low-Income Underrepresented Minorities

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Although we have some evidence of the effects of state policy on postsecondary costs, tuition waivers, and earmarked grants for college attendance, we have little evidence of the effects of STEM-specific state policy defined as math and science course requirements for high school graduation, and presence or absence of high-stakes testing on high school opportunities and short and long term outcomes for STEM. Although students interested in STEM pursue varying paths toward STEM degrees and related outcomes, high school opportunity structures are consequential. They can enhance or constrain later choices, particularly in hierarchically based STEM fields where continuous orderly progression in math and science, from high school through college, is expected. The study will illuminate the success/failure of state policy initiatives designed to increase and broaden participation in STEM fields. Given the increased role of state policies that is expected under the Every Student Succeeds Act (ESSA; signed December 2015), interstate differences in curriculum and testing policies and their effects on outcomes for underrepresented minorities (URM) will provide critical insight into the effectiveness of varying state-level policy initiatives. The proposed study will locate specific spaces and mechanisms wherein existing inequalities for URM can be ameliorated. This project is supported by the Education and Human Resources Core Research Program, which funds fundamental research in STEM learning and learning environments, broadening participation in STEM, and STEM workforce development. The purpose of this study is to investigate the interacting effects of: (1) state policy (math and science course requirements for high school graduation, and presence or absence of high stakes testing); and (2) high school opportunity structures (empirically verified math and science course availability, content, sequences and school level requirements). The proposed study is a multilevel analysis of nationally representative longitudinal data (HSLS:09). Using a multi-level regression, the study will look for relationships among high school opportunity structures and student outcomes including student learning, intentions to major in STEM disciplines, and longer term outcomes.