This S-STEM Research Hub is coordinated by the Quality Education for Minorities (QEM) Network in partnership with the American Institutes for Research (AIR) and seeks to better understand strategies for engaging and graduating low-income STEM students. The QEM-AIR Research Hub (The Hub) will provide an infrastructure for a strategic HBCU alliance to collaborate and expand their knowledge base on effective strategies to support domestic, low-income, talented STEM students. This knowledge is of utmost strategic importance for the Nation because the current composition of the science, technology, engineering, and mathematics (STEM) workforce does not reflect the current racial diversity of the U.S., and the intersection of race and socioeconomic status belies current efforts to broaden participation by exclusively focusing on race. According to the National Science Foundation National Center for Science and Engineering Statistics, in 2017, Blacks or African Americans represented approximately 12% of the U.S. adult population between the ages of 18-64 years; however, in 2016, their share of bachelor’s degrees awarded in science and engineering (S&E) were 9% and 4%, respectively. Historically Black Colleges and Universities (HBCUs) play a prominent role in the STEM education of African Americans, a role that is disproportionate to their representation among the Nation’s institutions of higher education. Although HBCUs represent only 3% of the nation’s institutions of higher learning, Fiegener & Proudfoot demonstrated that by 2013 they remain among the nation’s top baccalaureate-origin institutions for a significant proportion of African American S&E doctoral recipients. HBCUs share a common mission to provide and increase educational opportunities for underserved communities and are uniquely positioned to contribute to the nation’s efforts to diversify the STEM workforce. Understanding HBCUs strategies for engaging and graduating low-income STEM students is vital to the future STEM workforce.
Disclaimer statement: This work is supported by the National Science Foundation under Grant No. 2138273. Any opinions, findings, and conclusions or recommendations expressed on posted materials are those of the authors and do not necessarily reflect the views of the National Science Foundation.
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