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Meyerhoff Scholars Program: A Strengths‐Based, Institution‐Wide Approach to Increasing Diversity in Science, Technology, Engineering, and Mathematics
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The Meyerhoff Scholars Program at the University of Maryland, Baltimore County is widely viewed as a national model of a program that enhances the number of underrepresented minority students who pursue science, technology, engineering, and mathematics PhDs. The current article provides an overview of the program and the institution‐wide change process that led to its development, as well as a summary of key outcome and process evaluation research findings. African American Meyerhoff students are 5× more likely than comparison students to pursue a science, technology, engineering, and mathematics PhD. Program components viewed by the students as most beneficial include financial scholarship, being a part of the Meyerhoff Program community, the Summer Bridge program, study groups, and summer research. Qualitative findings from interviews and focus groups demonstrate the importance of the Meyerhoff Program in creating a sense of belonging and a shared identity, encouraging professional development, and emphasizing the importance of academic skills. Among Meyerhoff students, several precollege and college factors have emerged as predictors of successful entrance into a PhD program in the science, technology, engineering, and mathematics fields, including precollege research excitement, precollege intrinsic math/science motivation, number of summer research experiences during college, and college grade point average. Limitations of the research to date are noted, and directions for future research are proposed. Mt Sinai J Med 79:610–623, 2012 © 2012 Mount Sinai School of Medicine
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“and has been recommended a critical element needed to address the national crisis of lack of black men in medicine.9,26,27”
From Impact of the Bronx Community Health Leaders Program for Socioeconomically Disadvantaged Prehealth Students (2021) · cites this paper as [26]
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“This longitudinal mentorship component is known to be important for the persistence and success of URM students in the prehealth path”
From Impact of the Bronx Community Health Leaders Program for Socioeconomically Disadvantaged Prehealth Students (2021) · cites this paper as [26]
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“Specifically, African-American MSP students are five times more likely to pursue a STEM PhD compared with the declined sample (Maton et al., 2009, 2012).”
From Outcomes and Processes in the Meyerhoff Scholars Program: STEM PhD Completion, Sense of Community, Perceived Program Benefit, Science Identity, and Research Self-Efficacy (2016) · cites this paper as Maton et al., 2012
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“The Meyerhoff program is a comprehensive STEM program that far surpasses an intervention with a STEM bridge program as its primary element (providing intensive, ongoing support for participants throughout all 4 years of university).”
From A Meta-analysis of University STEM Summer Bridge Program Effectiveness (2021) · cites this paper as Maton et al., 2012
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“Notably, the Meyerhoff program (see Maton et al., 2012) is extremely successful, and including it in our meta-analysis would only strengthen the findings regarding STEM bridge program effectiveness.”
From A Meta-analysis of University STEM Summer Bridge Program Effectiveness (2021) · cites this paper as Maton et al., 2012
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“Our results align with previous research on the effectiveness of programs such as the Meyerhoff Scholars Program which focused on an integrated cohort approach for STEM to enhance student success (Maton et al., 2012(Maton et al., , 2016)).”
From The Importance of STEM Sense of Belonging and Academic Hope in Enhancing Persistence for Low-Income, Underrepresented STEM Students (2024) · cites this paper as Maton et al., 2012
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Bailey, T. C. (2015) · Deep Blue (University of Michigan) · Cited by 3
Desafíos en la enseñanza de ingeniería en el siglo XXI
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A Retrospective on Undergraduate Engineering Success for Underrepresented and First-Year Students
Roberts, S., Najafi, F., & Taylor, C. R. (2020) · ASEE Annual Conference & Exposition · doi:10.18260/1-2--31987 · Cited by 2
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Metadata
- Authors
- Maton, K. I., Pollard, S. A., McDougall Weise, T. V., & Hrabowski, F. A.
- Affiliations
- University of Maryland, Baltimore (US)
- Venue
- Mount Sinai Journal of Medicine: A Journal of Translational and Personalized Medicine
- Publisher
- Wiley
- Published
- 2012-09
- Volume
- 79
- Issue
- 5
- Pages
- 610-623
- ISSN
- 0027-2507 (ISSN-L)
- 1931-7581
- PMC
- PMC3444508
- OpenAlex
- W2044343289
- Cited by
- 143
- References
- 23
- Citations by year
- 2026: 12 · 2025: 5 · 2024: 15 · 2023: 16 · 2022: 14 · 2021: 14 · 2020: 9 · 2019: 7 · 2018: 6 · 2017: 14 · 2016: 12 · 2015: 8 · 2014: 9 · 2013: 1 · 2012: 1
- FWCI
- 15.71
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Mount Sinai Journal of Medicine A Journal of Translational and Personalized Medicine (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- Funders
- National Institute of General Medical Sciences (R01GM075278, R25GM055036)
- Topics
- Social Sciences › Psychology › Applied Psychology › Career Development and Diversity
- Social Sciences › Education › Higher Education Research Studies
- Social Sciences › Sociology and Political Science › Critical Race Theory in Education
- Keywords
- underrepresented minority students, African American students, institutional change, strengths-based approach, sense of belonging, professional development, summer research experience
- MeSH terms
- Workforce, Black or African American, Education, Graduate, Education, Medical, Engineering, Fellowships and Scholarships, Female, Humans, Male, Maryland, Mathematics, Minority Groups, School Admission Criteria, Technology, Program Evaluation, Models, Educational, Cultural Diversity, Biomedical Research
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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