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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.
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Illuminating inequality in access: Variation in enrollment in undergraduate engineering programs across Virginia's high schools
Abstract BackgroundDetermining the root causes of persistent underrepresentation of different subpopulations in engineering remains a continued challenge. Because place‐based variation of resource distribution is not random and because school and community contexts influence high school outcomes, considering variation across those contexts should be paramount in broadening participation research. Purpose/HypothesisThis study takes a macroscopic systems view of engineering enrollments to understand variation across one state's public high school rates of engineering matriculation. Design/MethodThis study uses a dataset from the Virginia Longitudinal Data System that includes all students who completed high school from a Virginia public school from 2007 to 2014 (N= 685,429). We explore geographic variation in four‐year undergraduate engineering enrollment as a function of gender, race/ethnicity, and economically disadvantaged status. Additionally, we investigate the relationship between characteristics of the high school and community contexts and undergraduate engineering enrollment across Virginia's high schools using regression analysis. ResultsOur findings illuminate inequality in enrollment in engineering programs at four‐year institutions across high schools by gender, race, and socioeconomic status (and the intersections among those demographics). Different high schools have different engineering enrollment rates among students who attend four‐year postsecondary institutions. We show strong associations between high schools' engineering enrollment rates and four‐year institution enrollment rates as well as moderate associations for high schools' community socioeconomic status. ConclusionsStrong systemic forces need to be overcome to broaden participation in engineering. We demonstrate the insights that state longitudinal data systems can illuminate in engineering education research.
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- Award ID(s):
- 1647928
- PAR ID:
- 10381291
- Publisher / Repository:
- Wiley Blackwell (John Wiley & Sons)
- Date Published:
- Journal Name:
- Journal of Engineering Education
- Volume:
- 109
- Issue:
- 4
- ISSN:
- 1069-4730
- Page Range / eLocation ID:
- p. 665-684
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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