The Urban Review

, Volume 47, Issue 1, pp 1–25 | Cite as

Narrowing Pathways? Exploring the Spatial Dynamics of Postsecondary STEM Preparation in Philadelphia, Pennsylvania

  • Kimberly A. Edmunds
  • Hamil Pearsall
  • Laura K. Porterfield
Article
First Online:

Abstract

This paper explores geographical factors associated with the postsecondary science, technology, engineering, and mathematics (STEM) preparation of students from underrepresented groups in the School District of Philadelphia from middle to high school during 2008 and 2011. We analyze Pennsylvania state assessment data for mathematics in conjunction with data from the American Community Survey using correlation analysis, cluster analysis, ordinary least squares regression, and geographically-weighted regression. Our analyses find strong relationships among math performance, a key indicator of college readiness for courses of study in STEM, and neighborhood factors within school catchment areas. For example, high percentages of unemployed residents are negatively correlated to math performance, while high median household income is positively correlated with math performance. These relationships vary spatially across middle and high school catchment areas. The results of this research can foster discussions about school reform towards more nuanced, spatially-informed STEM policies that focus on improving the educational outcomes of students who are traditionally underrepresented in STEM fields, particularly for those youth living in economically disadvantaged communities.

Keywords

Neighborhood factors STEM High schools Urban schools 
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Notes

Acknowledgments

Research for this paper was supported, in part, by the National Science Foundation (NSF) through a grant (Award 1061028) to the Association of American Geographers (AAG). Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the NSF or the AAG. We would like to acknowledge May Yuan, University of Oklahoma, for her generous guidance and feedback.

References

  1. Ainsworth, J. W. (2002). Why does it take a village? The mediation of neighborhood effects on educational achievement. Social Forces, 81(1), 117–152.CrossRefGoogle Scholar
  2. Alspaugh, J. W. (1998). Achievement loss associated with the transition to middle school and high school. The Journal of Educational Research, 92(1), 20–25.CrossRefGoogle Scholar
  3. Brunsdon, C., McClatchey, J., & Unwin, D. J. (2001). Spatial variations in the average rainfall-altitude relationship in Great Britain: An approach using geographically weighted regression. International Journal of Climatology, 21, 455–466.CrossRefGoogle Scholar
  4. Carter, P. L., & Welner, K. G. (Eds.). (2013). Closing the opportunity gap: What America must do to give every child an even chance. New York, NY: Oxford University Press.Google Scholar
  5. Catsambis, S., & Beveridge, A. A. (2001). Does neighborhood matter? Family, neighborhood, and school influences on eighth-grade mathematics achievement. Sociological Focus, 34(4), 435–457.CrossRefGoogle Scholar
  6. Coleman, J. S. (1966). Equality of educational opportunity. Washington, DC: National Center for Educational Statistics (DHEW/OE). Retrieved from ERIC database.Google Scholar
  7. Conley, D. (1999). Being black, living in the red: Race, wealth, and social policy in America. Berkeley, CA: University of California Press.Google Scholar
  8. Davis, A. (1949). Social-class influences upon learning. Cambridge, MA: Harvard University Press.Google Scholar
  9. Duncan, G. J., & Murnane, R. J. (Eds.). (2011). Whither opportunity? Rising inequality, schools, and children’s life chances. New York, NY: Russell Sage Foundation.Google Scholar
  10. Eamon, M. K. (2005). Social-demographic, school, neighborhood, and parenting influences on the academic achievement of Latino young adolescents. Journal of Youth and Adolescence, 34(2), 163–174.CrossRefGoogle Scholar
  11. Edmunds, K. (2010). Looking from the outside in: A spatial analysis of students’ neighborhood characteristics and school performance in Philadelphia. In Paper presented at the ESRI International Education User Conference, San Diego, CA, July 2010.Google Scholar
  12. Fotheringham, A. S., Charlton, M., & Brunsdon, C. (2001). Spatial variations in school performance: A local analysis using geographically weighted regression. Geographical & Environmental Modelling, 5(1), 43–66.CrossRefGoogle Scholar
  13. Gardner, D. P. (1983). A nation at risk: The imperative for educational reform. An open letter to the American people. A Report to the Nation and the Secretary of Education. Washington, DC: National Commission on Excellence in Education. Retrieved from ERIC database.Google Scholar
  14. Gold, E., Evans, S., Haxton, C., Maluk, H., Mitchell, C., Simon, E., et al. (2010a). Context, conditions, and consequences: Freshman year transition in Philadelphia. Philadelphia: Research for Action.Google Scholar
  15. Gold, E., Evans, S., Haxton, C., Maluk, H., Mitchell, C., Simon, E., et al. (2010b). Transition to high school: School ‘choice’ and freshman year in Philadelphia. Philadelphia: Research for Action.Google Scholar
  16. House, J. S., & Williams, D. R. (2000). Understanding and reducing socioeconomic and racial/ethnic disparities in health. In B. D. Smedley & S. L. Syme (Eds.), Promoting health: Intervention strategies from social and behavioral research (pp. 81–125). Washington, DC: National Academy Press.Google Scholar
  17. Hrabowski, F. A. (2011). Editorial: Boosting minorities in science. Science, 331, 125.CrossRefGoogle Scholar
  18. Lewin, T. (2012). Black students face more discipline, data suggests. The New York Times. Retrieved from http://www.nytimes.com/2012/03/06/education/black-students-face-more-harsh-discipline-data-shows.html?_r=2&nl=todaysheadlines&emc=edit_th_20120306.
  19. Lubrano, A. (2012). Poverty rises in Phila., suburbs, census study finds. Philadelphia Inquirer. Retrieved from http://articles.philly.com/2012-09-21/news/33978472_1_poverty-rate-median-household-income-census-figures-show.
  20. Massey, D., & Denton, N. (1993). American apartheid: Segregation and the making of the underclass. Boston, MA: Harvard University Press.Google Scholar
  21. Maxwell, L. A. (2012). Growing gaps bring focus on poverty’s role in schooling. Education Week. Retrieved from http://www.edweek.org/ew/articles/2012/03/07/23poverty_ep.h31.html?tkn=QYYFgsUqigQkeTfLtgpOzz3nMz6Sf3TbuZTr&cmp=clp-edweek&utm_source=fb&utm_medium=rss&utm_campaign=mrss.
  22. McIntosh, K., Flannery, K. B., Sugai, G., Braun, D. H., & Cochrane, K. L. (2008). Relationships between academics and problem behavior in the transition from middle school to high school. Journal of Positive Behavior Interventions, 10(4), 243–255.CrossRefGoogle Scholar
  23. Mickelson, R. A., Bottia, M. C., & Lambert, R. (2013). Effects of school racial composition on K-12 mathematics outcomes: A metaregression analysis. Review of Educational Research, 83(1), 121–158.CrossRefGoogle Scholar
  24. National Academy of Sciences (2011). Expanding underrepresented minority participation: America’s science and technology talent at the crossroads. Washington, DC: National Academies Press. Summary retrieved from http://www.nap.edu/catalog.php?record_id=12984.
  25. Ogneva-Himmelberger, Y., Pearsall, H., & Rakshit, R. (2009). Concrete evidence & geographically weighted regression: A regional analysis of wealth and the land cover in Massachusetts. Applied Geography, 29(4), 478–487.CrossRefGoogle Scholar
  26. Owens, A. (2010). Neighborhoods and schools as competing and reinforcing contexts for educational attainment. Sociology of Education, 83(4), 287–311.CrossRefGoogle Scholar
  27. Pearsall, H., & Christman, Z. (2012). Tree-lined lanes or vacant lots? Evaluating non-stationarity between urban greenness and socio-economic conditions in Philadelphia, Pennsylvania, USA at multiple scales. Applied Geography, 35(1), 257–264.CrossRefGoogle Scholar
  28. Perna, L. W. (Ed.). (2013). Preparing today’s students for tomorrow’s jobs in metropolitan America. Philadelphia: University of Pennsylvania Press.Google Scholar
  29. President’s Council of Advisors on Science and Technology. (2012). Summary. Engage to excel: Producing one million additional college graduates with degrees in science, technology, engineering, and mathematics. Retrieved from http://www.whitehouse.gov/sites/default/files/microsites/ostp/pcast-executive-report-final_2-13-12.pdf.
  30. Reardon, S. F. (2011). The widening academic achievement gap between the rich and the poor: New evidence and possible explanations. In G. J. Duncan & R. Murnane (Eds.), Whither opportunity? Rising inequality, schools and children’s life chances (pp. 91–116). New York, NY: Russell Sage Foundation.Google Scholar
  31. Rothwell, J. (2012). Housing costs, zoning, and access to high-scoring schools. Washington, DC: Brookings Institution.Google Scholar
  32. Sampson, R. (2012). Great American city: Chicago and the enduring neighborhood effect. Chicago: The University of Chicago Press.CrossRefGoogle Scholar
  33. Schiller, K. (1999). Effects of feeder patterns on students’ transition to high school. Sociology of Education, 72(4), 216–233.CrossRefGoogle Scholar
  34. Schmidt, W., Cogan, L., Houang, R., & McKnight, C. (2011). Content coverage differences across districts/states: A persisting challenge for U.S. American Journal of Education, 117(3), 399–427.CrossRefGoogle Scholar
  35. Schott Foundation for Public Education. (2012). A rotting apple: Education redlining in New York City. Executive summary. Cambridge, MA: Schott Foundation for Public Education.Google Scholar
  36. Socolar, P. (2012). District on-time graduation rate surpasses 60 percent. The Public School Notebook, 19(4). Retrieved from http://www.thenotebook.org/february-2012/124482/district-time-graduation-rate-surpasses-60-percent. Figure is the percentage of students who entered 9th grade in fall 2007 and finished high school by 2011.
  37. Tate, W. F. (2008). Geography of opportunity: Poverty, place, and educational outcomes. Educational Researcher, 37, 397–411.CrossRefGoogle Scholar
  38. Tavernise, S. (2012). Education gap grows between rich and poor, studies say. The New York Times. Retrieved from http://www.nytimes.com/2012/02/10/education/education-gap-grows-between-rich-and-poor-studies-show.html?_r=1&pagewanted=all.
  39. The Pew Charitable Trusts. (2011). Philadelphia 2011: The state of the city. Philadelphia: The pew charitable trusts. Retrieved from http://www.pewtrusts.org/uploadedFiles/wwwpewtrustsorg/Reports/Philadelphia_Research_Initiative/Philadelphia-City-Data-Population-Demographics.pdf.
  40. Von Bergen, J. (2012). Where are jobs for young people? Philadelphia Inquirer. Retrieved from http://www.philly.com/philly/news/special_packages/inquirer/phlJobsP2.html?viewAll=y.
  41. Wilson, W. J. (2009). More than just race: Being Black and poor in the inner city. New York, NY: W. W. Norton & Co.Google Scholar
  42. Womack, C. (2012). PowerPoint presented during the Philadelphia STEM Stakeholder Summit, June 20, 2012, School District of Philadelphia.Google Scholar
  43. Woolley, M. E., Grogan-Kaylor, A., Gilster, M. E., Karb, R. A., Gant, L. M., Reischl, T. M., et al. (2008). Neighborhood social capital, poor physical conditions, and school achievement. Children & Schools, 30(3), 133–145.CrossRefGoogle Scholar
  44. Yancey, W. L., & Saporito, S. J. (1995). Racial and economic segregation and educational outcomes: One tale, two cities. In Paper originally presented at the Conference of the National Center on Education in the Inner Cities, Philadelphia, PA, October 1994. Retrieved from ERIC database.Google Scholar

Copyright information

© Springer Science+Business Media New York 2014

Authors and Affiliations

  • Kimberly A. Edmunds
    • 1
  • Hamil Pearsall
    • 2
  • Laura K. Porterfield
    • 3
  1. 1.Research for ActionPhiladelphiaUSA
  2. 2.Department of Geography and Urban StudiesTemple UniversityPhiladelphiaUSA
  3. 3.Department of Educational FoundationsUniversity of Wisconsin-WhitewaterWhitewaterUSA

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