Skip to main content

Advertisement

SpringerLink
Log in

Schools’ Neighborhoods and Characteristics: Implications for Standardized Academic Achievement in Passaic, NJ’s Elementary, Middle and High Schools

  • Published:
The Urban Review Aims and scope Submit manuscript

A Correction to this article was published on 14 December 2022

This article has been updated

Abstract

Schools in urban neighborhoods receive less funding, have less programming, and have poorer infrastructure. Such disparities may impede academic outcomes among youth. This study used publicly available data to examine the association between school characteristics and surrounding neighborhood environment on educational outcomes across three academic years among 132 schools in Passaic County, New Jersey. Further, we assessed how schools’ socioeconomic status could buffer the effects of a school’s neighborhood disadvantage on academic outcomes. Results supported compound deprivation theory highlighting that lower-performing schools were located in lower-resourced neighborhoods. Further, school characteristics and neighborhood resource deprivation were associated with lower math, English, and science academic performance. Additionally, we found that associations between neighborhood resources and math and science academic outcomes were strongest in schools with greater economic support. We provide implications for research and practice by identifying multi-faceted approaches to challenge educational disparities addressing school and neighborhood-level disadvantages to improve educational outcomes for youth.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1

Similar content being viewed by others

Data Availability

Data will be made available through the Open Science Framework (OSF) page

Code Availability

Analytic code will be made available through the OSF page

Change history

References

  • Acevedo-Garcia, D., McArdle, N., Hardy, E. F., Crisan, U. I., Romano, B., Norris, D., Baek, M., & Reece, J. (2014). The child opportunity index: improving collaboration between community development and public health. Health affairs, 33(11), 1948–1957.

    Article  Google Scholar 

  • Acevedo-Garcia, D., Noelke, C., McArdle, N., Sofer, N., Hardy, E. F., Weiner, M., Baek, M., Huntington, N., Huber, R., & Reece, J. (2020). Racial And Ethnic Inequities In Children’s Neighborhoods: Evidence From The New Child Opportunity Index 2.0: The study uses the Child Opportunity Index 2.0 to examine geographic and racial/ethnic inequities children are exposed to in the one hundred largest metropolitan areas of the United States. Health Affairs, 39(10), 1693–1701.

    Article  Google Scholar 

  • Aris, I. M., Rifas-Shiman, S. L., Jimenez, M. P., Li, L. J., Hivert, M. F., Oken, E., & James, P. (2021). Neighborhood Child Opportunity Index and Adolescent Cardiometabolic Risk.Pediatrics, 147(2).

  • Beck, A. F., Sandel, M. T., Ryan, P. H., & Kahn, R. S. (2017). Mapping neighborhood health geomarkers to clinical care decisions to promote equity in child health. Health Affairs, 36(6), 999–1005.

    Article  Google Scholar 

  • Beghetto, R. A. (2017). Creativity in teaching. The Cambridge handbook of creativity across domains, 549–564.

  • Berman, J. D., McCormack, M. C., Koehler, K. A., Connolly, F., Clemons-Erby, D., Davis, M. F., Gummerson, C., Leaf, P. J., Jones, T. D., & Curriero, F. C. (2018). School environmental conditions and links to academic performance and absenteeism in urban, mid-Atlantic public schools. International journal of hygiene and environmental health, 221(5), 800–808.

    Article  Google Scholar 

  • Bronfenbrenner, U. (1977). Toward an experimental ecology of human development. American psychologist, 32(7), 513.

    Article  Google Scholar 

  • Brooks-Gunn, J., Duncan, G. J., & Maritato, N. (1997). Poor families, poor outcomes: The well-being of children and youth. Consequences of growing up poor, 1997, 1–17.

  • Burdick-Will, J., Ludwig, J., Raudenbush, S. W., Sampson, R. J., Sanbonmatsu, L., & Sharkey, P. (2011). Converging evidence for neighborhood effects on children’s test scores: An experimental, quasi-experimental, and observational comparison.Whither opportunity,255–276.

  • Carlson, D., & Cowen, J. M. (2015). Student neighborhoods, schools, and test score growth: Evidence from Milwaukee, Wisconsin. Sociology of Education, 88(1), 38–55.

    Article  Google Scholar 

  • Chetty, R., Hendren, N., & Katz, L. F. (2016). The effects of exposure to better neighborhoods on children: New evidence from the moving to opportunity experiment. American Economic Review, 106(4), 855–902.

    Article  Google Scholar 

  • Christensen, W. (2018). Model selection using information criteria (made easy in SAS). University of California, Los Angeles.

  • Clayton, J. K. (2011). Changing diversity in US schools: The impact on elementary student performance and achievement. Education and Urban Society, 43(6), 671–695.

    Article  Google Scholar 

  • Duncan, G. J., & Murnane, R. J. (2011). Whither opportunity?: Rising inequality, schools, and children’s life chances. Russell Sage Foundation.

  • Duncan, G. J., & Murnane, R. J. (2016). Rising inequality in family incomes and children’s educational outcomes. RSF: The Russell Sage Foundation Journal of the Social Sciences, 2(2), 142–158.

    Article  Google Scholar 

  • Durlak, J. A., Weissberg, R. P., & Pachan, M. (2010). A meta-analysis of after-school programs that seek to promote personal and social skills in children and adolescents. American journal of community psychology, 45(3), 294–309.

    Article  Google Scholar 

  • Dyson, L. L., Hett, G., & Blair, K. (2003). The effect of neighborhood poverty on school achievement and behavior: A study of children in a low-income neighborhood school in Canada. Connections, 3, 191–199.

    Google Scholar 

  • Flaxman, G., Kuscera, J., Orfield, G., Ayscue, J., & Siegel-Hawley, G. (2013). A status quo of segregation: Racial and economic imbalance in New Jersey Schools, 1989–2010.

  • García, E., & Weiss, E. (2019). The Teacher Shortage Is Real, Large and Growing, and Worse than We Thought. The First Report in" The Perfect Storm in the Teacher Labor Market" Series. Economic Policy Institute.

  • Gilliland, F. D., Berhane, K., Rappaport, E. B., Thomas, D. C., Avol, E., Gauderman, W. J., London, S. J., Margolis, H. G., McConnell, R., & Islam, K. T. (2001). The effects of ambient air pollution on school absenteeism due to respiratory illnesses.Epidemiology,43–54.

  • Hanson, M. J., Miller, A. D., Diamond, K., Odom, S., Lieber, J., Butera, G., Horn, E., Palmer, S., & Fleming, K. (2011). Neighborhood community risk influences on preschool children’s development and school readiness. Infants & Young Children, 24(1), 87–100.

    Article  Google Scholar 

  • Hoxby, C. M. (2000). The effects of class size on student achievement: New evidence from population variation. The Quarterly Journal of Economics, 115(4), 1239–1285.

    Article  Google Scholar 

  • Jencks, C., & Mayer, S. E. (1990). The social consequences of growing up in a poor neighborhood. Inner-city poverty in the United States, 111, 186.

    Google Scholar 

  • Jeon, L., Buettner, C. K., & Hur, E. (2014). Family and neighborhood disadvantage, home environment, and children’s school readiness. Journal of Family Psychology, 28(5), 718.

    Article  Google Scholar 

  • Kalil, A. (2016). How economic inequality affects children’s outcomes.Delivering equitable growth,25.

  • Kelly, M. G. (2020). The curious case of the missing tail: Trends among the top 1% of school districts in the United States, 2000–2015. Educational Researcher, 49(5), 312–320.

    Article  Google Scholar 

  • Koc, N., & Celik, B. (2015). The impact of number of students per teacher on student achievement. Procedia-Social and Behavioral Sciences, 177, 65–70.

    Article  Google Scholar 

  • Kohen, D. E., Leventhal, T., Dahinten, V. S., & McIntosh, C. N. (2008). Neighborhood disadvantage: Pathways of effects for young children. Child development, 79(1), 156–169.

    Article  Google Scholar 

  • Kornbluh, M., Ozer, E. J., Allen, C. D., & Kirshner, B. (2015). Youth participatory action research as an approach to sociopolitical development and the new academic standards: Considerations for educators. The Urban Review, 47(5), 868–892.

    Article  Google Scholar 

  • Kweon, B. S., Ellis, C. D., Lee, J., & Jacobs, K. (2017). The link between school environments and student academic performance. Urban Forestry & Urban Greening, 23, 35–43.

    Article  Google Scholar 

  • Lardier Jr, D. T., Herr, K. G., Barrios, V. R., Garcia-Reid, P., & Reid, R. J. (2019). Merit in meritocracy: Uncovering the myth of exceptionality and self-reliance through the voices of urban youth of color. Education and Urban Society, 51(4), 474–500.

    Article  Google Scholar 

  • Leventhal, T., Fauth, R. C., & Brooks-Gunn, J. (2005). Neighborhood poverty and public policy: A 5-year follow-up of children’s educational outcomes in the New York City moving to opportunity demonstration. Developmental Psychology, 41(6), 933.

    Article  Google Scholar 

  • Mahoney, J. L., Lord, H., & Carryl, E. (2005). An ecological analysis of after-school program participation and the development of academic performance and motivational attributes for disadvantaged children. Child development, 76(4), 811–825.

    Article  Google Scholar 

  • Martorell, P., Stange, K., & McFarlin Jr, I. (2016). Investing in schools: capital spending, facility conditions, and student achievement. Journal of Public Economics, 140, 13–29.

    Article  Google Scholar 

  • Mayer, S. E. (2002). How economic segregation affects children’s educational attainment. Social forces, 81(1), 153–176.

    Article  Google Scholar 

  • Mohai, P., Kweon, B. S., Lee, S., & Ard, K. (2011). Air pollution around schools is linked to poorer student health and academic performance. Health Affairs, 30(5), 852–862.

    Article  Google Scholar 

  • Molnar, A., Smith, P., Zahorik, J., Palmer, A., Halbach, A., & Ehrle, K. (1999). Evaluating the SAGE program: A pilot program in a targeted pupil-teacher reduction in Wisconsin. Educational Evaluation and Policy Analysis, 21(2), 165–177.

    Article  Google Scholar 

  • Morrissey, T. W., & Vinopal, K. M. (2018). Neighborhood poverty and children’s academic skills and behavior in early elementary school. Journal of Marriage and Family, 80(1), 182–197.

    Article  Google Scholar 

  • Noelke, C., McArdle, N., Baek, M., Huntington, N., Huber, R., Hardy, E., & Acevedo-Garcia, D. (2019). The Child Opportunity Index 2.0.

  • Noelke, C., McArdle, N., Baek, M., Huntington, N., Huber, R., Hardy, E., & Acevedo-Garcia, D. (2020). Child Opportunity Index 2.0.

  • O'Connell, A. A., & McCoach, D. B. (2008). Multilevel modeling of educational data. IAP.

  • Olejnik, S., Li, J., Supattathum, S., & Huberty, C. J. (1997). Multiple testing and statistical power with modified Bonferroni procedures. Journal of educational and behavioral statistics, 22(4), 389–406.

    Article  Google Scholar 

  • Orfield, G., Ee, J., & Coughlin, R. (2017). New Jersey’s segregated schools:Trends and paths forward.

  • Owens, A. (2010). Neighborhoods and schools as competing and reinforcing contexts for educational attainment. Sociology of Education, 83(4), 287–311.

    Article  Google Scholar 

  • Perry, L. B., & McConney, A. (2010). Does the SES of the school matter? An examination of socioeconomic status and student achievement using PISA 2003. Teachers college record, 112(4), 1137–1162.

    Article  Google Scholar 

  • Raftery, A. E. (1995). Bayesian model selection in social research.Sociological methodology,111–163.

  • Raudenbush, S. W., & Bryk, A. S. (2002). Hierarchical linear models: Applications and data analysis methods (Vol. 1). sage.

  • Reardon, S. F. (2016). School district socioeconomic status, race, and academic achievement. Stanford Center for Educational Policy Analysis. Retrieved from.

  • Reardon, S. F., Robinson, J. P., & Weathers, E. S. (2008). Patterns and trends in racial/ethnic and socioeconomic academic achievement gaps.Handbook of research in education finance and policy,497–516.

  • Roubinov, D. S., Hagan, M. J., Boyce, W. T., Adler, N. E., & Bush, N. R. (2018). Family socioeconomic status, cortisol, and physical health in early childhood: the role of advantageous neighborhood characteristics. Psychosomatic medicine, 80(5), 492.

    Article  Google Scholar 

  • Ruiz, L. D., McMahon, S. D., & Jason, L. A. (2018). The role of neighborhood context and school climate in school-level academic achievement. American journal of community psychology, 61(3–4), 296–309.

    Article  Google Scholar 

  • Rumberger, R. W., & Palardy, G. J. (2005). Does segregation still matter? The impact of student composition on academic achievement in high school. Teachers college record, 107(9), 1999.

  • Ryan, R. M., Fauth, R. C., & Brooks-Gunn, J. (2013). Childhood poverty: Implications for school readiness and early childhood education. Handbook of research on the education of young children (pp. 315–335). Routledge.

  • Schwartz, A. E., Horn, K. M., Ellen, I. G., & Cordes, S. A. (2020). Do housing vouchers improve academic performance? Evidence from New York City. Journal of Policy Analysis and Management, 39(1), 131–158.

    Article  Google Scholar 

  • Shin, Y. (2012). Do black children benefit more from small classes? Multivariate instrumental variable estimators with ignorable missing data. Journal of educational and behavioral statistics, 37(4), 543–574.

    Article  Google Scholar 

  • Sirin, S. R. (2005). Socioeconomic status and academic achievement: A meta-analytic review of research. Review of educational research, 75(3), 417–453.

    Article  Google Scholar 

  • Smart, M., Felton, J., Meghea, C., Buchalski, Z., Maschino, L., & Sadler, R. (2021). Is a School’s Neighborhood Physical Disorder Related to Its Academic Outcomes? Child & Youth Care Forum, 50(2), 247–259. https://doi.org/10.1007/s10566-020-09572-3

  • Taines, C. (2011). “What the real world in schools is like”: Urban youth in dialogue about educational inequality. The Urban Review, 43(3), 414–435.

    Article  Google Scholar 

  • Thorpe, D., & Klein, D. N. (2022). The Effect of Neighborhood-level Resources on Children’s Physical Development: Trajectories of Body Mass Index and Pubertal Development and the Influence of Child Biological Sex. Journal of youth and adolescence, 51(5), 967–983.

    Article  Google Scholar 

  • Unlu, F. (2005). California class size reduction reform: New findings from the NAEP. Unpublished manuscript.(13.84)(13.38)(13.52)(13.76)(14.08)(14.40).

  • Webster, B. J., & Fisher, D. L. (2003). School-level environment and student outcomes in mathematics. Learning Environments Research, 6(3), 309–326.

    Article  Google Scholar 

  • Wisman, R. A. (2020). Operationalizing the intersection of racial and socioeconomic diversity in predicting school-level academic achievement. Education and Urban Society, 52(6), 927–961.

    Article  Google Scholar 

  • Wodtke, G. T., Elwert, F., & Harding, D. J. (2016). Neighborhood effect heterogeneity by family income and developmental period. American journal of sociology, 121(4), 1168–1222.

    Article  Google Scholar 

  • Wu, H., Shen, J., Spybrook, J., & Gao, X. (2021). Closing achievement gaps: Examining the roles of school background and process. Education and Urban Society, 53(8), 909–937.

    Article  Google Scholar 

  • Ijeoma, Opara Noelle, R Leonard Daneele, Thorpe Trace, Kershaw (2021) Understanding Neighborhoods’ Impact on Youth Substance Use and Mental Health Outcomes in Paterson New Jersey: Protocol for a Community-Based Participatory Research Study. JMIR Research Protocols 10(5) e29427-v10i5e29427 10.2196/29427

Download references

Funding

Dr. Opara is fully supported by the NIH Director?s Early Independence Award (DP5OD029636)

Author information

Authors and Affiliations

  1. Department of Social & Behavioral Sciences, Yale School of Public Health, Yale University, New Haven, CT, United States

    Ijeoma Opara PhD, MSW, MPH

  2. Department of Psychology, Stony Brook University, New York, NY, United States

    Daneele Thorpe MA

  3. Department of Psychiatry and Behavioral Sciences, University of New Mexico School of Medicine, The University of New Mexico, Albuquerque, NM, United States

    David T. Lardier PhD

  4. Program of Public Health, Stony Brook University, New York, NY, United States

    Deanna Parisi

Authors
  1. Ijeoma Opara PhD, MSW, MPH
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Daneele Thorpe MA
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. David T. Lardier PhD
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Deanna Parisi
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Ijeoma Opara PhD, MSW, MPH.

Ethics declarations

Materials Availability

Additional materials will be made available through the OSF page

Conflicts of Interests

The authors report no conflict of interests

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

The original online version of this article was revised: the funding information is included in the article.

Electronic Supplementary Material

Below is the link to the electronic supplementary material.

Supplementary Material 1

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Opara, I., Thorpe, D., Lardier, D.T. et al. Schools’ Neighborhoods and Characteristics: Implications for Standardized Academic Achievement in Passaic, NJ’s Elementary, Middle and High Schools. Urban Rev 55, 393–414 (2023). https://doi.org/10.1007/s11256-022-00652-3

Download citation

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11256-022-00652-3

Keywords

Search

Navigation