Abstract
The achievement gap for racially and ethnically diverse students and students with disabilities remains among the most “wicked” problems in education. Data from the most recent National Assessment of Educational Performance (NAEP. NAEP Data Explorer. https://www.nationsreportcard.gov/ndecore/xplore/NDE, 2022) present a stark realization that there has been little change in the achievement gap between White and Black and Hispanic students since the 1990s. Data from the Early Childhood Longitudinal Study—Birth Cohort (ECLS-B), the Early Childhood Longitudinal Study—Kindergarten Cohort 1998 (ECLS-K), the Study of Early Child Care and Youth Development (SECCYD), and National Longitudinal Study of Youth 79—Child and Young Adult Cohort (CNLSY)—reported similar findings, particularly for White and Black students. In this chapter, we advance empirical evidence of disproportionate academic achievement through an in-depth analysis of the 2017–2018 civil rights collection data (CRDC). Analysis of the CRDC data updates current understandings about disproportionality of advanced placement (AP) course enrollment by race/ethnicity, disability status, and gender and, as an indicator of achievement, provides insights about disproportionality in academic achievement. Overall, the risk ratios for all subgroup comparisons were statistically significant, suggesting that the proportion of students enrolled in AP courses by subgroup is not equal. Specifically, Black and Hispanic students remain significantly less likely to be enrolled in these courses, while enrollment is almost non-existent for students with disabilities receiving special education services.
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References
Ambady, N., Shih, M., Kim, A., & Pittinsky, T. L. (2001). Stereotype susceptibility in children: Effects of identity activation on quantitative performance. Psychological Science, 12(5), 385–390. https://doi.org/10.1111/1467-9280.00371
Barnard-Brak, L., McGaha-Garnett, V., & Burley, H. (2011). Advanced placement course enrollment and school-level characteristics. NASSP Bulletin, 93(3), 165–174. https://doi.org/10.1177/0192636511418640
Budiman, A., & Ruiz, N. G. (2021). Key facts about Asian Americans, diverse and growing population. Pew Research Center. https://www.pewresearch.org/fact-tank/2021/04/29/key-facts-about-asian-americans/
Burchinal, M., McCartney, K., Steinberg, L., Crosnoe, R., Friedman, S. L., McLoyd, V., & Pianta, R. (2011). Examining the Black–White achievement gap among low-income children using the NICHD study of early child care and youth development. Child Development, 82(5), 1404–1420. https://doi.org/10.1111/j.1467-8624.2011.01620.x
Chajewski, M., Mattern, K. D., & Shaw, E. J. (2011). Examining the role of Advanced Placement Exam participation in 4-year college enrollment. Educational Measurement: Issues and Practice, 30(4), 16–27. https://doi.org/10.1111/j.1745-3992.2011.00219.x
Cimpian, J. R., Lubienski, S. T., Timmer, J. D., Makowski, M. B., & Miller, E. K. (2016). Have gender gaps in math closed? Achievement, teacher perceptions, and learning behaviors across two ECLS-K cohorts. AERA Open, 2(4). https://doi.org/10.1177/2332858416673617
Chatterji, M. (2006). Reading achievement gaps, correlates, and moderators of early reading achievement: Evidence from the Early Childhood Longitudinal Study (ECLS) kindergarten to first grade sample. Journal of Educational Psychology, 98, 489–507.
Coleman, J. S., E. Campbell, C. Hobson, J. McPartland, A. Mood, F. Weinfeld, and R. York. (1966). The Coleman Report. Equalityof Educational Opportunity
Conger, D., Long, M. C., & Iatarola, P. (2009). Explaining race, poverty, and gender disparities in advanced course-taking. Journal of Policy Analysis and Management, 28(4), 555–576. https://doi.org/10.1002/pam.20455
Eccles, J., Wigfield, A., Harold, R. D., & Blumenfeld, P. (1993). Age and gender differences in children’s self‐and task perceptions during elementary school. Child Development, 64(3), 830–847.
Fryer, R. G., & Levitt, S. D. (2004). Understanding the Black-White test score gap in the first two years of school. Review of Economics and Statistics, 86(2), 447–464. https://doi.org/10.1162/003465304323031049
Fryer, R. G., & Levitt, S. D. (2005). The Black-White test score gap through third grade. National Bureau of Economic Research. http://www.nber.org/papers/w11049
Fryer, R. G., & Levitt, S. D. (2010). An empirical analysis of the gender gap in mathematics. American Economic Journal: Applied Economics, 2, 210–240.
Gage, N. A., Whitford, D. K., Katsiyannis, A., Adams, S., & Jasper, A. (2019). National analysis of the disciplinary exclusion of black students with and without disabilities. Journal of Child and Family Studies, 28(7), 1754–1764. https://doi.org/10.1007/s10826-019-01407-7
Graefe, A. K., & Ritchotte, J. A. (2019). An exploration of factors that predict advanced placement exam success for gifted Hispanic students. Journal of Advanced Academics, 30(4), 441–462. https://doi.org/10.1177/1932202X19853194
Hartlep, N. D. (2021). The model minority stereotype: Demystifying Asian American success (2nd ed.). Information Age Publishing.
Hsin, A., & Xie, Y. (2014). Explaining Asian Americans’ academic advantage over whites. Proceedings of the National Academy of Sciences, 111(23), 8416–8421. https://www.pnas.org/doi/pdf/10.1073/pnas.1406402111
Husain, M., & Millimet, D. L. (2009). The mythical “boy crisis”? Economics of Education Review, 28, 38–48.
Lee, J., Moon, S., & Hegar, R. L. (2011). Mathematics skills in early childhood: Exploring gender and ethnic patterns. Child Indicators Research, 4, 353–368.
Lipscomb, S., Haimson, J., Liu, A. Y., Burghardt, J., Johnson, D. R., & Thurlow, M. L. (2017). Preparing for life after high school: The characteristics and experiences of youth in special education. Findings from the National Longitudinal Transition Study 2012. Volume 1: Comparisons with other youth: Full report (NCEE 2017-4016). U.S. Department of Education, Institute of Education Sciences, National Center for Education Evaluation and Regional Assistance.
Murnane, R. J., Willett, J. B., Bub, K. L., & McCartney, K. (2006). Understanding trends in the Black–White achievement gaps during the first years of school. (Brookings-Warton Papers on Urban Affairs). Brookings Institution Press.
National Assessment of Educational Performance (NAEP). (2022). NAEP Data Explorer. https://www.nationsreportcard.gov/ndecore/xplore/NDE
Office of Civil Rights [OCR]. (2021). 2017-18 Civil Rights Data Collection: List of CRDC Data Elements for School Year 2017–18. Washington, D.C.: Author. https://www2.ed.gov/about/offices/list/ocr/docs/2017-18-crdc-data-elements.pdf
Reardon, S. F., & Galindo, C. (2009). The Hispanic-White achievement gap in math and reading in the elementary grades. American Educational Research Journal, 46(3), 853–891. https://doi.org/10.3102/0002831209333184
Paschall, K. W., Gershoff, E. T., & Kuhfeld, M. A. (2018). A two-decade examination of historical race/ethnicity disparities in academic achievement by poverty status. Journal of Youth Adolescence, 47, 1164–1177. https://doi.org/10.1007/s10964-017-0800-7
Penner, A. M., & Paret, M. (2008). Gender differences in mathematics achievement: Exploring the early grades and the extremes. Social Science Research, 37, 239–253.
Reardon, S. F., Fahle, E. M., Kalogrides, D., Podolsky, A., & Zárate, R. C. (2019). Gender achievement gaps in US school districts. American Educational Research Journal, 56(6), 2474–2508. https://doi.org/10.3102/0002831219843824
Reardon, S. F., & Portilla, X. A. (2016). Recent trends in income, racial, and ethnic school readiness gaps at kindergarten entry. AERA Open, 2(3), 1–18. https://doi.org/10.1177/2332858416657343
Reardon, S. F., & Robinson, J. P. (2008). Patterns and trends in racial/ethnic and socioeconomic academic achievement gaps. In H. F. Ladd & E. B. Fiske (Eds.), Handbook of research in education finance and policy (pp. 499–518). Routledge.
Rittel, H. W., & Webber, M. M. (1973). Dilemmas in a general Theory of planning. Policy Sciences, 4(2), 155–169. https://www.cc.gatech.edu/fac/ellendo/rittel/rittel-dilemma.pdf
R Core Team (2021). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. https://www.R-project.org/.
Robinson, J. P., & Lubienski, S. T. (2011). The development of gender achievement gaps in mathematics and reading during elementary and middle school: Examining direct cognitive assessments and teacher ratings. American Educational Research Journal, 48, 268–302.
Schulte, A. C., & Stevens, J. J. (2015). Once, sometimes, or always in special education: Mathematics growth and achievement gaps. Exceptional Children, 81(3), 370–387. https://doi.org/10.1177/0014402914563695
Shores, K., Kim, H. E., & Still, M. (2020). Categorical inequality in Black and White: Linking disproportionality across multiple educational outcomes. American Educational Research Journal, 57(5), 2089–2131. https://doi.org/10.3102/0002831219900128
Sohn, K. (2012). A new insight into the gender gap in math. Bulletin of Economic Research, 64, 135–155.
Tomasetto, C., Alparone, F. R., & Cadinu, M. (2011). Girls’ math performance under stereotype threat: the moderating role of mothers’ gender stereotypes. Developmental Psychology, 47(4), 943.
U.S. Department of Education, National Center for Educational Statistics. (2022a). Digest of Education Statistics, Table 221.75. Average National Assessment of Educational Progress (NAEP) reading scale score and standard deviation, by selected student characteristics, percentile, and grade: Selected years, 1992 through 2019. https://nces.ed.gov/programs/digest/d19/tables/dt19_221.75.asp
U.S. Department of Education, National Center for Educational Statistics. (2022b). Digest of Education Statistics, Table 222.77. Average National Assessment of Educational Progress (NAEP) mathematics scale score and standard deviation, by selected student characteristics, percentile, and grade: Selected years, 1992 through 2019. https://nces.ed.gov/programs/digest/d19/tables/dt19_222.77.asp
U.S. Department of Education, National Center for Educational Statistics. (2022c). Fast facts: Students with disabilities. Author. https://nces.ed.gov/fastfacts/display.asp?id=64
U.S. National Commission on Excellence in Education. (1983). A nation at risk: The imperative for educational reform: A report to the Nation and the Secretary of Education, United States Department of Education. National Commission on Excellence in Education: [Superintendent of Documents, U.S. Government Printing Office distributor].
Viechtbauer, W. (2010). Conducting meta-analyses in R with the metafor package. Journal of Statistical Software, 36(3), 1–48. https://doi.org/10.18637/jss.v036.i03
Whiting, G. W., & Ford, D. Y. (2009). Multicultural issues: Black students and Advanced Placement classes: Summary, concerns, and recommendations. Gifted Child Today, 32(1), 23–26. https://doi.org/10.4219/gct-2009-840
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Gage, N., van Dijk, W. (2022). Academic Achievement. In: Gage, N., Rapa, L.J., Whitford, D.K., Katsiyannis, A. (eds) Disproportionality and Social Justice in Education. Springer Series on Child and Family Studies. Springer, Cham. https://doi.org/10.1007/978-3-031-13775-4_10
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