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Objective Course Placement and College Readiness: Evidence from Targeted Middle School Math Acceleration

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  • Shaun Dougherty
  • Joshua Goodman
  • Darryl Hill
  • Erica Litke
  • Lindsay C. Page

Abstract

Advanced math coursework can affect college and labor market outcomes, yet discretionary placement policies can lead to differential access at key points in the college preparatory pipeline. We examine a targeted approach to course assignment that uses prior test scores to identify middle school students deemed qualified for a college preparatory math sequence. Accelerated math placement of relatively low-skilled middle schoolers increases the fraction later enrolling in Precalculus by one-seventh, and by over one-third for female and non-low income students. Acceleration increases college readiness and intentions to pursue a bachelor’s degree. Course placement rules based on objective measures can identify students capable of completing rigorous coursework but whom discretionary systems might overlook.

Suggested Citation

  • Shaun Dougherty & Joshua Goodman & Darryl Hill & Erica Litke & Lindsay C. Page, 2015. "Objective Course Placement and College Readiness: Evidence from Targeted Middle School Math Acceleration," NBER Working Papers 21395, National Bureau of Economic Research, Inc.
  • Handle: RePEc:nbr:nberwo:21395
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    1. Levine, Phillip B & Zimmerman, David J, 1995. "The Benefit of Additional High-School Math and Science Classes for Young Men and Women," Journal of Business & Economic Statistics, American Statistical Association, vol. 13(2), pages 137-149, April.
    2. Charles T. Clotfelter & Helen F. Ladd & Jacob L. Vigdor, 2015. "The Aftermath of Accelerating Algebra: Evidence from District Policy Initiatives," Journal of Human Resources, University of Wisconsin Press, vol. 50(1), pages 159-188.
    3. Sebastian Calonico & Matias D. Cattaneo & Rocio Titiunik, 2014. "Robust Nonparametric Confidence Intervals for Regression‐Discontinuity Designs," Econometrica, Econometric Society, vol. 82, pages 2295-2326, November.
    4. Kalena E. Cortes & Joshua S. Goodman & Takako Nomi, 2015. "Intensive Math Instruction and Educational Attainment: Long-Run Impacts of Double-Dose Algebra," Journal of Human Resources, University of Wisconsin Press, vol. 50(1), pages 108-158.
    5. Alberto Alesina & Eliana La Ferrara, 2014. "A Test of Racial Bias in Capital Sentencing," American Economic Review, American Economic Association, vol. 104(11), pages 3397-3433, November.
    6. Jens Ludwig & Douglas L. Miller, 2007. "Does Head Start Improve Children's Life Chances? Evidence from a Regression Discontinuity Design," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 122(1), pages 159-208.
    7. Joseph G. Altonji, 1995. "The Effects of High School Curriculum on Education and Labor Market Outcomes," Journal of Human Resources, University of Wisconsin Press, vol. 30(3), pages 409-438.
    8. Sass, Tim R. & Hannaway, Jane & Xu, Zeyu & Figlio, David N. & Feng, Li, 2012. "Value added of teachers in high-poverty schools and lower poverty schools," Journal of Urban Economics, Elsevier, vol. 72(2), pages 104-122.
    9. C. Kirabo Jackson, 2010. "A Little Now for a Lot Later: A Look at a Texas Advanced Placement Incentive Program," Journal of Human Resources, University of Wisconsin Press, vol. 45(3).
    10. Joseph G. Altonji & Erica Blom & Costas Meghir, 2012. "Heterogeneity in Human Capital Investments: High School Curriculum, College Major, and Careers," Annual Review of Economics, Annual Reviews, vol. 4(1), pages 185-223, July.
    11. Clotfelter, Charles T. & Ladd, Helen F. & Vigdor, Jacob, 2005. "Who teaches whom? Race and the distribution of novice teachers," Economics of Education Review, Elsevier, vol. 24(4), pages 377-392, August.
    12. Juanna Schrøter Joensen & Helena Skyt Nielsen, 2009. "Is there a Causal Effect of High School Math on Labor Market Outcomes?," Journal of Human Resources, University of Wisconsin Press, vol. 44(1).
    13. Imbens, Guido W. & Lemieux, Thomas, 2008. "Regression discontinuity designs: A guide to practice," Journal of Econometrics, Elsevier, vol. 142(2), pages 615-635, February.
    14. Hanushek, Eric A. & Woessmann, Ludger, 2015. "The Knowledge Capital of Nations: Education and the Economics of Growth," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262029170, December.
    15. Goodman, Joshua Samuel, 2012. "The Labor of Division: Returns to Compulsory Math Coursework," Scholarly Articles 9403178, Harvard Kennedy School of Government.
    16. Donald Boyd & Hamilton Lankford & Susanna Loeb & James Wyckoff, 2005. "Explaining the Short Careers of High-Achieving Teachers in Schools with Low-Performing Students," American Economic Review, American Economic Association, vol. 95(2), pages 166-171, May.
    17. Lee, David S. & Card, David, 2008. "Regression discontinuity inference with specification error," Journal of Econometrics, Elsevier, vol. 142(2), pages 655-674, February.
    18. Dario Cestau & Dennis Epple & Holger Sieg, 2017. "Admitting Students to Selective Education Programs: Merit, Profiling, and Affirmative Action," Journal of Political Economy, University of Chicago Press, vol. 125(3), pages 761-797.
    19. Cecilia Rouse & Claudia Goldin, 2000. "Orchestrating Impartiality: The Impact of "Blind" Auditions on Female Musicians," American Economic Review, American Economic Association, vol. 90(4), pages 715-741, September.
    20. Charles T. Clotfelter & Helen F. Ladd & Jacob L. Vigdor, 2006. "Teacher-Student Matching and the Assessment of Teacher Effectiveness," Journal of Human Resources, University of Wisconsin Press, vol. 41(4).
    21. Mustard, David B, 2001. "Racial, Ethnic, and Gender Disparities in Sentencing: Evidence from the U.S. Federal Courts," Journal of Law and Economics, University of Chicago Press, vol. 44(1), pages 285-314, April.
    22. Guido Imbens & Karthik Kalyanaraman, 2012. "Optimal Bandwidth Choice for the Regression Discontinuity Estimator," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 79(3), pages 933-959.
    23. David Card & Laura Giuliano, 2015. "Can Universal Screening Increase the Representation of Low Income and Minority Students in Gifted Education?," NBER Working Papers 21519, National Bureau of Economic Research, Inc.
    24. Dougherty, Shaun & Joshua Goodman & Darryl Hill & Erica Litke & Lindsay Page, "undated". "Middle School Math Acceleration and Equitable Access to 8th Grade Algebra: Evidence from the Wake County Public School System," Working Paper 175236, Harvard University OpenScholar.
    25. Goldin, Claudia D. & Rouse, Cecilia, 2000. "Orchestrating Impartiality: The Impact of “Blind†Auditions on Female Musicians," Scholarly Articles 30703974, Harvard University Department of Economics.
    26. Brown, Charles & Corcoran, Mary, 1997. "Sex-Based Differences in School Content and the Male-Female Wage Gap," Journal of Labor Economics, University of Chicago Press, vol. 15(3), pages 431-465, July.
    27. Cortes, Kalena E. & Goodman, Joshua Samuel & Nomi, Takako, 2015. "Intensive Math Instruction and Educational Attainment," Scholarly Articles 34298862, Harvard Kennedy School of Government.
    28. Jonathan Smith & Michael Hurwitz & Christopher Avery, 2017. "Giving College Credit Where It Is Due: Advanced Placement Exam Scores and College Outcomes," Journal of Labor Economics, University of Chicago Press, vol. 35(1), pages 67-147.
    29. David S. Abrams & Marianne Bertrand & Sendhil Mullainathan, 2012. "Do Judges Vary in Their Treatment of Race?," The Journal of Legal Studies, University of Chicago Press, vol. 41(2), pages 347-383.
    30. Todd Sorensen & Supriya Sarnikar & Ronald L. Oaxaca, 2012. "Race and Gender Differences under Federal Sentencing Guidelines," American Economic Review, American Economic Association, vol. 102(3), pages 256-260, May.
    31. Edward P. Lazear, 2001. "Educational Production," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 116(3), pages 777-803.
    32. C. Kirabo Jackson, 2009. "Student Demographics, Teacher Sorting, and Teacher Quality: Evidence from the End of School Desegregation," Journal of Labor Economics, University of Chicago Press, vol. 27(2), pages 213-256, April.
    33. Jeff Grogger & Eric Eide, 1995. "Changes in College Skills and the Rise in the College Wage Premium," Journal of Human Resources, University of Wisconsin Press, vol. 30(2), pages 280-310.
    34. Blank, Rebecca M, 1991. "The Effects of Double-Blind versus Single-Blind Reviewing: Experimental Evidence from The American Economic Review," American Economic Review, American Economic Association, vol. 81(5), pages 1041-1067, December.
    35. Dylan Conger & Mark C. Long & Patrice Iatarola, 2009. "Explaining race, poverty, and gender disparities in advanced course-taking," Journal of Policy Analysis and Management, John Wiley & Sons, Ltd., vol. 28(4), pages 555-576.
    36. Rose Heather, 2004. "Has Curriculum Closed the Test Score Gap in Math?," The B.E. Journal of Economic Analysis & Policy, De Gruyter, vol. 4(1), pages 1-30, May.
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    Cited by:

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    4. Andrew McEachin & Thurston Domina & Andrew Penner, 2020. "Heterogeneous Effects of Early Algebra across California Middle Schools," Journal of Policy Analysis and Management, John Wiley & Sons, Ltd., vol. 39(3), pages 772-800, June.
    5. Hemelt, Steven W. & Lenard, Matthew A., 2020. "Math acceleration in elementary school: Access and effects on student outcomes," Economics of Education Review, Elsevier, vol. 74(C).

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    JEL classification:

    • I20 - Health, Education, and Welfare - - Education - - - General
    • I24 - Health, Education, and Welfare - - Education - - - Education and Inequality
    • J24 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Human Capital; Skills; Occupational Choice; Labor Productivity

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