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Selecting Growth Measures for School and Teacher Evaluations

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Abstract

The specifics of how growth models should be constructed and used to evaluate schools and teachers is a topic of lively policy debate in states and school districts nationwide. In this paper we take up the question of model choice and examine three competing approaches. The first approach, reflected in the popular student growth percentiles (SGPs) framework, eschews all controls for student covariates and schooling environments. The second approach, typically associated with value-added models (VAMs), controls for student background characteristics and aims to identify the causal effects of schools and teachers. The third approach, also VAM-based, fully levels the playing field so that the correlation between school- and teacher-level growth measures and student demographics is essentially zero. We argue that the third approach is the most desirable for use in educational evaluation systems. Our case rests on personnel economics, incentive-design theory, and the potential role that growth measures can play in improving instruction in K-12 schools.

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Bibliographic Info

Paper provided by Department of Economics, University of Missouri in its series Working Papers with number 1210.

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Length: 29 pgs.
Date of creation: 17 Aug 2012
Date of revision:
Handle: RePEc:umc:wpaper:1210

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Keywords: Teacher evaluation; school evaluation; value-added models; value-added versus SGP;

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References

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  1. Cory Koedel & Julian Betts, 2009. "Does Student Sorting Invalidate Value-Added Models of Teacher Effectiveness? An Extended Analysis of the Rothstein Critique," Working Papers 0902, Department of Economics, University of Missouri.
  2. Eric A. Hanushek & Steven G. Rivkin, 2010. "Generalizations about Using Value-Added Measures of Teacher Quality," American Economic Review, American Economic Association, vol. 100(2), pages 267-71, May.
  3. Lazear, Edward P & Rosen, Sherwin, 1981. "Rank-Order Tournaments as Optimum Labor Contracts," Journal of Political Economy, University of Chicago Press, vol. 89(5), pages 841-64, October.
  4. Charles T. Clotfelter & Helen F. Ladd & Jacob L. Vigdor, 2012. "Algebra for 8th Graders: Evidence on its Effects from 10 North Carolina Districts," NBER Working Papers 18649, National Bureau of Economic Research, Inc.
  5. Canice Prendergast, 1999. "The Provision of Incentives in Firms," Journal of Economic Literature, American Economic Association, vol. 37(1), pages 7-63, March.
  6. Gadi Barlevy & Derek Neal, 2009. "Pay for percentile," Working Paper Series WP-09-09, Federal Reserve Bank of Chicago.
  7. Thomas J. Kane & Douglas O. Staiger, 2002. "The Promise and Pitfalls of Using Imprecise School Accountability Measures," Journal of Economic Perspectives, American Economic Association, vol. 16(4), pages 91-114, Fall.
  8. Daniel Aaronson & Lisa Barrow & William Sander, 2007. "Teachers and Student Achievement in the Chicago Public High Schools," Journal of Labor Economics, University of Chicago Press, vol. 25, pages 95-135.
  9. 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.
  10. Esther Duflo & Pascaline Dupas & Michael Kremer, 2012. "School Governance, Teacher Incentives, and Pupil-Teacher Ratios: Experimental Evidence from Kenyan Primary Schools," NBER Working Papers 17939, National Bureau of Economic Research, Inc.
  11. Raj Chetty & John N. Friedman & Jonah E. Rockoff, 2011. "The Long-Term Impacts of Teachers: Teacher Value-Added and Student Outcomes in Adulthood," NBER Working Papers 17699, National Bureau of Economic Research, Inc.
  12. Eric S. Taylor & John H. Tyler, 2011. "The Effect of Evaluation on Performance: Evidence from Longitudinal Student Achievement Data of Mid-career Teachers," NBER Working Papers 16877, National Bureau of Economic Research, Inc.
  13. Dale Ballou, 2009. "Test Scaling and Value-Added Measurement," Education Finance and Policy, MIT Press, vol. 4(4), pages 351-383, October.
  14. Thomas J. Kane & Jonah E. Rockoff & Douglas O. Staiger, 2006. "What Does Certification Tell Us About Teacher Effectiveness? Evidence from New York City," NBER Working Papers 12155, National Bureau of Economic Research, Inc.
  15. Joseph G. Altonji & Todd E. Elder & Christopher R. Taber, 2005. "Selection on Observed and Unobserved Variables: Assessing the Effectiveness of Catholic Schools," Journal of Political Economy, University of Chicago Press, vol. 113(1), pages 151-184, February.
  16. Karthik Muralidharan & Venkatesh Sundararaman, 2011. "Teacher Performance Pay: Experimental Evidence from India," Journal of Political Economy, University of Chicago Press, vol. 119(1), pages 39 - 77.
  17. Cory Koedel & Jason A. Grissom & Shawn Ni & Michael Podgursky, 2011. "Pension-Induced Rigidities in the Labor Market for School Leaders," Working Papers 1115, Department of Economics, University of Missouri.
  18. Koedel Cory & Leatherman Rebecca & Parsons Eric, 2012. "Test Measurement Error and Inference from Value-Added Models," The B.E. Journal of Economic Analysis & Policy, De Gruyter, vol. 12(1), pages 1-37, November.
  19. Thomas J. Kane & Douglas O. Staiger, 2008. "Estimating Teacher Impacts on Student Achievement: An Experimental Evaluation," NBER Working Papers 14607, National Bureau of Economic Research, Inc.
  20. Charles T. Clotfelter & Helen F. Ladd & Jacob L. Vigdor, 2012. "The Aftermath of Accelerating Algebra: Evidence from a District Policy Initiative," NBER Working Papers 18161, National Bureau of Economic Research, Inc.
  21. Cory Koedel & Mark Ehlert & Eric Parsons & Michael Podgursky & P. Brett Xiang, 2014. "Selecting Growth Measures for School and Teacher Evaluations," Working Papers 1401, Department of Economics, University of Missouri.
  22. Eric A. Hanushek & John F. Kain & Steven G. Rivkin, 2001. "Why Public Schools Lose Teachers," NBER Working Papers 8599, National Bureau of Economic Research, Inc.
  23. Schotter, Andrew & Weigelt, Keith, 1992. "Asymmetric Tournaments, Equal Opportunity Laws, and Affirmative Action: Some Experimental Results," The Quarterly Journal of Economics, MIT Press, vol. 107(2), pages 511-39, May.
  24. Jesse Rothstein, 2009. "Student Sorting and Bias in Value-Added Estimation: Selection on Observables and Unobservables," Education Finance and Policy, MIT Press, vol. 4(4), pages 537-571, October.
  25. Eric A. Hanushek & John F. Kain & Daniel M. O'Brien & Steven G. Rivkin, 2005. "The Market for Teacher Quality," NBER Working Papers 11154, National Bureau of Economic Research, Inc.
  26. Timothy G. Conley & Christian B. Hansen & Peter E. Rossi, 2012. "Plausibly Exogenous," The Review of Economics and Statistics, MIT Press, vol. 94(1), pages 260-272, February.
  27. Eric A. Hanushek & Steven G. Rivkin, 2012. "The Distribution of Teacher Quality and Implications for Policy," Annual Review of Economics, Annual Reviews, vol. 4(1), pages 131-157, 07.
  28. Betts, Julian R, 1995. "Does School Quality Matter? Evidence from the National Longitudinal Survey of Youth," The Review of Economics and Statistics, MIT Press, vol. 77(2), pages 231-50, May.
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Citations

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Cited by:
  1. Brendan Houng & Moshe Justman, 2013. "Comparing Least-Squares Value-Added Analysis and Student Growth Percentile Analysis for Evaluating Student Progress and Estimating School Effects," Melbourne Institute Working Paper Series wp2013n07, Melbourne Institute of Applied Economic and Social Research, The University of Melbourne.
  2. Cory Koedel & Mark Ehlert & Eric Parsons & Michael Podgursky & P. Brett Xiang, 2014. "Selecting Growth Measures for School and Teacher Evaluations," Working Papers 1401, Department of Economics, University of Missouri.
  3. Matthew Johnson & Stephen Lipscomb & Brian Gill, 2013. "Sensitivity of Teacher Value-Added Estimates to Student and Peer Control Variables," Mathematica Policy Research Reports 7941, Mathematica Policy Research.
  4. Moshe Justman & Brendan Houng, 2013. "A Comparison Of Two Methods For Estimating School Effects And Tracking Student Progress From Standardized Test Scores," Working Papers 1316, Ben-Gurion University of the Negev, Department of Economics.
  5. Cory Koedel & Jiaxi Li, 2014. "The Efficiency Implications of Using Proportional Evaluations to Shape the Teaching Workforce," Working Papers 1402, Department of Economics, University of Missouri.
  6. Elias Walsh & Eric Isenberg, 2013. "How Does a Value-Added Model Compare to the Colorado Growth Model?," Mathematica Policy Research Reports 7949, Mathematica Policy Research.

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