IDEAS home Printed from https://ideas.repec.org/p/umc/wpaper/1401.html
   My bibliography  Save this paper

Selecting Growth Measures for School and Teacher Evaluations

Author

Abstract

There is increased policy interest in extending the test-based evaluation framework in K-12 education to include student achievement in high school. High school achievement is typically measured by performance on end-of-course exams (EOCs), which test course-specific standards in subjects including algebra, biology, English, geometry, and history, among others. However, unlike standardized tests in the early grades, students take EOCs at different points in their schooling careers. The timing of the test is a choice variable presumably determined by input from administrators, students and parents. Recent research indicates that school and district policies that determine when students take particular courses can have important consequences for achievement and subsequent outcomes, such as advanced course taking. The contribution of the present study is to develop an approach for modeling EOC test performance that disentangles the influence of school and district policies regarding the timing of course taking from other factors. After separating out the timing issue, better measures of the quality of instruction provided by districts, schools and teachers can be obtained. Our approach also offers diagnostic value because it explicitly separates out the influence of school and district course-taking policies from other factors that determine student achievement.

Suggested Citation

  • 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.
  • Handle: RePEc:umc:wpaper:1401
    as

    Download full text from publisher

    File URL: https://drive.google.com/file/d/1jpUMBQKHzC4bRHl15GwYmmFBceESQuo1/view?usp=sharing
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Harris, Douglas N. & Sass, Tim R., 2014. "Skills, productivity and the evaluation of teacher performance," Economics of Education Review, Elsevier, vol. 40(C), pages 183-204.
    2. 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 841-864, October.
    3. Eric A. Hanushek & EJohn F. Kain & Steven G. Rivkin, 2004. "Why Public Schools Lose Teachers," Journal of Human Resources, University of Wisconsin Press, vol. 39(2).
    4. 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.
    5. Gadi Barlevy & Derek Neal, 2012. "Pay for Percentile," American Economic Review, American Economic Association, vol. 102(5), pages 1805-1831, August.
    6. 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.
    7. Cory Koedel & Mark Ehlert & Eric Parsons & Michael Podgursky, 2012. "Selecting Growth Measures for School and Teacher Evaluations," Working Papers 1210, Department of Economics, University of Missouri.
    8. repec:pri:cepsud:170rothstein is not listed on IDEAS
    9. Jonah E. Rockoff, 2004. "The Impact of Individual Teachers on Student Achievement: Evidence from Panel Data," American Economic Review, American Economic Association, vol. 94(2), pages 247-252, May.
    10. 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.
    11. Andrew Schotter & Keith Weigelt, 1992. "Asymmetric Tournaments, Equal Opportunity Laws, and Affirmative Action: Some Experimental Results," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 107(2), pages 511-539.
    12. 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.
    13. 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.
    14. repec:mpr:mprres:7330 is not listed on IDEAS
    15. Canice Prendergast, 1999. "The Provision of Incentives in Firms," Journal of Economic Literature, American Economic Association, vol. 37(1), pages 7-63, March.
    16. 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.
    17. 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 267-271, May.
    18. Duflo, Esther & Dupas, Pascaline & Kremer, Michael, 2015. "School governance, teacher incentives, and pupil–teacher ratios: Experimental evidence from Kenyan primary schools," Journal of Public Economics, Elsevier, vol. 123(C), pages 92-110.
    19. repec:mpr:mprres:7333 is not listed on IDEAS
    20. Cory Koedel & Julian R. Betts, 2011. "Does Student Sorting Invalidate Value-Added Models of Teacher Effectiveness? An Extended Analysis of the Rothstein Critique," Education Finance and Policy, MIT Press, vol. 6(1), pages 18-42, January.
    21. Eric A. Hanushek & John F. Kain & Steven G. Rivkin & Daniel M. O'Brien, 2005. "The Market for Teacher Quality," Discussion Papers 04-025, Stanford Institute for Economic Policy Research.
    22. 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.
    23. 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(1), pages 95-135.
    24. 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.
    25. 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.
    26. C. Kirabo Jackson, 2014. "Teacher Quality at the High School Level: The Importance of Accounting for Tracks," Journal of Labor Economics, University of Chicago Press, vol. 32(4), pages 645-684.
    27. 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 231-250, May.
    28. Dan Goldhaber & Duncan Chaplin, "undated". "Assessing the Rothstein Test: Does It Really Show Teacher Value-Added Models Are Biased?," Mathematica Policy Research Reports 77f489fc94a34a0e96a42c419, Mathematica Policy Research.
    29. Kane, Thomas J. & Rockoff, Jonah E. & Staiger, Douglas O., 2008. "What does certification tell us about teacher effectiveness? Evidence from New York City," Economics of Education Review, Elsevier, vol. 27(6), pages 615-631, December.
    30. 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.
    31. 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.
    32. 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, July.
    33. 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.
    34. 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.
    35. Dan Goldhaber & Michael Hansen, 2010. "Using Performance on the Job to Inform Teacher Tenure Decisions," American Economic Review, American Economic Association, vol. 100(2), pages 250-255, May.
    36. Dale Ballou, 2009. "Test Scaling and Value-Added Measurement," Education Finance and Policy, MIT Press, vol. 4(4), pages 351-383, October.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    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. repec:mpr:mprres:7949 is not listed on IDEAS
    3. Cory Koedel & Jiaxi Li, 2016. "The Efficiency Implications Of Using Proportional Evaluations To Shape The Teaching Workforce," Contemporary Economic Policy, Western Economic Association International, vol. 34(1), pages 47-62, January.
    4. Matthew Johnson & Stephen Lipscomb & Brian Gill, 2013. "Sensitivity of Teacher Value-Added Estimates to Student and Peer Control Variables," Mathematica Policy Research Reports 3f875df699534c72b9e57c39d, Mathematica Policy Research.
    5. 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.
    6. Cory Koedel & Mark Ehlert & Eric Parsons & Michael Podgursky, 2012. "Selecting Growth Measures for School and Teacher Evaluations," Working Papers 1210, Department of Economics, University of Missouri.
    7. Eric Parsons & Cory Koedel & Li Tan, 2019. "Accounting for Student Disadvantage in Value-Added Models," Journal of Educational and Behavioral Statistics, , vol. 44(2), pages 144-179, April.
    8. Aedin Doris & Donal O'Neill & Olive Sweetman, 2019. "Good Schools or Good Students? The Importance of Selectivity for School Rankings," Economics Department Working Paper Series n293-19.pdf, Department of Economics, National University of Ireland - Maynooth.
    9. Elias Walsh & Eric Isenberg, 2013. "How Does a Value-Added Model Compare to the Colorado Growth Model?," Mathematica Policy Research Reports e703eea3252e43d39fee791e5, Mathematica Policy Research.
    10. Shannon W. Anderson & Amanda Kimball, 2019. "Evidence for the Feedback Role of Performance Measurement Systems," Management Science, INFORMS, vol. 65(9), pages 4385-4406, September.
    11. Andrew McEachin & Allison Atteberry, 2017. "The Impact of Summer Learning Loss on Measures of School Performance," Education Finance and Policy, MIT Press, vol. 12(4), pages 468-491, Fall.
    12. Katherine E. Castellano & Andrew D. Ho, 2015. "Practical Differences Among Aggregate-Level Conditional Status Metrics," Journal of Educational and Behavioral Statistics, , vol. 40(1), pages 35-68, February.
    13. Susanna Loeb & Michael S. Christian & Heather Hough & Robert H. Meyer & Andrew B. Rice & Martin R. West, 2019. "School Differences in Social–Emotional Learning Gains: Findings From the First Large-Scale Panel Survey of Students," Journal of Educational and Behavioral Statistics, , vol. 44(5), pages 507-542, October.
    14. repec:mpr:mprres:7941 is not listed on IDEAS
    15. Steinberg, Matthew P. & MacDonald, John M., 2019. "The effects of closing urban schools on students’ academic and behavioral outcomes: Evidence from Philadelphia," Economics of Education Review, Elsevier, vol. 69(C), pages 25-60.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. 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.
    2. Koedel, Cory & Mihaly, Kata & Rockoff, Jonah E., 2015. "Value-added modeling: A review," Economics of Education Review, Elsevier, vol. 47(C), pages 180-195.
    3. Cory Koedel & Jiaxi Li, 2016. "The Efficiency Implications Of Using Proportional Evaluations To Shape The Teaching Workforce," Contemporary Economic Policy, Western Economic Association International, vol. 34(1), pages 47-62, January.
    4. Allison Atteberry & Susanna Loeb & James Wyckoff, 2013. "Do First Impressions Matter? Improvement in Early Career Teacher Effectiveness," NBER Working Papers 19096, National Bureau of Economic Research, Inc.
    5. Azam, Mehtabul & Kingdon, Geeta Gandhi, 2015. "Assessing teacher quality in India," Journal of Development Economics, Elsevier, vol. 117(C), pages 74-83.
    6. Hanushek, Eric A. & Rivkin, Steven G. & Schiman, Jeffrey C., 2016. "Dynamic effects of teacher turnover on the quality of instruction," Economics of Education Review, Elsevier, vol. 55(C), pages 132-148.
    7. Dan Goldhaber & Michael Hansen, 2013. "Is it Just a Bad Class? Assessing the Long-term Stability of Estimated Teacher Performance," Economica, London School of Economics and Political Science, vol. 80(319), pages 589-612, July.
    8. Eric Parsons & Cory Koedel & Li Tan, 2019. "Accounting for Student Disadvantage in Value-Added Models," Journal of Educational and Behavioral Statistics, , vol. 44(2), pages 144-179, April.
    9. Marine de Talancé, 2015. "Better Teachers, Better Results? Evidence from Rural Pakistan," Working Papers DT/2015/21, DIAL (Développement, Institutions et Mondialisation).
    10. Nirav Mehta, 2019. "Measuring quality for use in incentive schemes: The case of “shrinkage” estimators," Quantitative Economics, Econometric Society, vol. 10(4), pages 1537-1577, November.
    11. Sean Corcoran & Dan Goldhaber, 2013. "Value Added and Its Uses: Where You Stand Depends on Where You Sit," Education Finance and Policy, MIT Press, vol. 8(3), pages 418-434, July.
    12. Raj Chetty & John N. Friedman & Jonah E. Rockoff, 2014. "Measuring the Impacts of Teachers I: Evaluating Bias in Teacher Value-Added Estimates," American Economic Review, American Economic Association, vol. 104(9), pages 2593-2632, September.
    13. Peter Z. Schochet & Hanley S. Chiang, 2013. "What Are Error Rates for Classifying Teacher and School Performance Using Value-Added Models?," Journal of Educational and Behavioral Statistics, , vol. 38(2), pages 142-171, April.
    14. Jonah E. Rockoff & Douglas O. Staiger & Thomas J. Kane & Eric S. Taylor, 2012. "Information and Employee Evaluation: Evidence from a Randomized Intervention in Public Schools," American Economic Review, American Economic Association, vol. 102(7), pages 3184-3213, December.
    15. Hanushek, Eric A., 2011. "The economic value of higher teacher quality," Economics of Education Review, Elsevier, vol. 30(3), pages 466-479, June.
    16. Figlio, D. & Karbownik, K. & Salvanes, K.G., 2016. "Education Research and Administrative Data," Handbook of the Economics of Education,, Elsevier.
    17. Rockoff, Jonah E. & Speroni, Cecilia, 2011. "Subjective and objective evaluations of teacher effectiveness: Evidence from New York City," Labour Economics, Elsevier, vol. 18(5), pages 687-696, October.
    18. Cory Koedel & Eric Parsons & Michael Podgursky & Mark Ehlert, 2015. "Teacher Preparation Programs and Teacher Quality: Are There Real Differences Across Programs?," Education Finance and Policy, MIT Press, vol. 10(4), pages 508-534, October.
    19. 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.
    20. Richard K. Mansfield, 2015. "Teacher Quality and Student Inequality," Journal of Labor Economics, University of Chicago Press, vol. 33(3), pages 751-788.

    More about this item

    Keywords

    value-added; end-of-course exam; end-of-course testing; course timing;
    All these keywords.

    JEL classification:

    • I20 - Health, Education, and Welfare - - Education - - - General

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:umc:wpaper:1401. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Chao Gu (email available below). General contact details of provider: https://edirc.repec.org/data/edumous.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.