IDEAS home Printed from https://ideas.repec.org/
MyIDEAS: Login to save this paper or follow this series

Evaluating Students' Evaluations of Professors

  • Braga, Michela

    ()

    (University of Milan)

  • Paccagnella, Marco

    ()

    (Bank of Italy)

  • Pellizzari, Michele

    ()

    (University of Geneva)

This paper contrasts measures of teacher effectiveness with the students' evaluations for the same teachers using administrative data from Bocconi University (Italy). The effectiveness measures are estimated by comparing the subsequent performance in follow-on coursework of students who are randomly assigned to teachers in each of their compulsory courses. We find that, even in a setting where the syllabuses are fixed and all teachers in the same course present exactly the same material, teachers still matter substantially. The average difference in subsequent performance between students who were assigned to the best and worst teacher (on the effectiveness scale) is approximately 43% of a standard deviation in the distribution of exam grades, corresponding to about 5.6% of the average grade. Additionally, we find that our measure of teacher effectiveness is negatively correlated with the students' evaluations: in other words, teachers who are associated with better subsequent performance receive worst evaluations from their students. We rationalize these results with a simple model where teachers can either engage in real teaching or in teaching-to-the-test, the former requiring higher students’ effort than the latter. Teaching-to-the-test guarantees high grades in the current course but does not improve future outcomes. Hence, if students are myopic and evaluate better teachers from which they derive higher utility in a static framework, the model is capable of predicting our empirical finding that good teachers receive bad evaluations, especially when teaching-to-the-test is very effective (for example, with multiple choice tests). Consistently with the predictions of the model, we also find that classes in which high skill students are over-represented produce evaluations that are less at odds with estimated teacher effectiveness.

If you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.

File URL: http://ftp.iza.org/dp5620.pdf
Download Restriction: no

Paper provided by Institute for the Study of Labor (IZA) in its series IZA Discussion Papers with number 5620.

as
in new window

Length: 54 pages
Date of creation: Apr 2011
Date of revision:
Publication status: published in: Economics of Education Review, 2014, 41, 71-88
Handle: RePEc:iza:izadps:dp5620
Contact details of provider: Postal: IZA, P.O. Box 7240, D-53072 Bonn, Germany
Phone: +49 228 3894 223
Fax: +49 228 3894 180
Web page: http://www.iza.org

Order Information: Postal: IZA, Margard Ody, P.O. Box 7240, D-53072 Bonn, Germany
Email:


References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:

as in new window
  1. Hanushek, Eric A. & Rivkin, Steven G., 2006. "Teacher Quality," Handbook of the Economics of Education, Elsevier.
  2. Swamy, P A V B & Arora, S S, 1972. "The Exact Finite Sample Properties of the Estimators of Coefficients in the Error Components Regression Models," Econometrica, Econometric Society, vol. 40(2), pages 261-75, March.
  3. Victor Lavy, 2009. "Performance Pay and Teachers' Effort, Productivity, and Grading Ethics," American Economic Review, American Economic Association, vol. 99(5), pages 1979-2011, December.
  4. Spence, A Michael, 1973. "Job Market Signaling," The Quarterly Journal of Economics, MIT Press, vol. 87(3), pages 355-74, August.
  5. Jesse Rothstein, 2009. "Student sorting and bias in value added estimation: Selection on observables and unobservables," NBER Working Papers 14666, National Bureau of Economic Research, Inc.
  6. Chetty, Raj & Friedman, John Norton & Hilger, Nathanial & Saez, Emmanuel & Schanzenbach, Dianne Whitmore & Yagan, Danny, 2011. "How Does Your Kindergarten Classroom Affect Your Earnings? Evidence from Project Star," Scholarly Articles 9639983, Harvard Kennedy School of Government.
  7. Canice Prendergast & Robert H. Topel, 1993. "Favoritism in Organizations," NBER Working Papers 4427, National Bureau of Economic Research, Inc.
  8. Bandiera, Oriana & Larcinese, Valentino & Rasul, Imran, 2009. "Heterogeneous Class Size Effects: New Evidence from a Panel of University Students," IZA Discussion Papers 4496, Institute for the Study of Labor (IZA).
  9. Holmstrom, Bengt & Milgrom, Paul, 1994. "The Firm as an Incentive System," American Economic Review, American Economic Association, vol. 84(4), pages 972-91, September.
  10. Giacomo De Giorgi & Michele Pellizzari & Silvia Redaelli, 2010. "Identification of Social Interactions through Partially Overlapping Peer Groups," American Economic Journal: Applied Economics, American Economic Association, vol. 2(2), pages 241-75, April.
  11. Figlio, David N. & Kenny, Lawrence W., 2007. "Individual teacher incentives and student performance," Journal of Public Economics, Elsevier, vol. 91(5-6), pages 901-914, June.
  12. Steven G. Rivkin & Eric A. Hanushek & John F. Kain, 2005. "Teachers, Schools, and Academic Achievement," Econometrica, Econometric Society, vol. 73(2), pages 417-458, 03.
  13. Scott E. Carrell & James E. West, 2008. "Does Professor Quality Matter? Evidence from Random Assignment of Students to Professors," NBER Working Papers 14081, National Bureau of Economic Research, Inc.
  14. Giacomo De Giorgi & Michele Pellizzari & William Gui Woolston, 2012. "Class Size And Class Heterogeneity," Journal of the European Economic Association, European Economic Association, vol. 10(4), pages 795-830, 08.
  15. 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.
  16. Beleche, Trinidad & Fairris, David & Marks, Mindy, 2012. "Do course evaluations truly reflect student learning? Evidence from an objectively graded post-test," Economics of Education Review, Elsevier, vol. 31(5), pages 709-719.
  17. Michael Watts & William E. Becker, 1999. "How Departments of Economics Evaluate Teaching," American Economic Review, American Economic Association, vol. 89(2), pages 344-349, May.
  18. Barrington-Leigh, Christopher P, 2008. "Weather as a transient influence on survey-reported satisfaction with life," MPRA Paper 25736, University Library of Munich, Germany.
  19. Bruce A. Weinberg & Masanori Hashimoto & Belton M. Fleisher, 2009. "Evaluating Teaching in Higher Education," The Journal of Economic Education, Taylor & Francis Journals, vol. 40(3), pages 227-261, July.
  20. 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 250-55, May.
  21. Krautmann, Anthony C. & Sander, William, 1999. "Grades and student evaluations of teachers," Economics of Education Review, Elsevier, vol. 18(1), pages 59-63, February.
  22. George Baker & Robert Gibbons & Kevin J. Murphy, 1993. "Subjective Performance Measures in Optimal Incentive Contracts," NBER Working Papers 4480, National Bureau of Economic Research, Inc.
  23. Jesse Rothstein, 2010. "Teacher Quality in Educational Production: Tracking, Decay, and Student Achievement," The Quarterly Journal of Economics, MIT Press, vol. 125(1), pages 175-214, February.
  24. Marie Connolly Pray, 2011. "Some Like It Mild and Not Too Wet: the Influence of Weather on Subjective Well-Being," Cahiers de recherche 1116, CIRPEE.
  25. Joshua D. Angrist & Victor Lavy, 1999. "Using Maimonides' Rule To Estimate The Effect Of Class Size On Scholastic Achievement," The Quarterly Journal of Economics, MIT Press, vol. 114(2), pages 533-575, May.
  26. Brian A. Jacob & Lars Lefgren, 2008. "Can Principals Identify Effective Teachers? Evidence on Subjective Performance Evaluation in Education," Journal of Labor Economics, University of Chicago Press, vol. 26, pages 101-136.
  27. John H. Tyler & Eric S. Taylor & Thomas J. Kane & Amy L. Wooten, 2010. "Using Student Performance Data to Identify Effective Classroom Practices," American Economic Review, American Economic Association, vol. 100(2), pages 256-60, May.
  28. 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.
  29. Timothy D. Hoga, 1981. "Faculty Research Activity and the Quality of Graduate Training," Journal of Human Resources, University of Wisconsin Press, vol. 16(3), pages 400-415.
  30. Alan B. Krueger, 1997. "Experimental Estimates of Education Production Functions," NBER Working Papers 6051, National Bureau of Economic Research, Inc.
  31. Brown, Byron W. & Saks, Daniel H., 1987. "The microeconomics of the allocation of teachers' time and student learning," Economics of Education Review, Elsevier, vol. 6(4), pages 319-332, August.
  32. Jonah E. Rockoff & Cecilia Speroni, 2010. "Subjective and Objective Evaluations of Teacher Effectiveness," American Economic Review, American Economic Association, vol. 100(2), pages 261-66, May.
  33. Esther Duflo & Rema Hanna & Stephen P. Ryan, 2012. "Incentives Work: Getting Teachers to Come to School," American Economic Review, American Economic Association, vol. 102(4), pages 1241-78, June.
  34. Eric A. Hanushek, 1979. "Conceptual and Empirical Issues in the Estimation of Educational Production Functions," Journal of Human Resources, University of Wisconsin Press, vol. 14(3), pages 351-388.
Full references (including those not matched with items on IDEAS)

This item is featured on the following reading lists or Wikipedia pages:

  1. Economic Logic blog

When requesting a correction, please mention this item's handle: RePEc:iza:izadps:dp5620. See general information about how to correct material in RePEc.

For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Mark Fallak)

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 references are entirely missing, you can add them using this form.

If the full references list an item that is present in RePEc, but the system did not link 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 profile, as there may be some citations waiting for confirmation.

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

This information is provided to you by IDEAS at the Research Division of the Federal Reserve Bank of St. Louis using RePEc data.