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Accounting for exogenous influences in a benevolent performance evaluation of teachers

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  • De Witte, Kristof

    () (Katholieke Universiteit Leuven, Belgium
    Maastricht University TIER, Maastricht, the Netherlands)

  • Rogge, Nicky

    () (Hogeschool-Universiteit Brussel (HUB), Belgium
    Katholieke Universiteit Leuven, Belgium)

Abstract

Students evaluations of teacher performance (SETs) are increasingly used by universities and colleges for teaching improvement and decision making (e.g., promotion or tenure). However, SETs are highly controversial mainly due to two issues: (1) teachers value various aspects of excellent teaching differently, and, to be fair, (2) SETs should be determined solely by the teachers actual performance in the classroom, not by other influences (related to the teacher, the students or the course) which are not under his or her control. To account for these two issues, this paper constructs SETs using a specially tailored version of the popular non-parametric Data Envelopment Analysis (DEA) approach. In particular, in a so-called Benefit of the doubt model we account for different values and interpretations that teachers attach to good teaching. Within this model, we reduce the impact of measurement errors and a-typical observations, and account explicitly for heterogeneous background characteristics arising from teacher, student and course characteristics. To show the potentiality of the method, we examine teacher performance for the Hogeschool Universiteit Brussel (located in Belgium). Our findings suggest that heterogeneous background characteristics play an important role in teacher performance.

Suggested Citation

  • De Witte, Kristof & Rogge, Nicky, 2009. "Accounting for exogenous influences in a benevolent performance evaluation of teachers," Working Papers 2009/15, Hogeschool-Universiteit Brussel, Faculteit Economie en Management.
  • Handle: RePEc:hub:wpecon:200915
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    References listed on IDEAS

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    1. Kristof DE WITTE & Mika KORTELAINEN, 2008. "Blaming the exogenous environment? Conditional efficiency estimation with continuous and discrete environmental variables," Working Papers Department of Economics ces0833, KU Leuven, Faculty of Economics and Business, Department of Economics.
    2. Michael A. McPherson, 2006. "Determinants of How Students Evaluate Teachers," The Journal of Economic Education, Taylor & Francis Journals, vol. 37(1), pages 3-20, January.
    3. Martin Davies & Joe Hirschberg & Jenny Lye & Carol Johnston & Ian Mcdonald, 2007. "Systematic Influences On Teaching Evaluations: The Case For Caution ," Australian Economic Papers, Wiley Blackwell, vol. 46(1), pages 18-38, March.
    4. Cinzia Daraio & Léopold Simar, 2005. "Introducing Environmental Variables in Nonparametric Frontier Models: a Probabilistic Approach," Journal of Productivity Analysis, Springer, vol. 24(1), pages 93-121, September.
    5. Rogge, Nicky, 2009. "Granting teachers the 'benefit of the doubt' in performance evaluations," Working Papers 2009/17, Hogeschool-Universiteit Brussel, Faculteit Economie en Management.
    6. Knox Lovell, C. A. & Pastor, Jesus T. & Turner, Judi A., 1995. "Measuring macroeconomic performance in the OECD: A comparison of European and non-European countries," European Journal of Operational Research, Elsevier, vol. 87(3), pages 507-518, December.
    7. Krautmann, Anthony C. & Sander, William, 1999. "Grades and student evaluations of teachers," Economics of Education Review, Elsevier, vol. 18(1), pages 59-63, February.
    8. Charnes, A. & Cooper, W. W. & Rhodes, E., 1978. "Measuring the efficiency of decision making units," European Journal of Operational Research, Elsevier, vol. 2(6), pages 429-444, November.
    9. Cinzia Daraio & Léopold Simar, 2007. "Conditional nonparametric frontier models for convex and nonconvex technologies: a unifying approach," Journal of Productivity Analysis, Springer, vol. 28(1), pages 13-32, October.
    10. Laurens Cherchye & Willem Moesen & Nicky Rogge & Tom Puyenbroeck, 2007. "An Introduction to ‘Benefit of the Doubt’ Composite Indicators," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 82(1), pages 111-145, May.
    11. Qi Li & Jeffrey Scott Racine, 2006. "Nonparametric Econometrics: Theory and Practice," Economics Books, Princeton University Press, edition 1, number 8355.
    12. Paul Isely & Harinder Singh, 2005. "Do Higher Grades Lead to Favorable Student Evaluations?," The Journal of Economic Education, Taylor & Francis Journals, vol. 36(1), pages 29-42, January.
    13. Zhou, P. & Ang, B.W. & Poh, K.L., 2007. "A mathematical programming approach to constructing composite indicators," Ecological Economics, Elsevier, vol. 62(2), pages 291-297, April.
    14. Cazals, Catherine & Florens, Jean-Pierre & Simar, Leopold, 2002. "Nonparametric frontier estimation: a robust approach," Journal of Econometrics, Elsevier, vol. 106(1), pages 1-25, January.
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    Cited by:

    1. Fabio Pammolli & Francesco Porcelli & Francesco Vidoli & Guido Borà, 2014. "La spesa sanitaria delle Regioni in Italia - Saniregio 3," Working Papers CERM 02-2014, Competitività, Regole, Mercati (CERM).
    2. Fabio Pammolli & Francesco Porcelli & Francesco Vidoli & Guido Borà, 2015. "La spesa sanitaria delle Regioni in Italia - Saniregio 2015," Working Papers CERM 01-2015, Competitività, Regole, Mercati (CERM), revised 04 Jan 2016.
    3. Rogge, Nicky, 2009. "Robust benevolent evaluations of teaching performance," Working Papers 2009/21, Hogeschool-Universiteit Brussel, Faculteit Economie en Management.
    4. Rogge, Nicky & De Witte, Kristof, 2009. "To publish or not to publish? On the aggregation and drivers of research performance," Working Papers 2009/42, Hogeschool-Universiteit Brussel, Faculteit Economie en Management.
    5. Francesco Vidoli & Elisa Fusco & Claudio Mazziotta, 2015. "Non-compensability in Composite Indicators: A Robust Directional Frontier Method," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 122(3), pages 635-652, July.
    6. repec:spr:scient:v:85:y:2010:i:3:d:10.1007_s11192-010-0286-5 is not listed on IDEAS

    More about this item

    Keywords

    Teacher performance; Data envelopment analysis; Conditional efficiency; Education;

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C25 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions; Probabilities
    • I21 - Health, Education, and Welfare - - Education - - - Analysis of Education

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