IDEAS home Printed from https://ideas.repec.org/p/pbs/ecofin/2020-05.html
   My bibliography  Save this paper

He Taught, She Taught: The effect of teaching style, academic credentials, bias awareness and academic discipline on gender bias in teaching evaluations

Author

Listed:
  • Nigel Burnell

    (University of Surrey)

  • Irina Cojuharenco

    (University of Surrey)

  • Zahra Murad

    (University of Portsmouth)

Abstract

Gender bias in teaching evaluations leads to unfair decisions during academics􏰀 careers. In four controlled experiments, we examine the role of academics􏰀 teaching style, academic credentials, academic discipline and bias awareness on gender bias in teaching evaluations. In Study 1, we test competing hypotheses regarding the effect of teaching style on gender bias. We find that a high warmth teaching style increases female academics􏰀 perceived warmth, but decreases their perceived competence, so gender bias in evaluations persists. In Study 2, we find that gender bias disappears for academic with senior credentials. Additionally, we find no evidence of less biased evaluations by those who anticipate gender bias. In Study 3 and Study 4, we test the robustness of our results in a different academic discipline and using different evaluation measures. In these latter studies, we do not find any evidence of gender bias in evaluations. We discuss our findings in the higher education context and make recommendations to mitigate gender bias in teaching evaluations.

Suggested Citation

  • Nigel Burnell & Irina Cojuharenco & Zahra Murad, 2020. "He Taught, She Taught: The effect of teaching style, academic credentials, bias awareness and academic discipline on gender bias in teaching evaluations," Working Papers in Economics & Finance 2020-05, University of Portsmouth, Portsmouth Business School, Economics and Finance Subject Group.
    • Handle: RePEc:pbs:ecofin:2020-05
    as

    Download full text from publisher

    File URL: http://repec.port.ac.uk/EconFinance/PBSEconFin_2020_05.pdf
    File Function: Full text
    Download Restriction: no

    References listed on IDEAS

    as
    1. Scott E. Carrell & Marianne E. Page & James E. West, 2010. "Sex and Science: How Professor Gender Perpetuates the Gender Gap," The Quarterly Journal of Economics, Oxford University Press, vol. 125(3), pages 1101-1144.
    2. Darby, Michael R & Karni, Edi, 1973. "Free Competition and the Optimal Amount of Fraud," Journal of Law and Economics, University of Chicago Press, vol. 16(1), pages 67-88, April.
    3. Jonathan Guryan & Kerwin Kofi Charles, 2013. "Taste‐based or Statistical Discrimination: The Economics of Discrimination Returns to its Roots," Economic Journal, Royal Economic Society, vol. 123(11), pages 417-432, November.
    4. Boring, Anne, 2017. "Gender biases in student evaluations of teaching," Journal of Public Economics, Elsevier, vol. 145(C), pages 27-41.
    5. Eric P. Bettinger & Bridget Terry Long, 2005. "Do Faculty Serve as Role Models? The Impact of Instructor Gender on Female Students," American Economic Review, American Economic Association, vol. 95(2), pages 152-157, May.
    6. Berna Tari Kasnakoglu, 2016. "Antecedents and consequences of co-creation in credence-based service contexts," The Service Industries Journal, Taylor & Francis Journals, vol. 36(1-2), pages 1-20, January.
    7. Neilson, William & Ying, Shanshan, 2016. "From taste-based to statistical discrimination," Journal of Economic Behavior & Organization, Elsevier, vol. 129(C), pages 116-128.
    8. Charles Wild & Daniel Berger, 2016. "The proposed Teaching Excellence Framework (TEF) for UK Universities," Proceedings of International Academic Conferences 3505701, International Institute of Social and Economic Sciences.
    9. J. Jobu Babin, 2019. "Detecting Group Gender Stereotypes: Opinion-mining vs. Incentivized Coordination Games," Journal of Economic Insight (formerly the Journal of Economics (MVEA)), Missouri Valley Economic Association, vol. 45(1), pages 21-42.
    10. Friederike Mengel & Jan Sauermann & Ulf Zölitz, 2019. "Gender Bias in Teaching Evaluations," Journal of the European Economic Association, European Economic Association, vol. 17(2), pages 535-566.
    11. Charles Wild & Daniel Berger, 2016. "The proposed Teaching Excellence Framework (TEF) for UK Universities," International Journal of Teaching and Education, International Institute of Social and Economic Sciences, vol. 4(3), pages 33-50, September.
    Full references (including those not matched with items on IDEAS)

    More about this item

    Keywords

    Gender bias; teaching evaluations; teaching style; academic credentials; bias awareness;

    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:pbs:ecofin:2020-05. 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: (Shuonan Zhang). General contact details of provider: http://edirc.repec.org/data/depbsuk.html .

    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 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.

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

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.