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Does More Accurate Knowledge of Course Grade Impact Teaching Evaluation?

Author

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  • Donghun Cho

    (Department of Economics Hallym University Gangwon-do, Korea 200-702)

  • Joonmo Cho

    (Department of Economics Sungkyunkwan University Jongno-gu, Seoul, Korea 110-745)

Abstract

Students’ different standards may yield different kinds of bias, such as self-directed (higher than their past performance) bias and peer-directed (higher than their classmates) bias. Utilizing data obtained from a natural experiment where some students were able to see their grades prior to teacher evaluations, and to investigate possible sources of bias, we empirically analyzed the role of information (such as the actual grade students received in their current course and their previous grade point average), and the average grade of the course, on the student evaluation of teaching. Because bias is sensitive to the accuracy of grade information, the randomized data examined in this paper are a valuable source for estimating both self-directed and peer-directed bias. We identify the existence of the two kinds of biases and demonstrate that the influence of peer-directed bias tends to increase after the accurate information on the course grade is revealed.

Suggested Citation

  • Donghun Cho & Joonmo Cho, 2017. "Does More Accurate Knowledge of Course Grade Impact Teaching Evaluation?," Education Finance and Policy, MIT Press, vol. 12(2), pages 224-240, Spring.
    • Handle: RePEc:tpr:edfpol:v:12:y:2017:i:2:p:224-240
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    References listed on IDEAS

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    Cited by:

    1. Wonyoung Baek & Joonmo Cho, 2018. "Identifying the Virtuous Circle of Humanity Education and Post-Graduate Employment: Evidence from a Confucian Country," Sustainability, MDPI, vol. 10(1), pages 1-14, January.
    2. Joonmo Cho & Wonyoung Baek, 2019. "Identifying Factors Affecting the Quality of Teaching in Basic Science Education: Physics, Biological Sciences, Mathematics, and Chemistry," Sustainability, MDPI, vol. 11(14), pages 1-18, July.
    3. Berezvai, Zombor & Lukáts, Gergely Dániel & Molontay, Roland, 2019. "A pénzügyi ösztönzők hatása az egyetemi oktatók osztályozási gyakorlatára [How financially rewarding student evaluation may affect grading behaviour. Evidence from a natural experiment]," Közgazdasági Szemle (Economic Review - monthly of the Hungarian Academy of Sciences), Közgazdasági Szemle Alapítvány (Economic Review Foundation), vol. 0(7), pages 733-750.
    4. Berezvai, Zombor, 2023. "Az érdemjegy torzító hatása a hallgatói véleményezési rendszerekben. Egy természetes kísérlet eredményei [How to reduce the grade bias in student evaluation systems? A natural experiment]," Közgazdasági Szemle (Economic Review - monthly of the Hungarian Academy of Sciences), Közgazdasági Szemle Alapítvány (Economic Review Foundation), vol. 0(7), pages 795-812.

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