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Measuring faculty teaching effectiveness using conditional fixed effects

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  • Maia Linask
  • James Monks

Abstract

Using a dataset of 48 faculty members and 88 courses over 26 semesters, the authors estimate Student Evaluation of Teaching (SET) ratings that are conditional on a multitude of course, faculty, and student attributes. They find that ratings are lower for required courses and those where students report a lower prior level of interest. Controlling for these variables substantially alters the SET ratings for many instructors. The average absolute value of the difference between the faculty ratings controlling just for time effects and fully conditional ratings is nearly one-half of a standard deviation in the students’ rating of how much they learned. This difference produces a change in quartile rank for over half the sample across two summary course evaluation measures.

Suggested Citation

  • Maia Linask & James Monks, 2018. "Measuring faculty teaching effectiveness using conditional fixed effects," The Journal of Economic Education, Taylor & Francis Journals, vol. 49(4), pages 324-339, October.
    • Handle: RePEc:taf:jeduce:v:49:y:2018:i:4:p:324-339
    DOI: 10.1080/00220485.2018.1500957
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    Cited by:

    1. Kenneth G. Elzinga & Daniel Q. Harper, 2023. "In‐person versus online instruction: Evidence from principles of economics," Southern Economic Journal, John Wiley & Sons, vol. 90(1), pages 3-30, July.
    2. Cannon, Edmund & Cipriani, Giam Pietro, 2021. "Gender Differences in Student Evaluations of Teaching: Identification and Consequences," IZA Discussion Papers 14387, Institute of Labor Economics (IZA).

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