DOI
10.1080/00220485.2018.1500957
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.
Document Type
Post-print Article
Publication Date
2018
Publisher Statement
Copyright © 2018 Routledge Journals, Taylor & Francis Ltd. Article first published online: October 2018.
DOI: 10.1080/00220485.2018.1500957
The definitive version is available at:
https://www.tandfonline.com/doi/full/10.1080/00220485.2018.1500957
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Full citation:
Linask, Maia and James Monks. "Measuring Faculty Teaching Effectiveness using Conditional Fixed Effects." Journal of Economic Education 49, no. 4 (2018): 324-339. https://www.tandfonline.com/doi/full/10.1080/00220485.2018.1500957
Recommended Citation
Linask, Maia K. and Monks, James, "Measuring Faculty Teaching Effectiveness Using Conditional Fixed Effects" (2018). Economics Faculty Publications. 62.
https://scholarship.richmond.edu/economics-faculty-publications/62