Published June 3, 2020 | Version v1
Journal article Open

Exploring the personal and professional factors associated with student evaluations of tenure-track faculty

  • 1. Indiana University
  • 2. University of Chicago
  • 3. Université de Montréal

Description

Tenure-track faculty members in the United States are evaluated on their performance in both research and teaching. In spite of accusations of bias and invalidity, student evaluations of teaching have dominated teaching evaluation at U.S. universities. However, studies on the topic have tended to be limited to particular institutional and disciplinary contexts. Moreover, in spite of the idealistic assumption that research and teaching are mutually beneficial, few studies have examined the link between research performance and student evaluations of teaching. In this study, we conduct a large scale exploratory analysis of the factors associated with student evaluations of teachers, controlling for heterogeneous institutional and disciplinary contexts. We source public student evaluations of teaching from RateMyProfessor.com and information regarding career and contemporary research performance indicators from the company Academic Analytics. The factors most associated with higher student ratings were the attractiveness of the faculty and the student's interest in the class; the factors most associated with lower student ratings were course difficulty and whether student comments mentioned an accent or a teaching assistant. Moreover, faculty tended to be rated more highly when they were young, male, White, in the Humanities, and held a rank of full professor. We observed little to no evidence of any relationship, positive or negative, between student evaluations of teaching and research performance. These results shed light on what factors relate to student evaluations of teaching across diverse contexts and contribute to the continuing discussion teaching evaluation and faculty assessment.

Data availability

A minimal, anonymized data-set has been provided containing all values behind the figures and aggregate measures presented in our manuscript. This minimal dataset, along with the code used to produce it from raw data, and to reproduce all figures and tables can be found within the GitHub repository at the following URL: https://github.com/murrayds/aa_rmp. Raw, unprocessed, and non-anonymized data cannot be provided due to ethical considerations and legal restrictions. However, we provide scripts for sampling data from RateMyProfessor.com, should readers wish to sample their own data. Requests for Academic Analytics data can be submitted via their website at https://academicanalytics.com/.

Files

journal.pone.0233515.pdf

Files (5.4 MB)

Name Size Download all
Article
md5:5ef8ace43ff90f7f57f009c87a275688
1.1 MB Preview Download
Supporting information
md5:096d41b1fb1e2ca860bbc16bc5202078
100.2 kB Preview Download
Figures
md5:58966e0d60f532ce1c71f7cd5bf89e70
3.4 MB Preview Download
md5:dc020c807500284912a78838cfb5e8b6
758.2 kB Preview Download

Additional details

Identifiers

DOI
10.1371/journal.pone.0233515
Other
oai:uchicago.tind.io:6272

Funding

National Science Foundation
EAGER: Illuminating the role of science funding on disparities in science

UChicago Information

Division(s)
Social Sciences Division
Department(s)
Sociology