CoChat
Sign Up
Cited by 77Evaluation of Teaching PracticesSchool Choice and PerformanceOnline Learning and Analytics

The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.

Do course evaluations truly reflect student learning? Evidence from an objectively graded post-test

Beleche, Trinidad, Fairris, David, Marks, Mindy·2012·Economics of Education Review
DOI 10.1016/j.econedurev.2012.05.001
Open this paper in CoChat — free account

Overview

Integrity signals

Registry

Crossref · 10.1016/j.econedurev.2012.05.001

Cites

1 of 1 references verified0 citation errors · 0 not checkable

Statistics

Recomputing p-values needs the paper’s full text.

Verification

Claims the paper makes

We couldn’t retrieve this paper’s full text, so its claims and self-check weren’t run. The registry and citation checks still apply.

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

Citations

Cites

Flagged first, then by citations

Show all 1 references

Research works printed but not linked: 22

  1. Aigner, 1986, On student evaluation of teaching ability, Journal of Economic Education, 17, 243, 10.2307/1182148 · DOI
  2. Bedard, 2008, Where class size really matters: Class size and student ratings of instructor effectiveness, Economics of Education Review, 27, 253, 10.1016/j.econedurev.2006.08.007 · DOI
  3. Braga, M., Paccagnella, M., & Pellizzari, M. (April 2011). Evaluating students’ evaluations of professors. IZA discussion Paper 5620. · DOI
  4. Carrell, 2010, Does professor quality matter?Evidence from random assignment of students to professors, Journal of Political Economy, 118, 409, 10.1086/653808 · DOI · Paper page
  5. Clayson, 2007, Conceptual and statistical problems of using between-class data in educational research, Journal of Marketing Education, 29, 34, 10.1177/0273475306297383 · DOI
  6. Clayson, 2009, Student evaluations of teaching: Are they related to what students learn? A meta-analysis and review of the literature, Journal of Marketing Education, 31, 16, 10.1177/0273475308324086 · DOI
  7. Cohen, 1981, Student ratings of instruction and student achievement: A meta-analysis of multi-section validity studies, Review of Educational Research, 51, 281, 10.3102/00346543051003281 · DOI
  8. Dowell, 1982, A selective review of the validity of student ratings of teaching, Journal of Higher Education, 53, 51, 10.2307/1981538 · DOI
  9. Felton, J., Koper, P. T., Mitchell, J. B., & Stinson, M. (2006). Attractiveness, easiness, and other issues: Student evaluations of professors on RateMyProfessors.com. SSRN Working Paper. · DOI
  10. Fischer, 2006, Implications of recent research on student evaluations of teaching, The Montana Professor, 17, 11
  11. Franz, 2010, Grade inflation under the threat of students’ nuisance: Theory and evidence, Economics of Education Review, 29, 411, 10.1016/j.econedurev.2009.10.013 · DOI
  12. Grant, 2007, Grades as information, Economics of Education Review, 26, 201, 10.1016/j.econedurev.2005.10.004 · DOI
  13. Greenwald, 1997, Grading leniency is a removable contaminant of student ratings, American Psychologist, 52, 1209, 10.1037/0003-066X.52.11.1209 · DOI
  14. Isely, 2005, Do higher grades lead to favorable student evaluations?, Journal of Economic Education, 36, 29, 10.3200/JECE.36.1.29-42 · DOI
  15. Krautmman, 1999, Grades and student evaluations of teachers, Economics of Education Review, 18, 59, 10.1016/S0272-7757(98)00004-1 · DOI
  16. Langbein, 2008, Management by results: Student evaluation of faculty teaching and the mis-measurement of performance, Economics of Education Review, 27, 417, 10.1023/A:1018738731032 · DOI
  17. Layne, 1999, Electronic versus traditional student ratings of instruction, Research in Higher Education, 40, 221, 10.1016/j.econedurev.2006.12.003 · DOI
  18. Mason, 1995, Student evaluations of faculty: A new procedure for using aggregate measures of performance, Economics of Education Review, 14, 403, 10.1016/0272-7757(95)00016-D · DOI
  19. McPherson, 2006, Determinants of how students evaluate teachers, Journal of Economic Education, 37, 3, 10.3200/JECE.37.1.3-20 · DOI
  20. Palmer, 1978, Leniency, learning and evaluations, Journal of Educational Psychology, 70, 855, 10.1037/0022-0663.70.5.855 · DOI
  21. Weinberg, 2009, Evaluating teaching in higher education. The entity from which ERIC acquires the content, including journal, organization, and conference names, or by means of online submission from the author, Journal of Economic Education, 40, 227, 10.3200/JECE.40.3.227-261 · DOI
  22. Yunker, 2003, Are student evaluations of teaching valid? Evidence from an analytical business core course, Journal of Education for Business, 78, 313, 10.1080/08832320309598619 · DOI

Cited by

Sorted by citations

See all 77

Metadata

Authors
Beleche, T., Fairris, D., & Marks, M.
Affiliations
  • United States Food and Drug Administration (US)
  • University of California, Riverside (US)
Corresponding author
Marks, Mindy
ORCID
Venue
Economics of Education Review
Publisher
Elsevier BV
Published
2012-10
Volume
31
Issue
5
Pages
709-719
ISSN
0272-7757 (ISSN-L)
DOI
10.1016/j.econedurev.2012.05.001
OpenAlex
W2053462556
Cited by
77
References
1
Citations by year
2026: 1 · 2025: 2 · 2024: 4 · 2023: 1 · 2022: 6 · 2021: 5 · 2020: 7 · 2019: 7 · 2018: 9 · 2017: 6 · 2016: 10 · 2015: 9 · 2014: 6 · 2013: 1 · 2012: 2
FWCI
25.06
Type
journal article
Language
en
Open access
closed
Licence
www.elsevier.com/tdm/userlicense/1.0/ (tdm)
Locations
  • Economics of Education Review (publishedVersion)
  • RePEc: Research Papers in Economics (submittedVersion)
Topics
  • Social Sciences › Education › Evaluation of Teaching Practices
  • Social Sciences › Education › School Choice and Performance
  • Physical Sciences › Computer Science › Computer Science Applications › Online Learning and Analytics
Keywords
course evaluation, student learning, learning assessment, post-test, high-stakes testing, student performance

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review