The Harriet W. Sheridan Center for Teaching and Learning

Interpretation of Course Feedback

Review guidance for instructors on interpreting the data offered by Brown’s course feedback system.

Brown uses EvaluationKit, an online course feedback system. While the system is housed in the College, the Sheridan Center provides  guidance for instructors and department personnel on how to review and interpret the feedback collected by the system.

References

Arreola, R.A. (2007). Developing a comprehensive evaluation system: A guide to designing, building, and operating large-scale faculty evaluation systems, 3rd ed. San Francisco: Anker.

Basow, S.A., & Martin, J.L. (2012). Bias in student evaluations. In M.E. Kite, Ed. Effective evaluation of teaching: A guide for faculty and administrators (pp. 40-49). Society for the Teaching of Psychology. Available: http://teachpsych.org/ebooks/evals2012/index.php

Bauer, C.C., & Baltes, B.B. (2002). Reducing the effects of gender stereotypes on performance evaluations. Sex Roles, 47(9/10): 465-476.

Benton, S. L., & Cashin, W. E. (2012). Student ratings of teaching: A summary of research and literature (IDEA Paper no. 50). Manhattan, KS: The IDEA Center. Retrieved from https://ideaedu.org/wpcontent/uploads/2014/11/idea-paper_50.pdf

Cohen, P. A. (1980). Effectiveness of student-rating feedback for improving college teaching: A meta-analysis of findings. Research in Higher Education, 13: 321-341.

Dewar, J. (2017). Student evaluations ratings of teaching: What every instructor should know. American Mathematical Society. Available: https://blogs.ams.org/matheducation/2017/04/17/student-evaluations-ratin...

Feldman, K.A. (2007). Identifying exemplary teachers and teaching: Evidence from student ratings. In R.P. Perry and J.C. Smart, Eds. The scholarship of teaching and learning in higher education: An evidence-based perspective (pp. 93-). Springer.

Finelli, C. J., Ott, M., Gottfried, A.C., Hershock, C., O’Neal, C., & Kaplan, M. (2008). Utilizing instructional consultations to enhance the teaching performance of engineering faculty. Journal of Engineering Education: 397-411. 

Franklin, J. (2001). Interpreting the numbers: Using a narrative to help others read student ratings of your teaching accurately. New Directions for Teaching and Learning, 87: 85-100.

Goos, M., & Salomons, A. (2017). Measuring teaching quality in higher education:  Assessing selection bias in higher education. Research in Higher Education, 58: 341-364.

Linse, A. (2016). Interpreting and using student ratings data: Guidance for faculty serving as administrators and on evaluation committees. Studies in Educational Evaluation, 54: 94-106.

Marsh, H.W. (2007). Students’ evaluations of university teaching: Dimensionality, reliability, validity, potential biases and usefulness. In R.P. Perry and J.C. Smart, Eds. The scholarship of teaching and learning in higher education: An evidence-based perspective (pp. 319-). Springer.

Mengel, F., Sauermann, J., Zölitz, U. (2017, September). Gender bias in teaching evaluations. IZA Institute of Labor Economics Discussion Paper Series. 

Murray, H. (2007). Low-inference teaching behaviors and college teaching effectiveness: Recent developments and controversies. In R.P. Perry and J.C. Smart, Eds. The scholarship of teaching and learning in higher education: An evidence-based perspective (pp. 145-183). Springer.

Ory, J.C. (2006, July). Getting the most out of your student ratings. Association for Psychological Science.

Penny, A. R., & Coe, R. (2004). Effectiveness of consultation on student ratings feedback: A meta-analysis. Review of Educational Research, 74(2): 215-253.

Theall, M., & Arreola, R.A. (2006). The meta-profession of teaching. Thriving in Academe, 22(5): 5-7. 

Yale College Teaching and Learning Committee. (2016). Report of the Teaching and Learning Committee, 2015-16: Recommendations to revise the Yale College online course evaluation survey. (unpublished report). New Haven, CT.