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Student Evaluation of Teaching, Formulation of Grade Expectations, and Instructor Choice: Explorations with Random-Effects Ordered Probability Models

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  • Horacio Matos-Díaz

    (Department of Business Administration, University of Puerto Rico at Bayamón, Parque Industrial Minillas # 170 Carretera 174, Bayamón, Puerto Rico 00959.)

Abstract

This paper explores new angles of the student evaluation of teaching (SET) debate. The SET ratings of 179 full-time professors of the University of Puerto Rico-Bayamón were tracked from 1998–1999 to 2003–2004. Information on the characteristics of professors, students, and courses was analyzed. Two principal findings are documented. First, students’ grade expectations formulation process is significantly influenced by their quality and by the mean and variance of their professors’ historical grade distribution. Second, students’ willingness to take additional courses with a particular professor is directly related to the optimism of their relative expected grades. Thus, professors might be able to increase enrollment in their courses by: (a) increasing the students’ expected grades and (b) promoting the academic environment that would transform students’ pessimistic expectations into optimistic ones.

Suggested Citation

  • Horacio Matos-Díaz, 2012. "Student Evaluation of Teaching, Formulation of Grade Expectations, and Instructor Choice: Explorations with Random-Effects Ordered Probability Models," Eastern Economic Journal, Palgrave Macmillan;Eastern Economic Association, vol. 38(3), pages 296-309.
    • Handle: RePEc:pal:easeco:v:38:y:2012:i:3:p:296-309
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    Cited by:

    1. Angelo Antoci & Irene Brunetti & Pierluigi Sacco & Mauro Sodini, 2021. "Student evaluation of teaching, social influence dynamics, and teachers’ choices: An evolutionary model," Journal of Evolutionary Economics, Springer, vol. 31(1), pages 325-348, January.
    2. Donghun Cho & Joonmo Cho, 2017. "Does More Accurate Knowledge of Course Grade Impact Teaching Evaluation?," Education Finance and Policy, MIT Press, vol. 12(2), pages 224-240, Spring.

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