Using Conjoint Analysis to Evaluate and Reward Teaching Performance

Abstract

Although widely used, student evaluations of teaching do not address several factors that should be considered in evaluating teaching performance such as new course preparations, teaching larger classes, and inconvenient class times. Consequently, the incentive exists to avoid certain teaching assignments to achieve high SET scores while minimizing workload. This hinders curriculum innovation and development and potentially creates dysfunction in the college. The authors demonstrate how conjoint analysis can be applied to create a model of teaching evaluation that simultaneously considers many aspects of teaching performance and increases fairness in the appraisal process. Findings from a pilot implementation are discussed.

Additional information

Notes on contributors

Donald R. Bacon

Donald R. Bacon (Ph.D., University of Michigan), Professor of Marketing, Daniels College of Business, University of Denver, Denver, CO, [email protected]

Yilong (Eric) Zheng

Yilong (Eric) Zheng (MS, Quantitative Research Methods), Department of Marketing, State University of New York at Binghamton, Binghamton, NY, [email protected]

Kim A. Stewart

Kim A. Stewart (Ph.D., University of Houston), Research Scholar, Daniels College of Business, University of Denver, Denver, CO, [email protected]

Carol J. Johnson

Carol J. Johnson (Ph.D., University of Maryland), Associate Professor and Chair of Marketing, Daniels College of Business, University of Denver, Denver, CO, [email protected]

Pallab Paul

Pallab Paul (Ph.D., University of Arizona), Professor of Marketing, Daniels College of Business, University of Denver, Denver, CO, [email protected]