Student evaluations are the most common and often the only method used to evaluate teachers. In these evaluations, which typically occur at the end of every term, students rate their instructors on criteria accepted as constituting exceptional instruction in addition to an overall assessment. This presentation explores factors that influence student evaluations using the teacher ratings data of Brigham Young University from Fall 2001 to Fall 2006. This project uses ordinal regression to model the probability of an instructor receiving a good, average, or poor rating. Student grade, instructor status, class level, student gender, total enrollment, term, GE class status, and college are used as explanatory variables.
College and Department
Physical and Mathematical Sciences; Statistics
BYU ScholarsArchive Citation
Bell, Emily Brooke, "Ordinal Regression to Evaluate Student Ratings Data" (2008). Theses and Dissertations. 1454.
ordinal regression, teacher evaluations