Course evaluations, or student evaluation of teaching (SETs), are a tool widely used to measure teaching effectiveness in higher education and compare it across different courses, teachers, departments, and the institution at large. Course evaluation results can and have been used in a variety of ways including but not limited to individual course improvement, curriculum development, pedagogical development and refinement, promotion and tenure decisions, general education assessment, and accreditation activities.
Student ratings and comments in course evaluations provide a single measure in a constellation of measurements of teaching effectiveness in higher education. As noted by Stephen L. Benton (2018), "effective instructor evaluation is complex and requires the use of multiple measures - formal and informal, traditional and authentic - as part of a balanced evaluation system". Indeed, the student voice in course evaluations is an important piece of this balanced evaluation system alongside self and peer evaluations of teaching effectiveness. It is important to provide a means for students to have a voice and for faculty to remain accountable to their students. It is also important to contextualize end-of-course evaluations of teaching effectiveness. Student ratings and comments provide one source of data. Further, it is the students' perspective at one particular moment in time, at the end of the course. As with other types of data, contextualizing data gathered from students in course evaluations is the keystone for fairly assessing teaching practices at any institution.
In the areas below, we will outline factors to think about when interpreting student evaluation data. We also provide further reading and other relevant resources. We also strongly recommend that review and promotion committees value student ratings and feedback data in light of self-assessment and peer review; taken together, these three areas offer meaningful data and analysis for evaluation. Reviewing the instructor's interpretation of student data - along with the instructor's discussion of instructional contexts, innovations, and classroom evidence - reflects robust best practice.