With support from the Association of American Universities (AAU), this work in progress paper shares our development of a system for evaluation of teaching in our engineering school that integrates evidence-based evaluative data from three sources: student course assessments, peer observation, and self-reflection. Existing student course assessments will be modified to focus on observable best practices, rather than on students’ intuitive impressions of the instructor. The student numerical responses to questions about observable best practices will be considered, in aggregate form, during faculty review and promotion. Peer observations will be conducted in accordance with a consistent protocol, which will include guided pre- and post-observation sessions between the observer and observee and questions focused on behavior and teaching rather than on perceptions and content. Self-reflection will be structured to allow for personal reflections as well as public reflections (those shared with promotion and review committees), allowing each instructor to note and report on their progress toward the implementation of best teaching practices.
To design our three evaluative mechanisms (student impressions, peer observations, and self-reflections), we have pulled from existing validated instruments and collections of best practices, such as the Wieman Teaching Practices Inventory (TPI) and the Classroom Observation Protocol for Undergraduate STEM (COPUS). We have been assisted in this work by experts from our center for teaching and learning, AAU, and elsewhere. Further we have adapted a teaching evaluation rubric that we hope may be used to synthesize the information from our three sources.
A pilot of this new system is already underway. We will conduct ongoing evaluation of this pilot en route to a broader implementation of the new system in our school. The instruments and rubrics that we are using will be shared along with the results of our pilot study.
Preferred presentation format: Lightning Talk
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