Author(s):
Need In the past decade, many groups have created structured observation protocols to understand and measure particular components of teaching. Examples of these protocols include the Classroom Observation Protocol for Undergraduate STEM (COPUS), which analyzes activities performed during class; Decibel Analysis for Research in Teaching (DART), which estimates the percentage of time spent in non-lecture; the Classroom Discourse Observation Protocol (CDOP), which analyzes the discourse patterns of classes; and the Protocol for Advancing Inclusive Teaching Efforts (PAITE), which analyzes inclusive teaching practices. Each protocol focuses on a different aspect of teaching, but they all measure some aspect of evidence-based teaching. Although Teaching & Learning Centers (TLCs) have started to use these protocols to support instructor professional development in higher education, it is not clear the extent to which these protocols can help instructors motivate and change their teaching practice. Guiding Questions 1. How do college STEM instructors make sense of classroom observation data?2. To what extent does interacting with their own classroom observation data motivate instructors to change their teaching practices?3. To what extent do instructors use these observation data to change their teaching?Outcomes We anticipate gaining an understanding of how STEM instructors interpret data from four structured teaching observation protocols: COPUS, CDOP, DART, and PAITE. We also anticipate uncovering the impact of receiving classroom observation data from these structured teaching observation protocols, as compared to receiving data solely from unstructured teaching observation protocols, on STEM instructors. We anticipate that exposure to these data might increase their motivation to adopt evidence-based teaching practices and change their actual practice, in both the short and long term. Broader Impacts All of the observation protocols we use quantify, to some extent, the use of evidence-based teaching practices like active learning, student-centered classroom discourse, and inclusive pedagogical techniques. We hope that by better understanding the role structured teaching observation protocols can play in encouraging STEM faculty to improve their teaching practices based on quantifiable data, professional developers and teaching and learning centers can better know how to serve their faculty. That, indirectly, could lead to a better-educated and more diverse scientific workforce.
Coauthors
Lauren Levitt, University of California Riverside, Riverside, CA; Melinda T. Owens, University of California San Diego, San Diego, CA
