Exploring the Impact of Observation Protocol Data in Changing Instructor Motivation and Practice

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This project aims to serve the national interest by establishing how instructors use classroom observation data to change their teaching practices. Traditionally, teaching and learning centers (TLCs) have used unstructured or informal classroom observation protocols to assess university teaching. However, many evidence-based structured observation protocols have been developed to understand and measure components of teaching and classroom activities. This project intends to advance understanding of how university instructors use data from structured and unstructured protocols to inform their teaching. To this end, the project will provide 48 instructors with classroom observations focused on evidence-based teaching practices, including active learning; a comparable group of 12 instructors will receive the results of traditional unstructured observations. The instructors span two institutions, the University of California San Diego and University of California Riverside, and will represent various STEM disciplines. As a result, the project plans to investigate multiple contexts for the impact of examining classroom observation data on instructor motivation and change in teaching practices. The project hopes to generate new knowledge about how instructors interpret observation data, which could result in more efficient and effective faculty professional development and benefit student learning. The goals of this project are to 1) identify how college STEM instructors make sense of classroom observation data, 2) measure the extent to which interacting with their own classroom observation data affects instructor motivation to change their teaching practices, and 3) establish the extent to which instructors use observation data to change their teaching. Data from four structured observation protocols and one informal protocol will be collected and shared from each instructor’s course. The project will study the efficacy of this approach through data collected from surveys, interviews, and classroom observations to explore changes in teaching practices and conceptions of teaching. These data will allow the project team to identify best practices for sharing observation data with instructors. A mixed methods approach with quantitative and qualitative data will allow for comparisons across instructional contexts and capture nuanced changes in teaching and motivation. The NSF IUSE: EHR program supports research and development projects to improve the effectiveness of STEM education for all students. Through its Institutional and Community Transformation track, the program supports efforts to transform and improve STEM education across institutions of higher education and disciplinary communities.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.