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

探索观察协议数据对改变教师动机和实践的影响

• 批准号: 2236327
• 负责人: Richard Edwards
• 金额: $ 99.5万
• 依托单位: University of California-Riverside
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-06-01 至 2028-05-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2236327&HistoricalAwards=false
• 关键词: Exploring; Impact; Observation; Protocol; Data

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.

该项目旨在通过建立讲师如何使用课堂观察数据来改变其教学实践来服务国家利益。传统上，教学中心（TLC）使用非结构化或非正式的课堂观察方案来评估大学教学。但是，已经制定了许多基于证据的结构化观察方案，以理解和衡量教学和课堂活动的组成部分。该项目旨在促进对大学讲师如何使用结构化和非结构化协议中的数据来告知他们的教学的数据。为此，该项目将为48位讲师提供专注于循证教学实践的课堂观察，包括积极学习；一个可比的12名讲师将获得传统的非结构化观察结果。讲师跨越了两个机构，即加利福尼亚大学圣地亚哥大学和加利福尼亚大学河滨分校，并将代表各种STEM学科。结果，该项目计划调查多种环境，以检查有关教师动机和教学实践变化的课堂观察数据的影响。该项目希望产生有关讲师如何解释观察数据的新知识，这可能会导致更高效，有效的教师发展并受益于学生学习。该项目的目标是1）确定大学STEM讲师如何理解课堂观察数据，2）衡量与自己的课堂观察数据相互作用的程度会影响教师改变其教学实践的动机，3）确定讲师使用观察数据改变教学的程度。将从每个讲师的课程中收集和共享四个结构化观察协议和一个非正式协议的数据。该项目将通过从调查，访谈和课堂观察中收集的数据来研究这种方法的效率，以探索教学实践和教学概念的变化。这些数据将使项目团队能够确定与讲师共享观察数据的最佳实践。具有定量和定性数据的混合方法方法将允许在教学环境中进行比较，并捕捉教学和动机的细微变化。 NSF IUSE：EHR计划支持研发项目，以提高所有学生STEM教育的有效性。该计划通过其机构和社区转型轨道，支持努力在高等教育和纪律社区的机构中转变和改善STEM教育。该奖项反映了NSF的法定任务，并被认为是值得通过基金会的知识分子优点和更广泛影响的评估来评估值得支持的。