Examining relationships among teacher professional learning and associated teacher and student outcomes in math and science: A meta-analytic approach to mediation and moderation

检查教师专业学习与数学和科学方面相关教师和学生成果之间的关系：调解和调节的元分析方法

• 批准号: 2300544
• 负责人: Ryan Williams
• 金额: $ 130.97万
• 依托单位: American Institutes for Research in the Behavioral Sciences
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-09-01 至 2026-08-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2300544&HistoricalAwards=false
• 关键词: Examining; relationships; among; teacher; professional

This research synthesis study reviews the effects of professional learning interventions and will advance STEM educators' understanding of the critically important relationships among teacher professional learning (PL), teacher knowledge and practice, and average student effects. Understanding these relationships will allow the field to design better PL experiences for teachers that truly benefit student learning. The project leverages the availability of causal impact studies in the primary literature and advancements in meta-analytic techniques to uncover relationships among PL features, teacher knowledge and practice, and student outcomes in a manner that has not been done before. To ensure that the research is as useful as possible to other researchers, the team will publicly share our data and analysis scripts, allowing other meta-analysts to build on our efforts. In addition, the researchers will generate web-based data analysis tools for other primary researchers to use to examine the data from the study, conduct a priori power analyses, and to help primary researchers better interpret findings in the context of research that has already been done. This synthesis research uses meta-analysis to study the effects from studies of PL interventions with math and science student and teacher outcomes. The research team uses meta-regression with robust variance estimation as well as meta-analytic structural equation modeling. Broader impacts are addressed as the data and analyses tools can be used by many communities of researchers, higher education faculty, and policy makers. The communities include teacher educators, education researchers, district PL providers, STEM education policy makers, along with math and science teachers and students.This research project is supported by NSF's EHR Core Research (ECR) program. The ECR program emphasizes fundamental STEM education research that generates foundational knowledge in the field. Investments are made in critical areas that are essential, broad, and enduring: STEM learning and STEM learning environments, broadening participation in STEM, and STEM workforce development. The program supports the accumulation of robust evidence to inform efforts to understand, build theory to explain, and suggest intervention and innovations to address persistent challenges in STEM interest, education, learning and participation. The project is also funded by the Discovery Research preK-12 program (DRK-12), which seeks to significantly enhance the learning and teaching of science, technology, engineering and mathematics (STEM) by preK-12 students and teachers, through research and development of innovative resources, models and tools. Projects in the DRK-12 program build on fundamental research in STEM education and prior research and development efforts that provide theoretical and empirical justification for proposed projects. 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.

这项研究综合研究回顾了专业学习干预的效果，并将促进 STEM 教育工作者对教师专业学习 (PL)、教师知识和实践以及平均学生效果之间关键关系的理解。了解这些关系将使该领域能够更好地设计。为教师提供真正有益于学生学习的 PL 体验。该项目利用原始文献中因果影响研究的可用性和元分析技术的进步，以一种有利于学生学习的方式揭示 PL 特征、教师知识和实践以及学生成绩之间的关系。以确保之前未进行过研究。为了尽可能对其他研究人员有用，该团队将公开共享我们的数据和分析脚本，允许其他元分析师以我们的努力为基础。此外，研究人员还将生成基于网络的数据分析工具，供其他主要研究人员使用。检查研究数据，进行先验功效分析，并帮助初级研究人员在已经完成的研究背景下更好地解释研究结果。这项综合研究使用荟萃分析来研究 PL 干预研究的影响。研究小组使用科学学生和教师的成果。具有稳健方差估计的元回归以及元分析结构方程模型可以解决更广泛的影响，因为数据和分析工具可以被许多研究人员、高等教育教师和政策制定者使用。教育研究人员、地区 PL 提供者、STEM 教育政策制定者以及数学和科学教师和学生。该研究项目由 NSF 的 EHR 核心研究 (ECR) 计划支持，ECR 计划强调基础 STEM 教育研究，以产生基础知识。领域.投资是在重要、广泛和持久的关键领域进行的：STEM 学习和 STEM 学习环境、扩大 STEM 的参与以及 STEM 劳动力发展。该计划支持积累强有力的证据，为理解、建立理论来解释、并提出干预和创新措施，以解决 STEM 兴趣、教育、学习和参与方面持续存在的挑战。该项目还得到 Discovery Research preK-12 计划 (DRK-12) 的资助，该计划旨在显着加强科学的学习和教学，技术、工程和数学(STEM) 由 preK-12 学生和教师通过 DRK-12 计划中的创新资源、模型和工具的研究和开发，以 STEM 教育的基础研究和先前的研究和开发工作为基础，为 STEM 教育提供理论和实证依据。该奖项反映了 NSF 的法定使命，并通过使用基金会的智力价值和更广泛的影响审查标准进行评估，被认为值得支持。