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
基本信息
- 批准号:2300544
- 负责人:
- 金额:$ 130.97万
- 依托单位:
- 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:
- 关键词:
项目摘要
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.
本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至关重要的关系的理解。了解这些关系将使该领域能够为教师设计更好的PL体验,真正有利于学生的学习。该项目利用主要文献中因果影响研究的可用性和元分析技术的进步,以前所未有的方式揭示PL功能,教师知识和实践以及学生成绩之间的关系。为了确保研究对其他研究人员尽可能有用,该团队将公开分享我们的数据和分析脚本,允许其他元分析师在我们的努力基础上再接再厉。此外,研究人员将为其他主要研究人员提供基于网络的数据分析工具,用于检查研究数据,进行先验功率分析,并帮助主要研究人员在已经完成的研究背景下更好地解释研究结果。本综合研究使用元分析来研究PL干预与数学和科学的学生和教师的结果的研究的影响。研究团队使用具有稳健方差估计的元回归以及元分析结构方程建模。更广泛的影响是由于数据和分析工具可以被许多社区的研究人员,高等教育教师和政策制定者使用。这些社区包括教师教育工作者、教育研究人员、地区PL提供者、STEM教育政策制定者沿着数学和科学教师和学生。ECR计划强调基础STEM教育研究,产生该领域的基础知识。投资是在关键领域是必不可少的,广泛的,持久的:干学习和干学习环境,扩大参与干,干劳动力发展。该计划支持积累强有力的证据,为理解,建立理论解释,并建议干预和创新,以解决STEM兴趣,教育,学习和参与方面的持续挑战提供信息。 该项目还得到了Discovery Research preK-12计划(DRK-12)的资助,该计划旨在通过研究和开发创新资源,模型和工具,显着提高preK-12学生和教师对科学,技术,工程和数学(STEM)的学习和教学。DRK-12项目中的项目建立在STEM教育的基础研究以及为拟议项目提供理论和经验依据的先前研究和开发工作的基础上。该奖项反映了NSF的法定使命,并通过使用基金会的知识价值和更广泛的影响审查标准进行评估,被认为值得支持。
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
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Ryan Williams其他文献
Sharp threshold results for computational complexity
计算复杂度的尖锐阈值结果
- DOI:
10.1145/3357713.3384283 - 发表时间:
2020 - 期刊:
- 影响因子:0
- 作者:
Lijie Chen;Ce Jin;Ryan Williams - 通讯作者:
Ryan Williams
Inductive Time-Space Lower Bounds for Sat and Related Problems
Sat 及相关问题的归纳时空下界
- DOI:
10.1007/s00037-007-0221-1 - 发表时间:
2006 - 期刊:
- 影响因子:1.4
- 作者:
Ryan Williams - 通讯作者:
Ryan Williams
Improved Parameterized Algorithms for above Average Constraint Satisfaction
改进的参数化算法可实现高于平均水平的约束满足
- DOI:
- 发表时间:
2011 - 期刊:
- 影响因子:0
- 作者:
Eun Jung Kim;Ryan Williams - 通讯作者:
Ryan Williams
All-pairs bottleneck paths for general graphs in truly sub-cubic time
真正亚立方时间内一般图的全对瓶颈路径
- DOI:
- 发表时间:
2007 - 期刊:
- 影响因子:0
- 作者:
V. V. Williams;Ryan Williams;R. Yuster - 通讯作者:
R. Yuster
Ryan Williams的其他文献
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{{ truncateString('Ryan Williams', 18)}}的其他基金
CAREER: Robots that Plan Interactions, Come and Go, and Build Trust
职业:规划交互、来来去去并建立信任的机器人
- 批准号:
2046770 - 财政年份:2021
- 资助金额:
$ 130.97万 - 项目类别:
Continuing Grant
AF: Small: Lower Bounds in Complexity Theory Via Algorithms
AF:小:通过算法实现复杂性理论的下界
- 批准号:
2127597 - 财政年份:2021
- 资助金额:
$ 130.97万 - 项目类别:
Standard Grant
CPS: Medium: Computation-Aware Autonomy for Timely and Resilient Multi-Agent Systems
CPS:中:及时且有弹性的多代理系统的计算感知自治
- 批准号:
1932074 - 财政年份:2019
- 资助金额:
$ 130.97万 - 项目类别:
Standard Grant
NRI: INT: Balancing Collaboration and Autonomy for Multi-Robot Multi-Human Search and Rescue
NRI:INT:平衡多机器人多人搜索和救援的协作与自主
- 批准号:
1830414 - 财政年份:2018
- 资助金额:
$ 130.97万 - 项目类别:
Standard Grant
CAREER: Common Links in Algorithms and Complexity
职业:算法和复杂性的常见联系
- 批准号:
1741615 - 财政年份:2017
- 资助金额:
$ 130.97万 - 项目类别:
Continuing Grant
CRII: RI: Distributed, Stable and Robust Topology Control: New Methods for Asymmetrically Interacting Multi-Robot Teams
CRII:RI:分布式、稳定和鲁棒的拓扑控制:非对称交互多机器人团队的新方法
- 批准号:
1657235 - 财政年份:2017
- 资助金额:
$ 130.97万 - 项目类别:
Standard Grant
AF:Small:Limitations on Algebraic Methods via Boolean Complexity Theory
AF:Small:布尔复杂性理论对代数方法的限制
- 批准号:
1741638 - 财政年份:2017
- 资助金额:
$ 130.97万 - 项目类别:
Standard Grant
AF:Small:Limitations on Algebraic Methods via Boolean Complexity Theory
AF:Small:布尔复杂性理论对代数方法的限制
- 批准号:
1617580 - 财政年份:2016
- 资助金额:
$ 130.97万 - 项目类别:
Standard Grant
NRI: Coordinated Detection and Tracking of Hazardous Agents with Aerial and Aquatic Robots to Inform Emergency Responders
NRI:与空中和水上机器人协调检测和跟踪危险物质,以通知紧急救援人员
- 批准号:
1637915 - 财政年份:2016
- 资助金额:
$ 130.97万 - 项目类别:
Standard Grant
CAREER: Common Links in Algorithms and Complexity
职业:算法和复杂性的常见联系
- 批准号:
1552651 - 财政年份:2015
- 资助金额:
$ 130.97万 - 项目类别:
Continuing Grant
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