Collaborative Research: Modern Meta-Analysis Research Institute

合作研究：现代荟萃分析研究所

• 批准号: 2321032
• 负责人: Joshua Polanin
• 金额: $ 35.98万
• 依托单位: American Institutes for Research in the Behavioral Sciences
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-10-01 至 2026-09-30
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2321032&HistoricalAwards=false
• 关键词: Collaborative; Research; Modern; Meta; Analysis

Improving the education of America’s youth in the disciplines of science, technology, engineering, and mathematics (STEM) is a well-documented, widely endorsed federal policy priority. Several public and private initiatives have emerged to address this economic reality, including developing more rigorous standards, curricula, and assessments for prekindergarten through grade 12 education in science and mathematics. Addressing this problem requires a multi-pronged approach. The first part of this approach is to examine the extensive number of STEM education interventions that have been developed and evaluated in recent decades. It is important to understand which interventions work, for whom, and under what conditions. Modern meta-analytic methods can examine intervention impacts on learning outcomes and explore how intervention effects vary across studies. This project seeks to deliver a 9-month-long training Institute, with online preworkshop activities, 5 days of an in-person, intensive workshop, and multiple postworkshop opportunities as participants develop a STEM education research meta-analysis project. Through this schedule of activities, the project aims to improve the methodological skill sets of STEM education researchers for conducting modern meta-analyses, resulting in a richer understanding of how STEM education interventions affect learning outcomes. This project will enable participants to conduct meta-analyses that explore which STEM interventions work, for whom, and under what conditions through methods to explore effect size heterogeneity. The Institute will support participants to develop meta-analysis research questions aimed at heterogeneity, to expand their skills for using modern meta-analytic software applications including MetaReviewer and R, to conduct meta-analytic analyses that explore and interpret heterogeneity in effect sizes using meta-regression models, and to interpret and communicate the results of a meta-analysis appropriately. Pre-Institute workshop activities will familiarize participants with the steps of a systematic review and the use of R for statistical analysis. The five-day in-person workshop will focus on how to conduct the preliminary stages of a systematic review and meta-analysis, drawing on the experiences of the instructor team in conducting large-scale reviews. The workshop schedule will also devote significant time to teaching the use of R programs to conduct meta-analysis and meta-regression, with methods to explore effect heterogeneity across studies. The Institute aims to provide participants with the knowledge and skills necessary to lead and conduct basic meta-analyses and to critically evaluate published meta-analyses in the context of STEM education research. The project is supported by NSF's EDU Core Research Building Capacity in STEM Education Research (ECR: BCSER) program, which is designed to build investigators’ capacity to carry out high-quality STEM education research.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.

在科学，技术，工程和数学学科（STEM）方面，改善美国青年的教育是一个有据可查的，广泛认可的联邦政策优先事项。已经出现了一些公共和私人计划来解决这一经济现实，包括通过科学和数学的12年级教育制定更严格的标准，课程和评估。解决此问题需要多管齐全的方法。这种方法的第一部分是检查近几十年来已经开发和评估的大量STEM教育干预措施。重要的是要了解哪些干预措施有效，在哪些条件下以及在哪些条件下。现代的荟萃分析方法可以检查干预对学习结果的影响，并探讨干预措施在研究中的影响如何变化。该项目旨在提供一个为期9个月的培训学院，通过在线前工厂活动，5天的面对面，密集的研讨会以及多个邮政工作坊的机会，因为参与者开发了STEM教育研究Meta-Analyses项目。通过这项活动时间表，该项目旨在提高STEM教育研究人员进行现代荟萃分析的方法学技能，从而对STEM教育干预如何影响学习成果有更丰富的了解。该项目将使参与者能够进行荟萃分析，以探讨哪些STEM干预措施有效，在哪些条件下通过方法探索效应大小异质性。该研究所将支持参与者开发旨在异质性的荟萃分析研究问题，以扩大其使用现代元分析软件应用程序的技能，包括元观看器和R在内，以进行元分析分析，以探索和解释使用元回归模型的效应尺寸中的异质性，以解释和交流Meta-Analsy的分析。建立前研讨会活动将使参与者熟悉系统审查的步骤和R进行统计分析。为期五天的面对面研讨会将重点介绍如何进行系统的审查和荟萃分析的初步阶段，并利用讲师团队进行大规模评论的经验。研讨会的时间表还将花费大量时间来教授R程序进行荟萃分析和元回归，并采用探索整个研究的效应异质性的方法。该研究所的目的是为参与者提供领导和进行基本荟萃分析所需的知识和技能，并在STEM教育研究的背景下进行批判性评估已发表的荟萃分析。该项目得到了NSF的EDU核心研究建设在STEM教育研究（ECR：BCSER）计划中的支持，该计划旨在建立研究人员进行高质量STEM教育研究的能力。该奖项反映了NSF的法定任务，并被认为是通过使用基金会的知识分子和更广泛影响的评估来审查Criteria来通过评估来通过评估来支持的。