Effects of the Engagement, Exploration, Explanation, Elaboration, and Evaluation Instructional Model: Systematic Review and Innovation Through New Meta-Analysis Methodology

参与、探索、解释、阐述和评估教学模式的效果：通过新的荟萃分析方法进行系统回顾和创新

• 批准号: 2000672
• 负责人: Joshua Polanin
• 金额: $ 137.81万
• 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: 2020
• 资助国家: 美国
• 起止时间: 2020-10-01 至 2024-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2000672&HistoricalAwards=false
• 关键词: Effects; Engagement; Exploration; Explanation; Elaboration

This project aims to serve the national interest by conducting basic research on the effectiveness of a commonly used teaching approach in K-12 STEM education, as well as by providing a tool that can help others do similar research studies. Specifically, the project will study the effectiveness of the 5E (Engagement, Exploration, Explanation, Elaboration, and Evaluation) model for instruction, which is commonly used in K-12 STEM education to organize instruction within programs, units, and lessons. More than 100 research studies have tested the effects of using the 5E model. However, these published studies differ from one another in content area focus, research methods, and other features. This project will use meta-analysis, a method that can scientifically combine results from many studies even when the studies are not identical. Through meta-analysis, the project will examine how the 5E model affects students’ STEM achievement, including their subject matter knowledge, critical thinking abilities, and scientific inquiry skills. In addition, this project will create a free, open-source tool that will it easier for other researchers to do meta-analysis. Thus, the project is expected to provide information about how science instruction can be improved and also improve the process of conducting meta-analyses.This project’s primary focus is to conduct a systematic review and meta-analysis of studies that evaluate the effectiveness of the 5E instructional model and interventions based directly on the 5E model on students’ STEM achievement outcomes. This project also will create an open-source, user-friendly data extraction and analysis tool specifically created for researchers conducting meta-analyses. The tool will advance the field by automating the codebook to data system process, applying established relational database techniques for data collection, and creating a simple graphical user interface for state-of-the-art meta-analytical techniques using the R platform. The two project activities will be conducted together, with the meta-analysis informing the creation of the meta-analytic tool, and the tool will be used to conduct the meta-analysis. The meta-analysis results will inform the design of STEM interventions (5E-based or otherwise) that have the goal of increasing STEM literacy and workforce outcomes, and the meta-analytic tool will advance the field of systematic review and meta-analysis methodology by providing applied meta-analysts with an open-source, free tool to streamline the meta-analytic process.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.

该项目旨在通过对K-12 STEM教育中常用教学方法的有效性进行基础研究，以及提供一种可以帮助其他人进行类似研究的工具，来服务于国家利益。 具体而言，该项目将研究5E（参与，探索，解释，激励和评估）教学模型的有效性，该模型通常用于K-12 STEM教育，以组织课程，单元和课程内的教学。超过100项研究已经测试了使用5E模型的效果。然而，这些已发表的研究在内容领域的重点，研究方法和其他功能方面彼此不同。该项目将使用荟萃分析，这种方法可以科学地将许多研究的结果联合收割机结合起来，即使这些研究并不相同。 通过元分析，该项目将研究5E模型如何影响学生的STEM成绩，包括他们的主题知识，批判性思维能力和科学探究技能。此外，该项目将创建一个免费的开源工具，使其他研究人员更容易进行荟萃分析。因此，该项目旨在提供关于如何改进科学教学的信息，并改进进行元分析的过程。该项目的主要重点是对评估5E教学模式和直接基于5E模式的干预措施对学生STEM成绩结果的有效性的研究进行系统审查和元分析。该项目还将创建一个开源的，用户友好的数据提取和分析工具，专门为进行元分析的研究人员创建。该工具将通过自动化码本到数据系统过程，应用已建立的关系数据库技术进行数据收集，并使用R平台为最先进的元分析技术创建简单的图形用户界面来推进该领域。这两个项目活动将一起进行，元分析为创建元分析工具提供信息，该工具将用于进行元分析。荟萃分析结果将为STEM干预措施的设计提供信息（基于5E或其他），其目标是提高STEM素养和劳动力成果，而元分析工具将通过为应用元分析师提供开源，免费工具，以简化Meta-该奖项反映了NSF的法定使命，并被认为值得通过使用基金会的智力价值和更广泛的评估来支持。影响审查标准。