EAGER: Collaborative Research: Changing the Paradigm: Developing a Framework for Secondary Analysis of EER Datasets

EAGER：协作研究：改变范式：开发 EER 数据集二次分析框架

基本信息

批准号：
2039871
负责人：
John Morelock
金额：
$ 4.74万
依托单位：
University of Georgia Research Foundation Inc
依托单位国家：
美国
项目类别：
Standard Grant
财政年份：
2021
资助国家：
美国
起止时间：
2021-03-01 至 2024-02-29
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=2039871&HistoricalAwards=false
关键词：
EAGER Collaborative Research Changing Paradigm

项目摘要

To help develop the nation’s engineering workforce, the National Science Foundation has invested substantial public funding in engineering education research over the past twenty years. This investment has helped markedly improve courses and programs at many universities by testing and sharing research-based practices that promote active learning, increase student motivation and engagement, diversify the field, and better prepare students for work. At the same time, the investment has typically focused on researchers collecting new data, resulting in hundreds of data sets that remain underexplored. These existing data sets have significant potential to be analyzed and even combined in new ways to further support large-scale changes in how we recruit, teach, and prepare engineering students for the demands and challenges of the 21st century. Currently, however, engineering education researchers do not have productive and effective ways for sharing and analyzing data beyond the original project. Thus the full potential of these data sets remains untapped. This project will address that gap by developing and promoting a viable approach that will enable researchers to leverage the rich data currently available. In doing so, it will simultaneously improve engineering education nationally and increase the return on investment of public funds. The project will bring experienced researchers together with those just beginning their careers to identify the major roadblocks to sharing and re-using data, develop strategies and practices for overcoming those roadblocks, and conduct a series of test cases that demonstrate how to put those strategies and practices into action. The results will help create a paradigm shift that can move both the study and the practice of engineering education in the U.S. to a new level and spur the kind of sea changes needed to keep the nation’s engineering workforce at the forefront of the global marketplace.Changing the paradigm of single-use data collection is a high-risk proposition that requires actionable, proven practices for effective, ethical data sharing, coupled with sufficient incentives to both share and use existing data. To that end, this proposal draws together a team of experts to overcome substantial obstacles in data sharing and build a framework to guide secondary analysis in engineering education research. In particular, we will bring together established and emerging scholars to deliver a tested framework that outlines methodological best practices for formally and informally sharing data, making data sets public, combining data from different studies, performing secondary analyses of both qualitative and quantitative data, publishing and sharing the results, securing the needed funding, and ensuring that the work is valued in the field. To create this framework, the research team will hold a series of six workshops over two years. In the first year, we will bring highly respected, experienced researchers from institutions across the country together with newer researchers to create the initial framework for data sharing and data re-use. In the second year, we will test and refine that framework on two existing data sets. We will solicit data sets from the wider community, and invite teams of scholars to conduct secondary analysis on those data sets, in conversation with the original researchers. Importantly, in selecting both the data sets and the approaches to secondary analysis, we will emphasize methodological diversity to ensure that the framework is widely applicable. The outcome will be a framework document that will comprise a set of tested guidelines for data sharing and secondary analysis in engineering education research, distributed through both journals and workshops to promote widespread adoption.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.

为了帮助发展国家的工程劳动力，国家科学基金会在过去的二十年中已经在工程教育研究方面投资了大量的公共资金。这项投资通过测试和共享基于研究的实践来促进积极学习，增加学生的动力和参与度，多样化的领域并更好地为学生做好准备，从而有助于改善许多大学的课程和课程。同时，这项投资通常集中在收集新数据的研究人员上，从而导致数百个数据集保持不足。这些现有的数据集具有分析的巨大潜力，甚至以新的方式结合在一起，以进一步支持我们如何招募，教学和准备工程专业学生满足21世纪的需求和挑战的方式。但是，目前，工程教育研究人员没有生产力和有效的方法来共享和分析原始项目以外的数据。这些数据集的全部潜力仍未开发。该项目将通过开发和促进可行的方法来解决这一差距，该方法将使研究人员能够利用当前可用的丰富数据。通过这样做，它将仅在全国范围内改善工程教育，并增加公共资金的投资回报率。该项目将把经验丰富的研究人员与刚刚开始职业生涯的人一起，以确定共享和重新利用数据的主要障碍，制定克服这些障碍的战略和实践，并进行一系列测试案例，以证明如何将这些策略和实践付诸行动。结果将有助于创造一个范式转变，该范式可以将美国的研究和工程教育的实践提升到一个新的水平，并促使将国家的工程劳动力保持在全球市场的最前沿所需的海洋变化，从而使单一利用数据收集的范式更加有效地共享，并有效地分享了一个高风险的提议，并有效地分享了有效的练习，并有效地共享有效的数据。数据。为此，该提案将一组专家团队汇集在一起，以克服数据共享中的重大障碍，并建立一个指导工程教育研究的二级分析的框架。特别是，我们将汇集既定和新兴的学者，以提供经过测试的框架，概述了正式和非正式共享数据的方法论最佳实践，使数据集公开，结合了来自不同研究的数据，对定性和定量数据进行二次分析，发布和共享结果，确保所需的资金并确保该领域的资金，并确保了该领域的重要资金。为了创建这个框架，研究团队将在两年内举办六个研讨会。在第一年，我们将与新的研究人员一起将来自全国机构的备受推崇的，经验丰富的研究人员与新的研究人员一起创建数据共享和数据重新使用的初始框架。在第二年，我们将在两个现有数据集上测试和完善该框架。我们将在与原始研究人员的交谈中征求更广泛社区的数据集，并邀请学者团队对这些数据集进行次要分析。重要的是，在选择数据集和辅助分析方法时，我们将强调方法学多样性，以确保该框架广泛适用。结果将是一份框架文件，该文件将包括一套通过期刊和讲习班分发的数据共享和二级分析的测试指南，以促进采用宽度。该奖项反映了NSF的法定任务，并通过该基金会的知识优点和广泛的范围来评估NSF的法定任务，并以评估的方式被认为是宝贵的。