Collaborative Research (EAGER): Data Ecosystem for Catalyzing Transformative Research in Engineering Education

工程教育研究 (EER) 社区的使命是改善工程师一生的教育。现在，从事联邦资助项目的 EER 研究人员被要求对他们收集的数据的性质逐渐透明，并与其他研究人员共享这些数据。这种对透明度的追求源于对研究结果的问责制和可验证性的需求，以及认识到数据共享能力的进步对于一个领域进行变革性研究和影响潜在受众至关重要。尽管数据管理和共享被认为是有利的，但尚未对 EER 研究人员之间的数据共享实践和能力进行检查。重要的是要了解当前的实践、采用模式和动机，以及与数据相关的未来社区需求，以充分利用数据共享的好处，为社区创建核心知识库，并最终创建大型数据集，使从学生和家长到管理员和政策制定者的其他决策者受益。跨项目共享数据更有可能提供具有代表性的情况以及研究结果的背景变化，导致有用的荟萃分析，并有助于避免重复的研究和政策制定。这个 EAGER 项目将为 EER 社区开发一个数据生态系统，并将工程教育和数据共享网络基础设施（即“大数据”）这两个目前尚未获得资助的主要领域结合在一起。我们提出的工作将 (a) 了解工程教育研究人员以及本研究的消费者社区中存在的数据创建、交换和使用文化； (b) 确定一系列有希望的可用数据共享机制，为初步开发工作奠定基础，并为采用已确定的机制提出指导方针。我们将通过访谈和焦点小组 (N=100) 以及对研究界代表性样本的调查 (N=300) 来收集数据。我们将通过二次数据收集和对大规模工作的有针对性的了解来补充这些努力。然后，我们将检查当前存在且可由 EER 社区使用的数据共享机制。这项工作的最终产品将是改进数据共享的指南，包括设计要求、现有机制的分析以及支持此类活动的网络基础设施的初始框架。这项研究将通过提供反映社区驱动的优先事项、最佳实践和设计原则的数据共享规则，使整个工程教育社区受益，这些原则可以构成工程教育研究数据共享实践和系统的基础。该项目将可能影响数百名从事工程教育研究和教学的教师和学生。该项目具有广泛的包容性，目标是让来自不同机构、不同背景的利益相关者参与进来。数据共享基础设施有可能为知识的共享和使用方式带来根本性的视角变化，从长远来看，我们期望该项目能够在研究人员和从业者社区之间架起桥梁。

The engineering education research (EER) community is engaged in a mission to improve the education of engineers across their lifespan. EER researchers working on federally funded projects are now being asked to become progressively transparent about the nature of data that they collect and to share that data with other researchers. This drive for transparency has its genesis both in the need for accountability and verifiability of research results, as well as the realization that advances in data sharing capabilities are essential for a field to conduct transformative research and to impact potential audiences. Although data management and sharing are seen as advantageous, no examination as yet has been done of data sharing practices and capabilities among EER researchers. It is important to understand current practices, adoption patterns and motivations, as well as future community needs related to data to fully leverage the benefits of data sharing and create a core knowledge base for the community as well as eventual creation of large datasets that can benefit other decision-makers from students and parents to administrators and policy makers. Sharing data across projects is more likely to provide a representative picture as well as contextual variation in findings, lead to useful meta-analyses, and help avoid repetitive research and policy making. This EAGER project will develop a data ecosystem for the EER community and bring together two major areas -- engineering education and data sharing cyberinfrastructure (i.e. "big data") -- that have not been funded together so far. Our proposed work will (a) Understand the culture of data creation, exchange, and use that exists within the community of engineering education researchers as well as the consumers of this research; and (b) Identify a promising collection of available data sharing mechanisms to seed an initial development effort and present guidelines for the uptake of identified mechanisms. We will collect data through interviews and focus groups (N=100) and surveys (N=300) with a representative sample of the research community. We will supplement these efforts with secondary data collection and targeted understanding of large-scale efforts. We will then examine currently existing data sharing mechanisms that exist and can be utilized by the EER community. The final product of this work will be guidelines for improving data sharing including design requirements, analysis of existing mechanisms, and an initial framework for a cyberinfrastructure to support such activities.This research will benefit the entire engineering education community by providing a rubric for sharing data that reflects community-driven priorities, best practices, and design principles that can form the foundation of a data sharing practice and system for engineering education research. This project will potentially impact hundreds of faculty and students engaged in engineering education research and teaching. The project is broadly inclusive with the goal to involve stakeholders from a diverse range of institutions with a variety of backgrounds. An infrastructure for data sharing has the potential to infuse a fundamental perspective change in how knowledge is shared and used and, in the long-term, we expect this project to bridge the communities of researchers and practitioners.