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

协作研究（EAGER）：促进工程教育变革性研究的数据生态系统

• 批准号: 1306373
• 负责人: Aditya Johri
• 金额: $ 15万
• 依托单位: Virginia Polytechnic Institute and State University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-01-01 至 2014-01-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1306373&HistoricalAwards=false
• 关键词: Collaborative; Research; EAGER; Data; Ecosystem; Collaborative; Research; EAGER; Data; Ecosystem

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.

工程教育研究（EER）社区的任务是改善其寿命的工程师的教育。现在要求从事联邦资助项目的研究人员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数据。这种透明度的驱动力既具有对研究结果的问责制和验证性的需求，又具有其起源，并且认识到数据共享能力的进步对于进行变革性研究并影响潜在受众的领域至关重要。尽管数据管理和共享被认为是有利的，但尚未对EER研究人员中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，并为社区创建核心知识库，并最终创建大型数据集，从而使学生和父母的其他决策者对行政人员和政策制定者受益。跨项目共享数据更有可能提供代表性的图片以及发现结果的上下文变化，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。这个急切的项目将为EER社区开发一个数据生态系统，并将两个主要领域（工程教育和数据共享网络基础设施（即“大数据”））汇总在一起，这些领域尚未得到资助。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中存在数据创建，交流和使用的文化； （b）确定有希望的可用数据共享机制的收集，以播种初始开发工作，并为采用确定机制提供指南。我们将通过访谈和焦点小组（n = 100）和调查（n = 300）收集数据，并与研究界的代表性样本一起收集。我们将通过二级数据收集并针对大规模努力来补充这些工作。然后，我们将检查当前现有的数据共享机制，这些机制可以由EER社区使用。这项工作的最终产品将是改善数据共享的指南，包括设计要求，现有机制分析以及网络基础设施的初始框架，以支持此类活动。这项研究将使整个工程教育社区受益，通过提供共享数据的数据来反映社区驱动的优先事项，最佳实践，最佳实践，设计原理，并以数据为基础进行数据工程工程进行工程研究。该项目可能会影响数百名从事工程教育研究和教学的学生。该项目具有广泛的包容性，目的是使来自各种背景的各种机构的利益相关者参与其中。用于数据共享的基础架构有可能注入知识的共享和使用方式的根本观点变化，从长远来看，我们希望该项目弥合研究人员和从业者的社区。