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

基本信息

项目摘要

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,并最终创建可以受益的大型数据集。其他决策者,从学生和家长到管理者和政策制定者。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) 确定一系列有前景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共享数据的标准来使整个工程教育界受益。它反映了社区驱动的优先事项、最佳实践和设计原则,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转变,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。

项目成果

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Aditya Johri其他文献

Representational literacy and participatory learning in large engineering classes using pen-based computing
使用笔式计算在大型工程课程中进行表征素养和参与式学习
Teaching Multidimensional Ethical Decision-Making Through a Role-Play Case Study
通过角色扮演案例研究教授多维道德决策
A Systematic Review of AI Literacy Conceptualization, Constructs, and Implementation and Assessment Efforts (2019-2023)
人工智能素养概念化、构建、实施和评估工作的系统回顾(2019-2023)
  • DOI:
  • 发表时间:
    2024
  • 期刊:
  • 影响因子:
    3.6
  • 作者:
    Omaima Almatrafi;Aditya Johri;Hyuna Lee
  • 通讯作者:
    Hyuna Lee
Learning Analytics in Higher Education
高等教育中的学习分析
  • DOI:
  • 发表时间:
    2017
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Jaime Lester;Carrie Klein;H. Rangwala;Aditya Johri
  • 通讯作者:
    Aditya Johri
Generative Artificial Intelligence in Higher Education: Evidence from an Analysis of Institutional Policies and Guidelines
高等教育中的生成人工智能:来自机构政策和指南分析的证据
  • DOI:
    10.48550/arxiv.2402.01659
  • 发表时间:
    2024-01-12
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Nora McDonald;Aditya Johri;Areej Ali;Aayushi Hingle
  • 通讯作者:
    Aayushi Hingle

Aditya Johri的其他文献

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{{ truncateString('Aditya Johri', 18)}}的其他基金

Education DCL: EAGER: An Embedded Case Study Approach for Broadening Students' Mindset for Ethical and Responsible Cybersecurity
教育 DCL:EAGER:一种嵌入式案例研究方法,用于拓宽学生道德和负责任的网络安全思维
  • 批准号:
    2335636
  • 财政年份:
    2024
  • 资助金额:
    $ 15万
  • 项目类别:
    Standard Grant
EAGER: Impact of Generative Artificial Intelligence (GAI) on Engineering Education Practices
EAGER:生成人工智能 (GAI) 对工程教育实践的影响
  • 批准号:
    2319137
  • 财政年份:
    2023
  • 资助金额:
    $ 15万
  • 项目类别:
    Standard Grant
Workshop: ProVis-EER: Developing Professional Vision into Empirical Practices within Engineering Education Research (EER) though Digital Apprenticeship
研讨会:ProVis-EER:通过数字学徒制将专业愿景发展为工程教育研究 (EER) 中的实证实践
  • 批准号:
    2112775
  • 财政年份:
    2021
  • 资助金额:
    $ 15万
  • 项目类别:
    Standard Grant
Collaborative EAGER: Novel Ethnographic Investigations of Engineering Workplaces to Advance Theory and Research Methods for Preparing the Future Workforce
协作 EAGER:对工程工作场所进行新颖的民族志调查,以推进为未来劳动力做好准备的理论和研究方法
  • 批准号:
    1939105
  • 财政年份:
    2020
  • 资助金额:
    $ 15万
  • 项目类别:
    Standard Grant
Workshop: Building an Inclusive Foundation of Engineering Education Research Scholarship for Future Growth
研讨会:为未来发展建立工程教育研究奖学金的包容性基础
  • 批准号:
    1941186
  • 财政年份:
    2020
  • 资助金额:
    $ 15万
  • 项目类别:
    Standard Grant
Situated Algorithmic Thinking: Preparing the Future Computing Workforce for Ethical Decision-Making through Interactive Case Studies
情境算法思维:通过交互式案例研究为未来的计算劳动力进行道德决策做好准备
  • 批准号:
    1937950
  • 财政年份:
    2020
  • 资助金额:
    $ 15万
  • 项目类别:
    Standard Grant
Deeper Learning of Data Science (DLDS): Studying Real-world Experiences of Engineering Professionals to Prepare the Future Workforce
数据科学深度学习 (DLDS):研究工程专业人员的真实经验,为未来的劳动力做好准备
  • 批准号:
    1712129
  • 财政年份:
    2017
  • 资助金额:
    $ 15万
  • 项目类别:
    Standard Grant
EAGER: Social Media Participation as Indicator of Actors, Awareness, Attitudes, and Activities Related to STEM Education
EAGER:社交媒体参与度作为与 STEM 教育相关的参与者、意识、态度和活动的指标
  • 批准号:
    1707837
  • 财政年份:
    2017
  • 资助金额:
    $ 15万
  • 项目类别:
    Standard Grant
RAPID: Collaborative Research: Technology Adoption during Environmental Jolts: Mobile Phone Use and Digital Services Appropriation during India's Demonetization Crisis
RAPID:合作研究:环境动荡期间的技术采用:印度废钞危机期间的手机使用和数字服务挪用
  • 批准号:
    1733634
  • 财政年份:
    2017
  • 资助金额:
    $ 15万
  • 项目类别:
    Standard Grant
Collaborative Research: Deep Insights Anytime, Anywhere (DIA2) - Central Resource for Characterizing the TUES Portfolio through Interactive Knowledge Mining and Visualizations
协作研究:随时随地深入洞察 (DIA2) - 通过交互式知识挖掘和可视化来表征 TUES 产品组合的中心资源
  • 批准号:
    1444277
  • 财政年份:
    2014
  • 资助金额:
    $ 15万
  • 项目类别:
    Continuing Grant

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