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Collaborative Research: A Virtual and Active Learning Approach to Digital Manufacturing Education for the Future of Manufacturing Workforce

Collaborative Research: A Virtual and Active Learning Approach to Digital Manufacturing Education for the Future of Manufacturing Workforce
协作研究:面向制造业劳动力未来的数字化制造教育的虚拟主动学习方法
批准号:
2142051
负责人:
Christopher Saldana
金额:
$25.5万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2022
资助国家:
美国
项目状态:
未结题
起止时间:
2022-09-01 至 2025-08-31

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中文摘要
翻译
该项目旨在通过调查虚拟和主动学习方法在数字制造本科教育中的使用来服务于国家利益。虚拟学习可以让那些由于经济限制、全职工作、残疾或移民等许多情况而无法出现在实体校园的人参与进来。面向工科本科生的数字制造教学,无论是在虚拟学习环境中还是在面对面的学习环境中,都对国内外制造业的未来至关重要。该项目的重点将是开发有效的方法,通过数字技术,特别是通过使用嵌入式系统、大数据及其使用迅速成熟的云计算平台进行集成,来教育学生在制造业生产率方面取得革命性的进步。该项目旨在了解虚拟学习如何影响学生理解和保留数字制造中的核心概念的能力,以及如何在数字制造的完全虚拟学习环境中部署积极的学习体验。为了实现这一目标,将在虚拟学习环境中部署数字制造课程,使用传统教学和主动学习活动相结合的方式,以提高学生的参与度、核心概念的保持和自我效能。佐治亚理工学院将为虚拟学习环境开发和迭代部署一门新的本科数字制造课程,其中包括主动学习方法。将设计和试点不同类型的基于虚拟的制造业实践学习体验,包括用于网络制造的嵌入式系统的虚拟培训模拟器。课程材料将分发给伙伴组织和机构,以便在全国范围内广泛部署。最后,项目组将评估通过虚拟主动学习环境促进数字制造基本概念学习的材料。这一统一的努力将推动应用于制造系统的数字技术领域的教育创新。通过实现这种培训的虚拟交付,更多的学生将能够获得机会,更深入地了解数字制造理论,并在毕业后成为未来制造业劳动力中更强大的一员。NSF IUSE:EHR计划支持研究和开发项目,以提高所有学生的STEM教育的有效性。通过参与的学生学习路径,该计划支持有前景的实践和工具的创建、探索和实施。该奖项反映了NSF的法定使命,并通过使用基金会的智力优势和更广泛的影响审查标准进行评估,被认为值得支持。
英文摘要
This project aims to serve the national interest by investigating the use of virtual and active learning approaches in undergraduate education in digital manufacturing. Virtual learning can enable participation for those who may not be able to be present on a physical campus, due to financial restrictions, full-time employment, disability, or immigration, among many other circumstances. Teaching of digital manufacturing for undergraduate engineering students, whether in virtual or in-person learning environments, is critical to the future of manufacturing domestically and abroad. The focus of the project will be on developing effective approaches for educating students about transformative advances in manufacturing productivity through digital technologies, particularly through use of embedded systems, big data and their integration using rapidly maturing cloud computing platforms.The project seeks to understand how virtual learning affects student ability to understand and retain core concepts in digital manufacturing and how active learning experiences can be deployed in fully virtual learning environments for digital manufacturing. To accomplish this, a digital manufacturing course will be deployed in a virtual learning environment using a mixture of traditional lecture and active learning activities in order to improve student engagement, retention of core concepts, and self-efficacy. A new undergraduate digital manufacturing course for virtual learning environments will be developed and iteratively deployed at Georgia Tech incorporating active learning approaches. Different types of virtual-based, hands-on learning experiences for manufacturing will be designed and piloted, including virtual training simulators for embedded systems for cybermanufacturing. Course materials will be disseminated to partner organizations and institutions for broad deployment nationally. Finally, the project team will evaluate materials for facilitating learning of concepts fundamental to digital manufacturing through virtual active learning environments. This unified effort will drive educational innovation in the domain of digital technologies applied to manufacturing systems. By enabling virtual delivery of this training, more students will be able to access opportunities to understand digital manufacturing theory more deeply and will become stronger members of the future manufacturing workforce when they graduate. The NSF IUSE: EHR Program supports research and development projects to improve the effectiveness of STEM education for all students. Through the Engaged Student Learning track, the program supports the creation, exploration, and implementation of promising practices and tools.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.
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IUCRC Planning Grant: Georgia Tech: Center for Digital Factory Innovations (CDFI)
  • 批准号:
    2113821
  • 项目类别:
    Standard Grant
  • 资助金额:
    $2.0万
  • 财政年份:
    2021
  • 负责人:
    Christopher Saldana
  • 依托单位:
Collaborative Research: Hybrid-Compatible Deformation Processing of Performance Critical Components
  • 批准号:
    1825640
  • 项目类别:
    Standard Grant
  • 资助金额:
    $21.47万
  • 财政年份:
    2018
  • 负责人:
    Christopher Saldana
  • 依托单位:
Collaborative Research: Deformation Phenomena in Surface Texturing by Machining-Based Processes
  • 批准号:
    1465158
  • 项目类别:
    Standard Grant
  • 资助金额:
    $6.22万
  • 财政年份:
    2014
  • 负责人:
    Christopher Saldana
  • 依托单位:
CAREER: Deformation-Based Surface Generation for Microstructure Control
  • 批准号:
    1464853
  • 项目类别:
    Standard Grant
  • 资助金额:
    $39.71万
  • 财政年份:
    2014
  • 负责人:
    Christopher Saldana
  • 依托单位:
国内基金
海外基金
Research on Quantum Field Theory without a Lagrangian Description
  • 批准号:
    24ZR1403900
  • 项目类别:
    省市级项目
  • 资助金额:
    --
  • 批准年份:
    2024
  • 负责人:
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  • 依托单位:
Cell Research
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