课题基金 / 基金详情

Convergence Accelerator Phase I(RAISE): Empowering a Digital Technology Workforce through Alignment and Coordination of Upskilling and Reskilling Opportunities

Convergence Accelerator Phase I(RAISE): Empowering a Digital Technology Workforce through Alignment and Coordination of Upskilling and Reskilling Opportunities
融合加速器第一阶段 (RAISE):通过调整和协调技能提升和再培训机会来增强数字技术劳动力的能力
批准号:
1936894
负责人:
Jennifer Thornton
金额:
$100.0万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2019
资助国家:
美国
项目状态:
已结题
起止时间:
2019-09-01 至 2020-10-31

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中文摘要
翻译
NSF融合加速器支持以团队为基础的多学科努力,解决国家重要性的挑战,并在不久的将来显示出可交付成果的潜力。“融合加速器”第一阶段项目的更广泛影响/潜在利益是增加可负担得起的数字技术(DT)途径的数量,以提高技能/再培训,从而使美国工人能够改善他们的职业生涯,使美国公司能够获得高技能、多样化的人才库。这项工作将研究三个组织如何商业-高等教育论坛、大华盛顿伙伴关系和商业圆桌会议;可以将华盛顿特区、马里兰州和弗吉尼亚州的二十多家雇主和高等教育机构联合起来,开发一种伙伴关系模式,大规模提供新的创新技术提升/再培训途径。这些途径将侧重于提高美国工人在网络安全、云计算、网络/IT和人工智能/机器学习领域的技能,以满足雇主的需求。鉴于技术变革的快速步伐,迫切需要一种模式,将教育和劳动力利益相关者聚集在一起,快速、大规模地开发新的数字技术技能提升/再培训途径。“融合加速器”第一阶段项目将通过协调公司、高等教育机构、第三方教育/培训提供商和STEM专业人员,解决中介组织如何加快数字技术领域技能提升/再培训工作的速度和影响。迄今为止,在这一领域所做的大多数研究都局限于教育政策制定者与实施伙伴之间,或雇员与雇主之间的中介机构。STEM专业人员的DT技能提升/再培训需要更广泛的教育和劳动力利益相关者之间的合作,这可以通过可信任的中介机构进行协调。本研究将考察中介机构?对解决差距和机会的影响;开展相关研究,就如何解决这些差距和机会提出建议;与所有利益攸关方沟通,建立共同的行动框架;支持协调一致的努力和调动资源;建立共享指标并确定成功;并传播关于DT提升技能/再培训工作的合作成果。拟议的努力将产生一个可复制的合作模式,以支持DT快速和大规模地提高技能/再培训。该奖项反映了美国国家科学基金会的法定使命,并通过使用基金会的知识价值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
The NSF Convergence Accelerator supports team-based, multidisciplinary efforts that address challenges of national importance and show potential for deliverables in the near future. The broader impact/ potential benefit of this Convergence Accelerator Phase I project is to increase the number of affordable digital technology (DT) pathways for upskilling/reskilling so American workers can improve their careers and American companies have access to a highly skilled, diverse talent pool. This work will examine how three organizations ― the Business-Higher Education Forum, the Greater Washington Partnership, and the Business Roundtable ― can bring together two dozen employers and higher education institutions in the Washington, D.C., Maryland, and Virginia region to develop a partnership model which will deliver new DT upskilling/reskilling pathways at scale. These pathways will be focused on increasing the skills of American workers in the areas of cybersecurity, cloud computing, networking/IT, and artificial intelligence/machine learning in order to the meet the demands of employers. Given the rapid pace at which technology changes, there is tremendous need for a model that brings together education and workforce stakeholders to develop new DT upskilling/reskilling pathways rapidly and at scale. This Convergence Accelerator Phase I project will address how intermediary organizations can accelerate the speed and impact of upskilling/reskilling efforts in DT by aligning and coordinating companies, higher education institutions, third-party education/training providers, and STEM professionals. The majority of studies done to date in this field are narrowly focused on intermediaries working between education policymakers and implementation partners, or between employees and employers. DT upskilling/reskilling for STEM professionals requires collaboration between a broader group of education and workforce stakeholders, which can be coordinated through trusted intermediaries. This research will examine the intermediaries? effect on: addressing gaps and opportunities; conducting relevant research in order to provide recommendations on how to address these gaps and opportunities; communicating with all stakeholders to create a common framework for action; supporting aligned efforts and mobilizing resources; establishing shared metrics and identifying success; and disseminating the results of the collaboration on DT upskilling/reskilling efforts. The proposed effort will result in a replicable model for collaborations to support DT upskilling/reskilling rapidly and at scale.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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大规模非确定图数据分析及其Multi-Accelerator并行系统架构研究
  • 批准号:
    62002350
  • 项目类别:
    青年科学基金项目
  • 资助金额:
    24.0万元
  • 批准年份:
    2020
  • 负责人:
    张珩
  • 依托单位: