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Collaborative Research: Innovating Quantum-Inspired Learning for Undergraduates in Research and Engineering

Collaborative Research: Innovating Quantum-Inspired Learning for Undergraduates in Research and Engineering
协作研究:为研究和工程本科生创新量子启发学习
批准号:
2142248
负责人:
Chris Kim
金额:
$75.0万
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 2027-08-31

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中文摘要
翻译
该项目旨在通过为STEM本科生开发具有体验式学习的量子信息科学与技术课程来服务于国家利益。新兴的量子技术有望以非传统的方式和信息安全为计算、通信、网络和传感带来革命性的变化。这就产生了对能够在STEM劳动力中应用量子科学和技术原理的新一代工程师、科学家和程序员的需求。量子技术的多学科性质给为来自不同学位项目的学生提供全面教育带来了挑战,这些学生可能在某些领域缺乏技术背景。该项目旨在降低学生的入学门槛,开发可转移的量子计算和工程技能,产生关于在这一多学科领域进行创造性教学和有效学生学习的条件的知识,并为学生进入这一迅速崛起的领域做好准备。该项目的成功将导致大量的工程和理科本科生具备基本的量子知识和技能,以及适合其他院校本科生的新的量子教育计划。该项目的总体目标是促进来自多个STEM学科的本科生学习量子信息科学与技术的学习过程的知识,进而开发新的在线模块和可扩展的学习范式,以有效地教授量子基础。范围包括软件和硬件两个方面,并涵盖相关的工程和科学学科。项目团队计划研究量子科学和工程的技术和认知进入障碍,创建用于教授量子基础的模块,开发体验式学习工具,并将新工具和模块无缝集成到现有的本科工程课程中。研究小组将调查改善学生学习量子科学和工程的条件,并进一步研究创建的工具和方法的有效性。在这个项目中开发的新的量子工程学习平台和课程应该会在这个新兴的技术前沿推动工程和科学教育以及劳动力发展。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 developing a quantum information science and technology curriculum with experiential learning for undergraduate STEM students. Emerging quantum technologies promise to revolutionize computing, communication, networking, and sensing in unconventional ways and with information security. This has created a need for a new generation of engineers, scientists, and programmers who can apply quantum science and technology principles in the STEM workforce. The multidisciplinary nature of quantum technologies poses challenges to providing a comprehensive education for students from different degree programs who may lack the technical background in some areas. This project aims to lower entry barriers for students, to develop transferable skillsets for quantum computing and engineering, to generate knowledge about conditions for creative teaching and effective student learning in this multidisciplinary field, and to prepare students for entering this rapidly emerging field. The success of this project should lead to large numbers of undergraduate engineering and science students equipped with essential quantum knowledge and skills and a new quantum education program adaptable for undergraduate STEM students at other institutions.The overarching goal of this project is to advance knowledge of the learning process for undergraduate students from multiple STEM disciplines in studying quantum information science and technology, and then to develop new online modules and a scalable learning paradigm for effectively teaching quantum fundamentals. The scope includes both software and hardware aspects and encompasses related engineering and science disciplines. The project team plans to study the technical and cognitive entry barriers to quantum science and engineering, create modules for teaching quantum fundamentals, develop experiential learning tools, and seamlessly integrate new tools and modules into existing undergraduate engineering curricula. The research team will investigate the conditions under which improved student learning of quantum science and engineering occurs and further study the effectiveness of the created tools and approaches. The new quantum engineering learning platform and curriculum developed in this project should advance engineering and science education and workforce development in this emerging technology frontier. 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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ASCENT: TUNA: TUnable randomness for NAtural computing
  • 批准号:
    2230963
  • 项目类别:
    Standard Grant
  • 资助金额:
    $150.0万
  • 财政年份:
    2022
  • 负责人:
    Chris Kim
  • 依托单位:
SHF: Medium: Time Based Deep Neural Networks: An Integrated Hardware-Software Approach
  • 批准号:
    1763761
  • 项目类别:
    Continuing Grant
  • 资助金额:
    $90.0万
  • 财政年份:
    2018
  • 负责人:
    Chris Kim
  • 依托单位:
Collaborative Research: Feedback-Driven Resiliency for Near-Threshold Systems
  • 批准号:
    1255937
  • 项目类别:
    Continuing Grant
  • 资助金额:
    $9.6万
  • 财政年份:
    2013
  • 负责人:
    Chris Kim
  • 依托单位:
A Sub-2V Printed Flexible Organic RFID System Design for Long Range Communication
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:
    SATOSHI NAWATA
  • 依托单位:
Cell Research
Cell Research
Cell Research (细胞研究)