Collaborative Research: IUSE: EDU: Innovative and Inclusive Undergraduate XR Engineering Education to Cultivate Future Metaverse Workforce
合作研究:IUSE:EDU:创新和包容的本科 XR 工程教育,培养未来的元宇宙劳动力
基本信息
- 批准号:2315596
- 负责人:
- 金额:$ 19.44万
- 依托单位:
- 依托单位国家:美国
- 项目类别:Standard Grant
- 财政年份:2023
- 资助国家:美国
- 起止时间:2023-10-01 至 2026-09-30
- 项目状态:未结题
- 来源:
- 关键词:
项目摘要
This project aims to serve the national interest by establishing an interdisciplinary mixed reality (XR) Engineering curriculum that prepares undergraduate students for flourishing careers as XR professionals and researchers. The rapidly evolving field of XR technology presents U.S. higher education institutions with a unique combination of opportunities and challenges, as the higher education institutions endeavor to tap into the potential of the XR domain. This project intends to advance XR engineering education and foster workforce development, with crafted learning materials and activities empowering students to create XR applications across diverse industries, tackle societal challenges, and unlock innovative opportunities. The project will employ evidence-based pedagogical approaches, such as learning-by-doing and learning-by-teaching, while integrating recent advances in XR technology. The proposed curriculum is designed with adaptability in mind, enabling its implementation as a new STEM program, minor, or certificate, thereby expanding participation and bolstering institutional capacity for STEM workforce development. The curriculum will initially be launched as a pilot program at Kennesaw State University and Georgia State University, two minority serving institutions. The study will be conducted using both quantitative and qualitative research methods, encompassing a review of existing literature, surveys, expert interviews, and focus group discussions with undergraduate students. Anticipated outcomes encompass a comprehensive XR engineering curriculum, enriched learning materials, and engaging activities that boost student engagement and retention while promoting increased STEM participation among women and minority students. The project results will be disseminated to other institutions, particularly Historically Black Colleges and Universities in the local area to further strengthen the XR education ecosystem and broaden the impacts of the proposed work. The NSF IUSE: EDU Program supports research and development projects to improve the effectiveness of STEM education for all students. Through its 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.
该项目旨在通过建立跨学科混合现实(XR)工程课程来服务于国家利益,该课程为本科生做好准备以作为XR专业人员和研究人员的繁荣职业做好准备。随着高等教育机构努力利用XR领域的潜力,XR技术迅速发展的领域为美国高等教育机构提供了独特的机会和挑战。该项目旨在推进XR工程教育和促进劳动力发展,并通过精心设计的学习材料和活动来授权学生在各种行业,应对社会挑战以及解锁创新的机会上创建XR应用程序。该项目将采用基于证据的教学方法,例如通过学习和学习学习,同时整合XR技术的最新进展。拟议的课程旨在考虑适应性,使其作为新的STEM计划,未成年人或证书的实施,从而扩大参与并增强STEM劳动力发展的机构能力。该课程最初将在肯尼索州立大学和佐治亚州立大学(两个少数服务机构)的试点计划中启动。该研究将使用定量和定性研究方法进行,包括对现有文献,调查,专家访谈以及与本科生的焦点小组讨论的审查。 预期的结果涵盖了一项全面的XR工程课程,丰富的学习材料以及参与活动,从而促进学生的参与和保留率,同时促进女性和少数族裔学生的STEM参与度增加。该项目的结果将被传播给其他机构,尤其是历史上的黑人学院和当地的大学,以进一步加强XR教育生态系统并扩大拟议工作的影响。 NSF IUSE:EDU计划支持研发项目,以提高所有学生STEM教育的有效性。通过其参与的学生学习轨道,该计划支持了有前途的实践和工具的创建,探索和实施。该奖项反映了NSF的法定任务,并被认为是值得通过基金会的知识分子优点和更广泛的影响评估的评估来支持的。
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
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Yingshu Li其他文献
Data Aggregation Scheduling in Battery-Free Wireless Sensor Networks
无电池无线传感器网络中的数据聚合调度
- DOI:
10.1109/tmc.2020.3035671 - 发表时间:
2022-06 - 期刊:
- 影响因子:7.9
- 作者:
Tongxin Zhu;Jianzhong Li;Hong Gao;Yingshu Li - 通讯作者:
Yingshu Li
A combination of wireless multicast advantage and hitch-hiking
无线组播优势与搭便车的结合
- DOI:
10.1109/lcomm.2005.1576580 - 发表时间:
2005 - 期刊:
- 影响因子:0
- 作者:
M. Thai;Yingshu Li;D. Du - 通讯作者:
D. Du
An Energy-Efficient Distributed Algorithm for Minimum-Latency Aggregation Scheduling in Wireless Sensor Networks
- DOI:
10.1109/icdcs.2010.11 - 发表时间:
2010-01-01 - 期刊:
- 影响因子:0
- 作者:
Yingshu Li;Longjiang Guo;Prasad, Sushil K. - 通讯作者:
Prasad, Sushil K.
Epidemic Vulnerability Index for Effective Vaccine Distribution Against Pandemic
针对流行病有效分发疫苗的流行病脆弱性指数
- DOI:
10.1109/tcbb.2022.3198365 - 发表时间:
2022 - 期刊:
- 影响因子:0
- 作者:
Hunmi Lee;Mingon Kang;Donghyun Kim;Daehee Seo;Yingshu Li - 通讯作者:
Yingshu Li
nbsp;Computing an effective decision making group of a society using social network analysis
- DOI:
- 发表时间:
2014 - 期刊:
- 影响因子:0
- 作者:
Donghyun Kim;Deying Li;Omid Asgari;Yingshu Li - 通讯作者:
Yingshu Li
Yingshu Li的其他文献
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{{ truncateString('Yingshu Li', 18)}}的其他基金
BIGDATA: F: Collaborative Research: Acquisition, Collection and Computation of Dynamic Big Sensory Data in Smart Cities
BIGDATA:F:协作研究:智慧城市动态大传感数据的采集、收集和计算
- 批准号:
1741277 - 财政年份:2018
- 资助金额:
$ 19.44万 - 项目类别:
Standard Grant
EAGER: Evaluating the feasibility of Self-Protecting Heterogeneous Wireless Sensor Networks
EAGER:评估自我保护异构无线传感器网络的可行性
- 批准号:
1052769 - 财政年份:2010
- 资助金额:
$ 19.44万 - 项目类别:
Standard Grant
SGER: A New Framework for Energy-Efficient and Realtime Data Delivery in Heterogeneous Wireless Sensor Networks
SGER:异构无线传感器网络中节能和实时数据传输的新框架
- 批准号:
0844829 - 财政年份:2008
- 资助金额:
$ 19.44万 - 项目类别:
Standard Grant
CAREER: Algorithms for Optimization Problems in Wireless Networks
职业:无线网络优化问题的算法
- 批准号:
0545667 - 财政年份:2006
- 资助金额:
$ 19.44万 - 项目类别:
Continuing Grant
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