Collaborative Research: Leveraging the Collective Strengths of e4usa and FiRST for Greater Impact on the Future Engineering Workforce (e4usa+FIRST)
合作研究:利用 e4usa 和 FiRST 的集体优势对未来工程人员产生更大影响(e4usa FIRST)
基本信息
- 批准号:2113402
- 负责人:
- 金额:$ 26.09万
- 依托单位:
- 依托单位国家:美国
- 项目类别:Standard Grant
- 财政年份:2021
- 资助国家:美国
- 起止时间:2021-04-15 至 2024-06-30
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
Industry demands for highly trained science, technology, engineering, and math (STEM) professionals are growing at a rate not supported by current post-secondary student enrollments. Efforts have been made primarily in isolation at the pre-college level to educate and excite students about possible careers in STEM. The e4usa+FIRST project is an unprecedented effort that establishes a partnership between two existing programs - Engineering for US All (e4usa) and For Inspiration and Recognition of Science and Technology (FIRST) - in an effort to leverage collective strengths toward furthering the democratization of engineering education. This collaborative effort prepares teachers to educate, inform, and excite youth about careers in engineering for greater overall impact on the future engineering workforce.The project’s overarching goal is to design and test a myriad of blended e4usa and FIRST models to be implemented within underserved communities that have been unable to offer or maintain engineering experiences at their schools. Targeting unserved communities is designed to intentionally expand the reach and impact of these two programs. The overarching goal is accompanied by four objectives: 1) establish blended e4usa+FIRST models for high schools in underserved communities, 2) prepare teachers and schools to implement an e4usa+FIRST model, 3) link teachers with mentors, universities, and industry, and 4) explore program scalability and sustainability through innovative business models and technological tools. The overall effort entails a kick-off workshop, multiple development sprints, summer professional development, academic year community of practice, mentorship, university and industry partnerships, and scalability and sustainability initiatives. Implementation will be evaluated using teacher interviews, student focus groups, classroom observations, and surveys. Additional efforts exploring mechanisms to support scalability, sustainability, and incorporation of new schools into the engineering education ecosystem are intended to increase the longevity and overall impact of the e4usa+FIRST program. This effort provides the foundation for testing the likelihood of the collaboration’s future success, specifically within underserved communities. The blended approach has the potential to contribute greatly to recruitment and retention of a more diverse future engineering workforce, while demonstrating the value of such efforts to university and industry partners. The result will be a better educated citizenship with a growing interest in engineering and engineering careers.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.
行业对训练有素的科学、技术、工程和数学(STEM)专业人员的需求正在以目前高等教育学生入学率无法支持的速度增长。主要是在大学预科阶段孤立地努力教育和激发学生对STEM领域可能的职业生涯的兴趣。e4usa+FIRST项目是一项前所未有的努力,它在现有的两个项目之间建立了伙伴关系——为我们所有的工程(e4usa)和为科学和技术的灵感和认可(FIRST)——努力利用集体力量进一步推进工程教育的民主化。这种合作努力使教师能够教育、告知和激发年轻人对工程职业的兴趣,从而对未来的工程劳动力产生更大的整体影响。该项目的首要目标是设计和测试无数混合e4usa和FIRST模型,以便在服务不足的社区中实施,这些社区无法在学校提供或维持工程经验。以未得到服务的社区为目标,旨在有意扩大这两个项目的覆盖范围和影响。总体目标包括四个目标:1)为服务不足社区的高中建立混合e4usa+FIRST模式;2)为教师和学校实施e4usa+FIRST模式做好准备;3)将教师与导师、大学和行业联系起来;4)通过创新的商业模式和技术工具探索项目的可扩展性和可持续性。总体努力包括启动研讨会、多个开发冲刺、夏季专业发展、学年实践社区、指导、大学和行业伙伴关系,以及可扩展性和可持续性倡议。实施情况将通过教师访谈、学生焦点小组、课堂观察和调查进行评估。进一步努力探索支持可扩展性、可持续性和将新学校纳入工程教育生态系统的机制,旨在延长e4usa+FIRST项目的寿命和整体影响。这项工作为测试合作未来成功的可能性提供了基础,特别是在服务不足的社区中。这种混合方法有可能为招聘和留住未来更多样化的工程人才做出巨大贡献,同时向大学和行业合作伙伴展示这种努力的价值。结果将是一个受过更好教育的公民,对工程和工程职业的兴趣越来越大。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。
项目成果
期刊论文数量(0)
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专利数量(0)
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Steve Efe其他文献
Seismic response prediction of composite plate shear walls- concrete filled (C-PSW/CF) using machine learning methods
基于机器学习方法的混凝土填充组合板剪力墙(C-PSW/CF)抗震反应预测
- DOI:
10.1016/j.engstruct.2024.119228 - 发表时间:
2025-01-01 - 期刊:
- 影响因子:6.400
- 作者:
Nakisa Haghi;Steve Efe;Siamak Epackachi - 通讯作者:
Siamak Epackachi
Steve Efe的其他文献
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{{ truncateString('Steve Efe', 18)}}的其他基金
Collaborative Research BPE track 3: Minority Mentoring for Advancement and Participation in Engineering Hub
协作研究 BPE 轨道 3:少数族裔指导以促进工程中心的进步和参与
- 批准号:
2217718 - 财政年份:2022
- 资助金额:
$ 26.09万 - 项目类别:
Standard Grant
NSF INCLUDES Planning Grant: Increasing the Representation of Minorities in Engineering (IRME)
NSF 包括规划拨款:增加少数族裔在工程领域的代表性 (IRME)
- 批准号:
2040830 - 财政年份:2020
- 资助金额:
$ 26.09万 - 项目类别:
Standard Grant
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Cell Research
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- 批准号:10774081
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