Collaborative Research: HDR DSC: Infusion of Data Science and Computation into Engineering Curricula
合作研究:HDR DSC:将数据科学和计算融入工程课程
基本信息
- 批准号:2123285
- 负责人:
- 金额:$ 1.5万
- 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:2021-10-01 至 2024-09-30
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
The goal of this project is to develop a curricular framework for data science education and workforce development that is transferable between diverse institutions, so STEM-related programs can plug and play data science lessons with existing curricula without much overhead. These lessons will be created in conjunction with community stakeholders and industry partners to ensure a focus on real-world problem solving and include student organizations in course development to promote flexible learning pathways. The proposed additions to undergraduate STEM education will provide an evidence-based blueprint for best practices in integrating data science with existing engineering curricula. Implementation across multiple engineering departments will result in a significant impact on society through the training of a diverse, globally competitive STEM workforce with high data literacy. The objectives of this project are to (1) facilitate data science education and workforce development for engineering and related topics, (2) provide opportunities for students to participate in practical experiences where they can learn new skills in a variety of environments, and (3) expand the data science talent pool by enabling the participation of undergraduate students with diverse backgrounds, experiences, skills, and technical maturity in the Data Science Corps. This work will support the Data Science Corps objective of building capacity for education and workforce development to harness the data revolution at local, state, and national levels. The institutions gathered for this project will develop training programs and curate datasets that will be made available so they can be included in undergraduate instruction nationwide. Furthermore, the training materials will be shared with industry partners, facilitating workforce development. The project team will develop a website to house data science training programs, didactic datasets, and other resources for educators. These resources are intended to reduce barrier to entry for faculty seeking to incorporate data science into their instruction, as recruiting and retaining faculty to create and teach integrated introductory courses in data science has been recognized as a significant hurdle by the National Academies.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.
该项目的目标是为数据科学教育和劳动力发展开发一个可在不同机构之间转移的课程框架,以便STEM相关课程可以在现有课程中插入和播放数据科学课程,而不会产生太多开销。这些课程将与社区利益相关者和行业合作伙伴一起创建,以确保关注现实世界的问题解决,并将学生组织纳入课程开发,以促进灵活的学习途径。拟议增加的本科STEM教育将为将数据科学与现有工程课程相结合的最佳做法提供基于证据的蓝图。跨多个工程部门的实施将通过培训具有高数据素养的多样化、具有全球竞争力的STEM员工队伍,对社会产生重大影响。该项目的目标是(1)促进工程及相关主题的数据科学教育和劳动力发展,(2)为学生提供参与实践经验的机会,使他们能够在各种环境中学习新技能,以及(3)通过允许具有不同背景、经验、技能和技术成熟度的本科生参与数据科学团队,扩大数据科学人才库。这项工作将支持数据科学公司的目标,即建设教育和劳动力发展能力,以利用地方、州和国家各级的数据革命。为该项目聚集的机构将开发培训计划并管理数据集,这些数据集将被提供,以便它们可以被纳入全国的本科教学。此外,培训材料将与行业合作伙伴共享,促进劳动力发展。该项目团队将开发一个网站,为教育工作者提供数据科学培训计划、教学数据集和其他资源。这些资源旨在降低寻求将数据科学纳入其教学的教师的准入门槛,因为招聘和留住教师来创建和教授数据科学的综合入门课程一直是美国国家科学院承认的一个重大障碍。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。
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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Zufen Wang其他文献
Investigation of efficiency models in EnergyPlus and AMCA standard 207 for induction motors powered by variable frequency drives
- DOI:
10.1016/j.enbuild.2019.04.045 - 发表时间:
2019-08-01 - 期刊:
- 影响因子:
- 作者:
Gang Wang;Zufen Wang;Zhitao Han;Reidel Diaz Rodriguez - 通讯作者:
Reidel Diaz Rodriguez
Uncertainty analysis for different virtual pump water flow meters
不同虚拟泵水流量计的不确定度分析
- DOI:
10.1080/23744731.2018.1526015 - 发表时间:
2019 - 期刊:
- 影响因子:1.9
- 作者:
Gang Wang;Zufen Wang;Li Song - 通讯作者:
Li Song
Accuracy improvement of virtual pump water flow meters using calibrated characteristics curves at various frequencies
- DOI:
10.1016/j.enbuild.2019.03.021 - 发表时间:
2019-05-15 - 期刊:
- 影响因子:
- 作者:
Zufen Wang;Esber Andiroglu;Gang Wang;Li Song - 通讯作者:
Li Song
Evaluation of supply air temperature control performance with different control strategies at air handling units
- DOI:
10.1016/j.buildenv.2023.110649 - 发表时间:
2023-09-01 - 期刊:
- 影响因子:
- 作者:
Zufen Wang;Marwan R. Hashem;Li Song;Gang Wang - 通讯作者:
Gang Wang
Development, validation and application of an energy model for energy efficient operation of parallel pump systems
- DOI:
10.1016/j.jobe.2022.105098 - 发表时间:
2022-11-01 - 期刊:
- 影响因子:7.400
- 作者:
Gang Wang;Saeed Ghoddousi;Zufen Wang;Li Song - 通讯作者:
Li Song
Zufen Wang的其他文献
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