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

• 批准号: 2123244
• 负责人: Stephanie Paal
• 金额: $ 10万
• 依托单位: Texas A&M Engineering Experiment Station
• 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: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2123244&HistoricalAwards=false
• 关键词: Collaborative; Research; HDR; DSC; Infusion

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课程框架，该框架可在不同机构之间转移，因此STEM相关课程可以在现有课程中插入和播放数据科学课程，而无需太多开销。这些课程将与社区利益相关者和行业合作伙伴一起创建，以确保专注于解决现实世界的问题，并将学生组织纳入课程开发，以促进灵活的学习途径。本科STEM教育的拟议补充将为数据科学与现有工程课程整合的最佳实践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元化、全球竞争力的STEM劳动力对社会产生重大影响。该项目的目标是（1）促进工程和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，让他们可以在各种环境中学习新技能，以及（3）通过使具有不同背景，经验，技能，和技术成熟度。这项工作将支持数据科学团的教育和劳动力发展能力建设目标，以利用地方，州和国家层面的数据革命。为这个项目聚集的机构将开发培训计划和策划数据集，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。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。这些资源旨在减少教师寻求将数据科学纳入其教学的门槛，作为招聘和留住教师，创建和教授数据科学综合入门课程，已被美国国家科学院视为一个重大障碍。该奖项反映了NSF的法定使命，并被认为值得通过使用基金会的智力价值和更广泛的影响力进行评估来支持审查标准。