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: 2123237
• 负责人: David Lattanzi
• 金额: $ 12.01万
• 依托单位: George Mason University
• 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=2123237&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.

该项目的目标是开发一个可在不同机构之间转移的数据科学教育和劳动力发展课程框架，以便 STEM 相关项目可以将数据科学课程与现有课程即插即用，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共同创建，以确保关注现实世界问题的解决，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将数据科学与现有工程课程相结合的最佳实践提供循证蓝图。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、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，让他们可以在各种环境中学习新技能，以及 (3 ）通过让具有不同背景、经验、技能和技术成熟度的本科生参与数据科学军团，扩大数据科学人才库。这项工作将支持数据科学军团的目标，即建设教育和劳动力发展能力，以利用地方、州和国家层面的数据革命。参与该项目的机构将开发培训计划并整理数据集，以便将其纳入全国范围内的本科教学中。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。这些资源旨在减少寻求将数据科学纳入教学的教师的准入门槛，因为招募和留住教师来创建和教授数据科学综合入门课程已被国家科学院视为一个重大障碍。该奖项反映了通过使用基金会的智力价值和更广泛的影响审查标准进行评估，NSF 的法定使命被认为值得支持。