Workshop on Data Science Across the Undergraduate Curriculum: University-Industry Online Case Studies on Applications of Data Science

本科课程数据科学研讨会：大学-工业界在线数据科学应用案例研究

• 批准号: 1912159
• 负责人: Gang He
• 金额: $ 4.98万
• 依托单位: SUNY at Stony Brook
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-10-01 至 2020-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1912159&HistoricalAwards=false
• 关键词: Workshop; Data; Science; Across; Undergraduate

With support from the NSF Improving Undergraduate STEM Education Program: Education and Human Resources (IUSE: EHR), this project will develop and hold a national workshop entitled "Data Science Across the Undergraduate Curriculum: University-Industry Online Case Studies on Applications of Data Science." The workshop has two major aims: 1) review the national landscape of major online resources for learning and teaching data science across the undergraduate curriculum; and 2) make initial plans for developing frameworks that will guide curricular design, facilitating learning environments, and doing assessments in the context of online case studies on applications of data science. The growing abundance of data from heterogeneous sources is impacting research, design, manufacturing, marketing, and many workplace practices. Workshop participants will explore how colleges and universities, in partnership with industry, can better prepare undergraduate students from any major to gather, analyze and use data effectively to improve processes. The workshop will engage participants in online resources and learning environments to develop case studies based on examples of data science applications across a wide range of STEM areas. Each case study will address technical and technology dimensions, applications, and societal implications. Participants will also consider ways to help students understand societal impacts of data science. The workshop will generate a report of its findings that will be available online and on relevant STEM education networks. The NSF IUSE:EHR Program supports research and development projects to improve the effectiveness of STEM education for all students.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.

在NSF改善本科STEM教育计划：教育和人力资源（IUSE：EHR）的支持下，该项目将开发并举办一个名为“跨本科课程的数据科学：数据科学应用的大学-行业在线案例研究”的国家研讨会。该研讨会有两个主要目标：1）审查本科课程中学习和教学数据科学的主要在线资源的国家景观; 2）制定初步计划，以制定指导课程设计的框架，促进学习环境，并在数据科学应用的在线案例研究背景下进行评估。 来自异构源的数据日益丰富，正在影响研究、设计、制造、营销和许多工作场所的实践。 研讨会的参与者将探讨学院和大学如何与行业合作，更好地帮助任何专业的本科生有效地收集、分析和使用数据，以改进流程。该研讨会将让参与者参与在线资源和学习环境，根据广泛的STEM领域的数据科学应用实例开发案例研究。每个案例研究将涉及技术和技术层面，应用和社会影响。与会者还将考虑如何帮助学生了解数据科学的社会影响。研讨会将产生一份关于其调查结果的报告，该报告将在网上和相关的STEM教育网络上提供。 NSF IUSE：EHR计划支持研究和开发项目，以提高所有学生STEM教育的有效性。该奖项反映了NSF的法定使命，并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，被认为值得支持。