HDR DSC: Collaborative Research: The Data Science WAV: Experiential Learning with Local Community Organizations

该项目同时解决了两个问题：1）社区和非营利组织无法解决数据科学问题; 2）学习数据科学的学生缺乏真实的世界经验。数据可用性的提高，加上以较低成本提高的计算能力，为桌面带来了巨大的分析和解决问题的能力。然而，许多组织无法利用这些发展，因为他们往往缺乏适当的人员来解决复杂的数据科学问题。与此同时，随着学生越来越倾向于数据科学课程，他们的大部分课程解决问题的经验都集中在简单数据集的干净问题上。这让他们对在专业环境中面临的数据科学应用的现实毫无准备。该项目通过部署数据科学学生团队来帮助当地组织解决这两个问题，从而提高数据科学劳动力的长期能力。这是一个多方面的项目，将通过宝贵的数据科学实践经验为当地组织带来直接影响，并为学生带来长期利益。拟议项目有两个主要组成部分。首先，由四名受过专门培训的本科生组成的数据科学WAV团队将被部署到社区组织，以分析，分析和可视化他们的数据。其次，该项目将提供暑期教师发展研讨会，旨在帮助新教师，特别是社区大学的教师，在他们的机构教授数据科学。将体验式数据科学学习纳入课程的课程创新将对合作学术机构和更大的先锋谷地区产生持续影响。这一提议在机构和学生群体中各不相同。它包括一个主要的研究型大学（马萨诸塞州大学，阿默斯特），四个文科学院（阿默斯特，汉普郡，霍利奥克山和史密斯），和三个地方社区学院（格林菲尔德，霍利奥克和斯普林菲尔德技术）。纳入两所女子学院（史密斯和霍利奥克山）和两所西班牙裔服务机构（霍利奥克和斯普林菲尔德技术）将有助于确保多样化的学生群体参与该项目。NSF的利用数据革命数据科学团计划侧重于在地方，州，国家和国际层面建设利用数据革命的能力，以帮助释放数据的力量，为科学和社会服务。该计划中的项目由NSF的利用数据革命大想法;信息和智能系统部计算机和信息科学与工程局;本科教育部教育和人力资源局;数学科学部数学和物理科学局;该奖项反映了NSF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。

This project simultaneously addresses two problems: 1) the inability of community-based and non-profit organizations to tackle data science problems; and 2) the lack of real world experience gained by students studying data science. The increased availability of data, combined with increased computing power at lower costs, has brought to the desktop tremendous analytical and problem solving capabilities. Yet many organizations are not able to take advantage of these developments because they often lack appropriate staffing to wrestle with complex data science problems. Meanwhile, as students increasingly gravitate toward data science programs, much of their course-based problem solving experience focuses on clean problems with simple data sets. This leaves them unprepared for the reality of the data science applications they will face in professional settings. This project addresses both issues by deploying teams of data science students to assist local organizations, thereby increasing the long-term capacity of the data science workforce.This is a multifaceted project that will provide immediate impact to local organizations and long-term benefit for students through valuable hands-on data science experience. There are two major components of the proposed project. First, Data Science WAV teams of four specially-trained undergraduate students will be deployed to community-based organizations to Wrangle, Analyze, and Visualize their data. Second, this project will offer summer faculty development workshops designed to help new instructors, especially those at community colleges, teach data science at their institutions. Curricular innovations that bring experiential data science learning into the curriculum will lead to sustained impact at the partnering academic institutions and in the larger Pioneer Valley region. This proposal is diverse across both institutions and student populations. It comprises one major research university (The University of Massachusetts, Amherst), four liberal arts colleges (Amherst, Hampshire, Mount Holyoke, and Smith), and three local community colleges (Greenfield, Holyoke, and Springfield Technical). The inclusion of two women's colleges (Smith and Mount Holyoke) and two Hispanic-serving institutions (Holyoke and Springfield Technical) will help ensure that a diverse student population is engaged in the project. NSF's Harnessing the Data Revolution Data Science Corps program focuses on building capacity for harnessing the data revolution at the local, state, national, and international levels to help unleash the power of data in the service of science and society. Projects in this program are being jointly funded by the NSF's Harnessing the Data Revolution Big Idea; the Directorate for Computer and Information Science and Engineering, Division of Information and Intelligent Systems; the Directorate for Education and Human Resources, Division of Undergraduate Education; the Directorate for Mathematical and Physical Sciences, Division of Mathematical Sciences; and the Directorate for Social, Behavioral and Economic Sciences, Office of Multidisciplinary Activities and Division of Behavioral and Cognitive Sciences.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.