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世界的经验。数据可用性的提高，加上以较低成本增加的计算能力，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。同时，随着越来越多的学生被数据科学项目所吸引，他们基于课程的问题解决经验主要集中在使用简单数据集的清晰问题上。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协助当地组织，从而提高数据科学劳动力的长期能力，解决了这两个问题。这是一个多方面的项目，将为当地组织提供即时影响，并通过宝贵的动手数据科学经验为学生提供长期利益。拟议的项目有两个主要组成部分。首先，由四名受过特殊训练的本科生组成的数据科学WAV团队将被部署到社区组织中，对他们的数据进行整理、分析和可视化。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，在他们的机构中教授数据科学。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。该提案在机构和学生群体中都是多样化的。它包括一所主要的研究型大学（马萨诸塞大学，阿默斯特），四所文理学院（阿默斯特，汉普郡，芒特霍利奥克和史密斯）和三所当地社区学院（格林菲尔德，霍利奥克和斯普林菲尔德技术学院）。两所女子学院（史密斯学院和芒特霍利奥克学院）和两所西班牙裔服务机构（霍利奥克学院和斯普林菲尔德技术学院）的加入将有助于确保参与该项目的学生群体多样化。美国国家科学基金会的“驾驭数据革命”数据科学队项目侧重于在地方、州、国家和国际层面建立驾驭数据革命的能力，以帮助释放数据的力量，为科学和社会服务。该项目由美国国家科学基金会“利用数据革命大创意”项目联合资助；计算机和信息科学与工程理事会，信息和智能系统司；教育和人力资源司本科教育司；数学科学司数学和物理科学理事会；社会、行为和经济科学司、多学科活动办公室和行为和认知科学司。该奖项反映了美国国家科学基金会的法定使命，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.