HDR DSC: Collaborative Research: The Data Science WAV: Experiential Learning with Local Community Organizations
HDR DSC:协作研究:数据科学 WAV:与当地社区组织的体验式学习
基本信息
- 批准号:2242944
- 负责人:
- 金额:$ 13.59万
- 依托单位:
- 依托单位国家:美国
- 项目类别:Standard Grant
- 财政年份:2022
- 资助国家:美国
- 起止时间:2022-08-01 至 2024-03-31
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
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.
该项目同时解决了两个问题:1)社区和非营利组织无力解决数据科学问题; 2)学习数据科学的学生缺乏现实世界的经验。数据可用性的提高,加上以更低的成本提高计算能力,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项目,他们的大部分基于课程的问题解决经验都集中在简单数据集的干净问题上。这使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来解决这两个问题,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,将为当地组织带来直接影响,并为学生带来长期利益通过宝贵的数据科学实践经验。拟议项目有两个主要组成部分。首先,由四名经过专门培训的本科生组成的数据科学 WAV 团队将被部署到基于社区的组织,以整理、分析和可视化他们的数据。其次,该项目将提供夏季教师发展研讨会,旨在帮助新教师,尤其是社区学院的新教师在其机构教授数据科学。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。该提案在各个机构和学生群体中都有所不同。它由一所主要研究型大学(马萨诸塞大学阿默斯特分校)、四所文理学院(阿默斯特学院、汉普郡学院、曼荷莲学院和史密斯学院)和三所当地社区学院(格林菲尔德学院、霍利奥克学院和斯普林菲尔德技术学院)组成。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多元化的学生群体参与该项目。 NSF 的“利用数据革命数据科学军团”计划侧重于建设在地方、州、国家和国际层面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 Harnessing the Data Revolution Big Idea 联合资助;计算机与信息科学与工程局、信息与智能系统部;教育和人力资源局本科教育司;数学和物理科学理事会,数学科学部;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。
项目成果
期刊论文数量(0)
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会议论文数量(0)
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Valerie Barr其他文献
CS + X: Approaches, Challenges, and Opportunities in Developing Interdisciplinary Computing Curricula
CS X:开发跨学科计算课程的方法、挑战和机遇
- DOI:
- 发表时间:
2023 - 期刊:
- 影响因子:0
- 作者:
Valerie Barr;Carla E. Brodley;Elsa L. Gunter;M. Guzdial - 通讯作者:
M. Guzdial
Building bridges to other departments: three strategies
与其他部门建立桥梁:三个策略
- DOI:
10.1145/1734263.1734285 - 发表时间:
2010 - 期刊:
- 影响因子:0
- 作者:
Valerie Barr;C. Liew;R. Salter - 通讯作者:
R. Salter
Beyond computer science: computational thinking across disciplines
超越计算机科学:跨学科的计算思维
- DOI:
10.1145/2462476.2462511 - 发表时间:
2013 - 期刊:
- 影响因子:0.8
- 作者:
Amber Settle;D. Goldberg;Valerie Barr - 通讯作者:
Valerie Barr
Computational thinking in high school courses
高中课程中的计算思维
- DOI:
- 发表时间:
2010 - 期刊:
- 影响因子:0
- 作者:
V. Allan;Valerie Barr;Dennis Brylow;Susanne E. Hambrusch - 通讯作者:
Susanne E. Hambrusch
Computational thinking
- DOI:
10.1109/vlhcc.2011.6070404 - 发表时间:
2006-03 - 期刊:
- 影响因子:22.7
- 作者:
Valerie Barr - 通讯作者:
Valerie Barr
Valerie Barr的其他文献
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{{ truncateString('Valerie Barr', 18)}}的其他基金
The efficacy of a computing-concepts video library for students and peer tutors in multidisciplinary contexts
计算概念视频库在多学科背景下对学生和同伴导师的功效
- 批准号:
2337252 - 财政年份:2024
- 资助金额:
$ 13.59万 - 项目类别:
Standard Grant
CUE Ethics: Collaborative Research: Evaluating Frameworks for Incorporating Computing Across the Curriculum
CUE 伦理:协作研究:评估将计算纳入整个课程的框架
- 批准号:
1935113 - 财政年份:2020
- 资助金额:
$ 13.59万 - 项目类别:
Standard Grant
HDR DSC: Collaborative Research: The Data Science WAV: Experiential Learning with Local Community Organizations
HDR DSC:协作研究:数据科学 WAV:与当地社区组织的体验式学习
- 批准号:
1923934 - 财政年份:2019
- 资助金额:
$ 13.59万 - 项目类别:
Standard Grant
POWRE: Software Evaluation: The Application of Software Testing Techniques to Rule-Based Natural Language Processing Components
POWRE:软件评估:软件测试技术在基于规则的自然语言处理组件中的应用
- 批准号:
9973855 - 财政年份:1999
- 资助金额:
$ 13.59万 - 项目类别:
Standard Grant
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