HDR DSC: Collaborative Research: Transforming Data Science Education through a Portable and Sustainable Anthropocentric Data Analytics for Community Enrichment Program

HDR DSC：协作研究：通过便携式和可持续的以人类为中心的数据分析来改变数据科学教育，促进社区丰富计划

• 批准号: 1924092
• 负责人: Jiang Li
• 金额: $ 45万
• 依托单位: Howard University
• 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 2023-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1924092&HistoricalAwards=false
• 关键词: HDR; DSC; Collaborative; Research; Transforming

This project will focus on human-centric analytics, or anthropocentric data analytics, to provide a common ground for beginning studies in data science and to prepare students to address interdisciplinary problems. As one of the most promising subareas of data science, human-centric data analytics either considers humans as the research object or involves humans as the executors over all stages of data analytics. The proposed Anthropocentric Data Analytics for Community Enrichment (ADACE) project will form a three-institution partnership, with University of Tennessee at Chattanooga (UTC) as the coordinating organization, and UTC, Chattanooga State Community College and Howard University as implementing organizations. Together they will address the challenge of developing a large, high-quality workforce skilled in data-related disciplines. This is essential for the United States to maintain its competitiveness in the 21st century. The project aims to establish an interdisciplinary platform with a curriculum that integrates real-world community research projects. In today's increasingly globalized world, data science occupations are essential for sustained social and economic development. Most U.S. colleges and universities are witnessing an increased interest from students in these programs offered by computer science and other related departments. However, a lack of training programs and community engagement through real-life projects makes it difficult to keep students engaged and interested. Limited access to internships can also reduce students' success in data science and may even direct them away from these fields. This project addresses the critical need to attract higher numbers of talented students, to better stimulate students' interest, to increase the retention rates, and to eventually meet the rising workforce demand. The project endeavors to promote undergraduate training in data science. An interdisciplinary and multi-institutional collaboration will strive to establish an infrastructure that accommodates 41 students and spans the entire four years of their college career. The project aspires to enhance current data science and related curricula of the participating institutions, as two of them have data science programs for undergraduate and graduate students. To attract students with a broad range of interests, ADACE will consist of four core modules - mathematics foundation, computational foundation, data science, and data science applications - and integrate multiple interdisciplinary and human-centric community projects. Those projects will feature six areas: (1) human-in-the-loop data integration, (2) visible neural network architecture, (3) human-in-the-loop machine learning, (4) seamless interaction between users and machines, (5) human-oriented topics investigating the behavior of individuals or society, and (6) studies of ethics in terms of both AI scientists/engineers and artificial agents. Participating institutions will have the opportunity to leverage existing relationships with local for- and non-profit organizations to expose students to real-world problems of data science and provide opportunities for networking. Each concentration will be led by a co-principal investigator with expertise in that area, building on their research findings and experience with interdisciplinary collaboration to shape innovative curricula and research projects. Students will have the opportunity to gain knowledge in data science, problem-solving skills, hands-on experience, and rigorous research training through this proposed program. All curricular materials will be designed to be portable, sustainable, and easily disseminated to ensure their expanded impact. They will also be evaluated for measurable outcomes and tailored to include non-traditional students, who form a large portion of the potential data science workforce in the regions surrounding the participating institutions. 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.

该项目将专注于以人为中心的分析，或以人为中心的数据分析，为开始数据科学研究提供共同基础，并为学生解决跨学科问题做好准备。作为数据科学中最有前途的子领域之一，以人为中心的数据分析要么将人类视为研究对象，要么将人类作为数据分析各个阶段的执行者。拟议的以人为中心的数据分析促进社区丰富（ADACE）项目将形成三个机构的伙伴关系，田纳西大学查塔努加（UTC）作为协调组织，UTC，查塔努加州立社区学院和霍华德大学作为执行组织。他们将共同应对发展一支在数据相关学科熟练的大型高素质劳动力队伍的挑战。 这对美国在21世纪保持竞争力至关重要。该项目旨在建立一个跨学科平台，其课程整合了现实世界的社区研究项目。在当今日益全球化的世界中，数据科学职业对于社会和经济的可持续发展至关重要。大多数美国学院和大学都见证了学生对计算机科学和其他相关部门提供的这些课程的兴趣越来越大。然而，缺乏培训计划和社区参与，通过现实生活中的项目，很难让学生参与和感兴趣。有限的实习机会也会降低学生在数据科学领域的成功率，甚至可能导致他们远离这些领域。该项目解决了吸引更多有才华的学生的迫切需要，以更好地激发学生的兴趣，提高保留率，并最终满足不断增长的劳动力需求。该项目致力于促进数据科学的本科生培训。一个跨学科和多机构的合作将努力建立一个基础设施，可容纳41名学生，并跨越他们的大学生涯的整个四年。该项目旨在加强参与机构当前的数据科学和相关课程，因为其中两个机构为本科生和研究生提供数据科学课程。为了吸引具有广泛兴趣的学生，ADACE将包括四个核心模块-数学基础，计算基础，数据科学和数据科学应用-并整合多个跨学科和以人为本的社区项目。这些项目将包括六个领域：（1）人在环数据集成，（2）可见神经网络架构，（3）人在环机器学习，（4）用户和机器之间的无缝交互，（5）以人为本的主题，调查个人或社会的行为，以及（6）人工智能科学家/工程师和人工智能代理人的伦理研究。参与机构将有机会利用与当地非营利组织的现有关系，让学生接触数据科学的现实问题，并提供建立网络的机会。每个浓度将由一个共同的主要研究者在该领域的专业知识，他们的研究成果和跨学科合作的经验，塑造创新的课程和研究项目的基础上领导。学生将有机会获得数据科学知识，解决问题的能力，实践经验，并通过这个拟议的计划严格的研究培训。所有课程材料将被设计为便携式，可持续和易于传播，以确保其扩大的影响。他们还将评估可衡量的成果，并针对非传统学生进行定制，这些学生构成了参与机构周围地区潜在数据科学劳动力的很大一部分。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。该计划中的项目由美国国家科学基金会利用数据革命大创意联合资助;信息和智能系统部计算机和信息科学与工程理事会;本科教育部教育和人力资源理事会;数学科学部数学和物理科学理事会;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。

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