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

这个项目将侧重于以人为中心的分析，或以人为中心的数据分析，为开始学习数据科学提供一个共同的基础，并为学生解决跨学科问题做好准备。作为数据科学最有前途的子领域之一，以人为中心的数据分析要么将人作为研究对象，要么将人作为数据分析所有阶段的执行者。拟议的以人类为中心的数据分析促进社区丰富(ADACE)项目将形成一个三机构伙伴关系，田纳西大学查塔努加分校(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。它们将共同应对培养一支在数据相关学科方面熟练掌握大量高素质劳动力的挑战。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，数据科学职业对社会和经济的持续发展至关重要。大多数美国学院和大学都看到，学生对计算机科学和其他相关系提供的这些课程的兴趣越来越大。然而，由于缺乏培训计划和通过现实生活项目进行的社区参与，很难保持学生的参与度和兴趣。有限的实习机会也会降低学生在数据科学领域的成功，甚至可能导致他们远离这些领域。这个项目解决了吸引更多有才华的学生，更好地激发学生的兴趣，提高留校率，并最终满足不断增长的劳动力需求的迫切需要。该项目旨在促进数据科学方面的本科生培训。跨学科和多机构合作将努力建立一个可容纳41名学生并跨越其大学生涯整整四年的基础设施。该项目旨在加强参与机构目前的数据科学和相关课程，因为其中两个机构有面向本科生和研究生的数据科学课程。为了吸引兴趣广泛的学生，ADACE将由四个核心模块组成-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中心的社区项目。这些项目将包括六个领域：(1)人在环路数据集成，(2)可见神经网络结构，(3)人在环路机器学习，(4)用户与机器之间的无缝交互，(5)调查个人或社会行为的以人为本的主题，以及(6)人工智能科学家/工程师和人工代理人方面的伦理研究。参与机构将有机会利用与当地营利性和非营利性组织的现有关系，让学生接触到现实世界中的数据科学问题，并提供联网机会。每个集中将由一名具有该领域专门知识的联合首席调查员领导，以他们的研究成果和跨学科协作经验为基础，制定创新的课程和研究项目。通过该计划，学生将有机会获得数据科学知识、解决问题的技能、实践经验和严格的研究培训。所有课程材料都将设计成便于携带、可持续和易于传播的，以确保其扩大影响。它们还将接受可衡量结果的评估，并将非传统学生纳入其中，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兵团计划专注于建设在地方、州、国家和国际层面利用数据革命的能力，以帮助释放数据服务于科学和社会的力量。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、信息和智能系统部门的计算机和信息科学与工程委员会、本科教育部门的教育和人力资源委员会、数学科学部门的数学和物理科学委员会以及社会、行为和经济科学委员会、多学科活动办公室和行为和认知科学部门共同资助。该奖项反映了国家科学基金会的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

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.