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

该项目将专注于以人为中心的分析，或以人类为中心的数据分析，为数据科学的初步研究提供一个共同的基础，并为学生解决跨学科问题做好准备。以人为中心的数据分析作为数据科学中最有前途的子领域之一，要么将人类作为研究对象，要么将人类作为数据分析各个阶段的执行者。拟议的以人类为中心的社区丰富数据分析（ADACE）项目将形成一个三机构合作伙伴关系，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实施组织。他们将共同应对发展一支庞大、高质量、精通数据相关学科的劳动力队伍的挑战。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的平台，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，数据科学职业对于持续的社会和经济发展至关重要。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日益浓厚。然而，缺乏培训计划和通过现实生活项目的社区参与使得很难保持学生的参与和兴趣。实习机会有限也会减少学生在数据科学领域的成功，甚至可能导致他们离开这些领域。这个项目解决了吸引更多有才能的学生，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的关键需求。该项目致力于促进数据科学方面的本科培训。跨学科和多机构合作将努力建立一个可容纳41名学生的基础设施，并跨越他们整个四年的大学生涯。该项目旨在加强参与院校现有的数据科学和相关课程，因为其中两所院校为本科生和研究生开设了数据科学课程。为了吸引兴趣广泛的学生，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)用户与机器之间的无缝交互，(5)以人为本的主题调查个人或社会行为，以及(6)人工智能科学家/工程师和人工智能代理方面的伦理研究。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。每个专业将由一名在该领域具有专业知识的联合首席研究员领导，以他们的研究成果和跨学科合作的经验为基础，形成创新的课程和研究项目。学生将有机会获得数据科学知识、解决问题的能力、实践经验和严格的研究培训。所有课程材料的设计应便于携带、可持续和易于传播，以确保其扩大影响。这些项目还将根据可衡量的结果进行评估，并针对非传统学生进行量身定制，这些学生在参与院校周边地区的潜在数据科学劳动力中占很大比例。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 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.