CUE Ethics: Collaborative Research: Open Collaborative Experiential Learning (OCEL.AI): Bridging Digital Divides in Undergraduate Education of Data Science

密苏里-堪萨斯城大学与东密歇根大学、埃塞克斯县学院和佛罗里达大学合作，提出了开放式协作体验学习(OCEL.AI)项目，这是一个开放知识网络(OKN)，支持在现有机构结构内教授服务不足人群计算机科学(CS)+新闻和战略传播的大专教师。人工智能(AI)，特别是深度学习(DL)的最新进展改善了数据驱动的方法和工具在广泛领域的最新成果。为了构建未来的人才生态系统，迫切需要创建一支合格的数据科学员工队伍，他们能够在新闻、健康传播和广告等人类社会的各个领域和方面履行关键职能。为了满足这一需求，基于智能云的协作工具将为人工智能和数据驱动的研究和教育社区提供GitHub和代码存储库为软件工程和开源社区提供的服务。在这个OKN中，少数族裔学生将感到学习数据科学的动力和动力，因为他们可以实时共享、重用、复制、部署、讨论、学习和应用数据和AI模型。预计参加CS+新闻学和战略传播学课程的学生会发现，CS专业和非CS专业的学生学习数据科学的兴趣、自我效能和动机都会增加，特别是在黑人、女性和西班牙裔学生中。作为一个网络改进社区，该项目将专注于三个主要任务：1)启动由研究人员实验室开发的OCEL.AI在线教师专业发展计划；2)推出OCEL.AI上的学生学习界面，为CS+新闻和战略传播专业的学生提供引人入胜的学习体验，同时也提供可扩展到CS+X计划的基础设施，用于商业和医疗等一系列其他X项目；以及3)引发对数据科学伦理的批判性思考。为了让数据科学与少数族裔学生更相关，该项目将通过将围绕数字鸿沟和数据科学伦理的批判性思维纳入课程，突出少数族裔在美国的经历。该奖项反映了NSF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。

The University of Missouri-Kansas City, in partnership with Eastern Michigan University, Essex County College, and University of Florida, proposes the Open Collaborative Experiential Learning (OCEL.AI) project, an Open Knowledge Network (OKN), that supports postsecondary instructors who teach underserved populations Computer Science (CS)+Journalism and Strategic Communication within their existing institutional structure. Recent advances in artificial intelligence (AI), and specifically deep learning (DL) have improved the state-of-the-art results of the data-driven approaches and tools in a wide range of domains. To build the future talent ecosystem, there is an urgent need to create a qualified data science workforce that can perform critical functions in a variety of domains and aspects of human society, such as journalism, health communication, and advertising. To address this need, the intelligent cloud-based collaborative tool will provide to the AI and data-driven research and education communities what GitHub and code repositories provide to the software engineering and open-source communities. In this OKN, minority students will feel empowered and motivated to study data science since they can share, reuse, reproduce, deploy, discuss, learn, and apply data and AI models in real time. It is expected that students taking these CS+Journalism and Strategic Communication courses will see increased interest, self-efficacy, and motivation in studying data science among both CS majors and non-majors - in particular among black, female, and Hispanic students. Organized as a Networked Improvement Community, the project will focus on three major tasks: 1) launching an online faculty professional development program on OCEL.AI that has been developed by the researcher's lab; 2) launching a student learning interface on OCEL.AI to offer engaging learning experiences to CS+Journalism and Strategic Communication students but also providing infrastructure that can be extended to CS+X programs for a range of other Xs such as business and health care; and 3) sparking critical thinking of data science ethics. To make data science more relevant to minority students, the project will highlight minority experiences in the United States by incorporating critical thinking around digital divides and data science ethics into the curriculum.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.