CAP: Data Science, Learning and Youth: Connecting Research and Creating Frameworks

网络学习和未来学习技术计划资助的努力将有助于展望下一代学习技术，并促进我们对人们在技术丰富的环境中如何学习的了解。网络学习能力(CAP)项目侧重于扩大和加强网络学习社区，通常包括会议、研讨会或短期课程。这个项目的重点是一个研讨会，探索数据科学在K-12教育中的应用。它的动机是与数据进行推理在当今世界的重要性。研讨会的标题是数据科学，学习和青年：连接研究和创建框架。它的目标是将数据科学的教育意义推到网络学习研究界对话的前沿。目前，大量的本科生和研究生课程都侧重于传授数据技能和计算推理。本次研讨会将把这一重点扩展到K-12教育。它将汇集来自学习科学、人机交互和计算机科学、数学和统计教育、科学教育、社区参与和公民科学等领域的对数据科学教育感兴趣的老牌和新兴学者，以及来自K-12环境的从业者。这次研讨会将促进新的跨学科合作，并让对数据科学教育感兴趣的研究人员接触到相关的社区、文献和项目。短期目标是使这些社区能够综合新兴的发现、框架和理论，并更好地了解哪些工具、活动和环境可以支持数据科学素养。我们的长期目标是促进对数据科学教育感兴趣的统一研究社区的发展。讲习班的直接成果将包括制定具体计划，以便在讲习班结束后的一年内编写侧重于数据科学教育的文章和综合文件。这些文件将面向三个广泛和互补的受众：研究人员，通过提议在一本学术期刊上出版一期特刊；从业人员，通过两篇以从业人员为重点的文章，侧重于数学和科学教育；以及更广泛的网络学习社区，通过网络学习创新研究中心(CIRCL)资源网站主办的在线综合声明。

The Cyberlearning and Future Learning Technologies Program funds efforts that will help envision the next generation of learning technologies and advance what we know about how people learn in technology-rich environments. Cyberlearning Capacity (CAP) Projects focus on expanding and strengthening the cyberlearning community and often include conferences, workshops, or short courses. This project focuses on a workshop exploring the application of data science to K-12 education. It is motivated by the importance that reasoning with data has in today's world.The workshop is entitled Data Science, Learning and Youth: Connecting Research and Creating Frameworks. Its objective is to move the educational implications of Data Science to the forefront of conversations among the cyberlearning research community. A large number of undergraduate and post-graduate programs are presently focusing on imparting data skills and computational reasoning. This workshop will extend this focus to K-12 education. It will bring together established and emerging scholars interested in Data Science Education from fields including Learning Sciences, Human-Computer Interaction and Computer Science, Mathematics and Statistics Education, Science Education, and Community Engagement and Citizen Science, and practitioners from K-12 settings. This workshop will foster new interdisciplinary collaborations and expose researchers interested in Data Science Education to relevant communities, literatures, and projects. The short term goal is to enable these communities to synthesize emerging findings, frameworks, and theories and better understand what tools, activities, and environments can support Data Science literacy. Our long term goal is to foster the development of a unified research community interested in Data Science Education. Direct outcomes of the workshop will include concrete plans to produce articles and synthesis documents focused on Data Science Education during the year immediately following the workshop. These documents will speak to three broad and complementary audiences: researchers, through the proposal of a special issue of a scholarly journal; practitioners, through two practitioner-oriented articles focusing on mathematics and science education; and the broader Cyberlearning community, through an online Synthesis Statement to be hosted by the Center for Innovative Research in Cyberlearning (CIRCL) resource website.