Convergence HDR: Social Science Insights for 21st Century Data Science Education (SSI)

Convergence HDR：21 世纪数据科学教育 (SSI) 的社会科学见解

• 批准号: 1744428
• 负责人: Cathryn Carson
• 金额: $ 10万
• 依托单位: University of California-Berkeley
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-10-01 至 2022-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1744428&HistoricalAwards=false
• 关键词: Convergence; HDR; Social; Science; Insights

A pair of workshops will be conducted to develop innovative ways of incorporating social science findings about the practice of data science and insights from educational research into data science curricula. The workshop series will develop elements of 21st-century data science education anchored in the doing of data science in disciplinary research settings. Workshop participants will form a community of practice with practicing data scientists, educators, and social scientists working together. This project promotes Convergence by integrating insights from social science research and education research in the context of addressing the problem of how to teach data science and develop the appropriate curricular materials. The first workshop is planned for 1.5 days with about 50 participants, and will strive to identify key insights from social science research and education research into the practice of data science, in the service of their translation into data science curriculum. It will draw on findings from a range of social science disciplines (such as science and technology studies, ethnographic observation of transdisciplinary collaboration, computer supported cooperative work, work on inclusion and diversity in teams, organizational / management theory, systems thinking in design, and the human/technology interface) and educational research and design together with disciplinary data science practitioners and educators. In panels and working sessions, the workshop will draw in participants to frame key themes associated with the doing of data science and develop ways of targeting these to curriculum design. The product from this workshop will be a publicly available white paper identifying core insights for the next stage of work.In the intervening period between the first and second workshops, the observations and insights from the first workshop will be recorded and refined for use by the second workshop. In the interest of cross-fertilization, the workshop organizers will also make contact with select industry practitioners to assess the importance of the identified concepts for data science translated to real world application. The second workshop will be for 1 day with about 30 participants. It will outline and construct implementable approaches for translating the key insights into data science curricula. Thematic sessions through the day will build on the taxonomy of key insights developed in the first workshop, and address substantive issues around practical implementation, and prototyping of new curricular forms. The products from this workshop will be a fleshed-out set of curricular elements (such as exercises, course modules, etc.) and best practices guidelines to be publicly disseminated.These workshops will spotlight the doing of data science as a key arena for collaboratively engaging data science educators and social scientists in curriculum design. This project reorients the transdisciplinary data science education agenda by focusing on practitioners and practice. The workshops will develop implementable, publicly available curricular elements and best practices for data science education oriented to the collaborative doing of data science, with attention to important issues such as diversity, inclusion, and societal and ethical context.

将举办两个研讨会，以开发创新方法，将有关数据科学实践的社会科学发现和教育研究的见解纳入数据科学课程。该系列研讨会将开发21世纪数据科学教育的要素，这些要素将在学科研究环境中进行数据科学。研讨会的参与者将与实践数据科学家，教育工作者和社会科学家一起形成一个实践社区。该项目通过整合社会科学研究和教育研究的见解来促进融合，解决如何教授数据科学和开发适当的课程材料的问题。第一次研讨会计划为期1.5天，约有50名与会者，将努力从社会科学研究和教育研究中找出数据科学实践的关键见解，以服务于将其转化为数据科学课程。它将借鉴一系列社会科学学科（如科学和技术研究，跨学科合作的人种学观察，计算机支持的合作工作，团队的包容性和多样性，组织/管理理论，设计中的系统思维以及人/技术界面）和教育研究的结果，并与学科数据科学从业者和教育工作者一起设计。在小组讨论和工作会议中，研讨会将吸引参与者来构建与数据科学相关的关键主题，并制定将这些主题用于课程设计的方法。这次研讨会的成果将是一份可公开获取的白色文件，确定下一阶段工作的核心见解，在第一次和第二次研讨会之间的间隔期内，第一次研讨会的意见和见解将被记录和完善，供第二次研讨会使用。为了促进交流，研讨会组织者还将与选定的行业从业者接触，以评估已确定的数据科学概念转化为真实的世界应用的重要性。第二次研讨会为期一天，约有30名与会者。它将概述并构建可实施的方法，将关键见解转化为数据科学课程。通过一天的主题会议将建立在第一次研讨会中开发的关键见解的分类，并解决围绕实际实施的实质性问题，以及新课程形式的原型。本次研讨会的成果将是一套充实的课程元素（如练习、课程模块等）。和最佳实践指南将公开传播。这些研讨会将突出数据科学作为一个关键的竞技场，让数据科学教育工作者和社会科学家共同参与课程设计。该项目通过关注从业者和实践来重新定位跨学科数据科学教育议程。这些研讨会将为面向数据科学合作的数据科学教育开发可实施的、公开可用的课程要素和最佳实践，并关注多样性、包容性、社会和伦理背景等重要问题。