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; 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.

将进行一对研讨会，以开发创新的方式，以结合有关数据科学实践以及来自数据科学课程的见解的社会科学发现。研讨会系列将开发21世纪数据科学教育的要素，该教育依靠纪律研究环境中的数据科学。研讨会的参与者将与实践的数据科学家，教育工作者和社会科学家共同努力。该项目通过将社会科学研究和教育研究的见解整合到解决如何教授数据科学和开发适当的课程材料的问题的背景下来促进融合。第一个研讨会计划与大约50名参与者一起进行1.5天，并将努力确定社会科学研究和教育研究对数据科学实践的关键见解，以将其转化为数据科学课程。它将借鉴各种社会科学学科的发现（例如科学和技术研究，跨学科合作的人种学观察，计算机支持的合作工作，在团队中的包容性和多样性，组织 /管理理论，设计中的系统思维以及人类 /技术界面）以及与学科数据科学从业者和教育者以及教育研究和设计以及教育研究和设计。在面板和工作会议中，研讨会将吸引参与者，以构建与数据科学的关键主题相关的关键主题，并开发针对课程设计的方法。该研讨会上的产品将是一份公开可用的白皮书，识别下一个工作阶段的核心见解。在第一和第二次研讨会之间的间隔期间，第二个研讨会的观察和见解将被记录并完善，以供第二个研讨会使用。为了进行交叉利用，研讨会组织者还将与精选行业从业人员联系，以评估已确定的概念对转化为现实世界应用的数据科学的重要性。第二个研讨会将与大约30名参与者一起进行1天。它将概述和构建可实施方法，以将关键见解转化为数据科学课程。一整天的主题会议将基于第一个研讨会中开发的主要见解的分类法，并围绕实际实施和新课程形式的原型解决实质性问题。该研讨会上的产品将是一套有充实的课程元素（例如练习，课程模块等），以及将公开传播的最佳实践指南。这些研讨会将把数据科学作为与课程设计中吸引数据科学和社会科学家协作吸引的数据科学的关键领域。该项目通过专注于从业人员和实践来重新重新跨学科数据科学教育议程。这些研讨会将开发可实施的公开课程要素和针对数据科学协作的数据科学教育的最佳实践，并关注诸如多样性，包容性以及社会和道德背景等重要问题。