NRT-IGE: Augmenting, Piloting, and Scaling Computational Notebooks to Train New Graduate Researchers in Data-Centric Programming

NRT-IGE：增强、试点和扩展计算笔记本以培训新研究生研究人员进行以数据为中心的编程

• 批准号: 1735234
• 负责人: James Hollan
• 金额: $ 49.88万
• 依托单位: University of California-San Diego
• 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: 2017-09-01 至 2021-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1735234&HistoricalAwards=false
• 关键词: NRT; IGE; Augmenting; Piloting; Scaling

Every research area is confronting torrents of data arriving with increasing velocity, volume, and variety. The unprecedented scales of data, the accelerating pace of its accumulation, and disappearing disciplinary boundaries bring exciting research and development opportunities but also challenge traditional graduate education. A central challenge for virtually every discipline is ensuring students have the computational skills needed for increasingly data-intensive research and necessary for a competitive and rapidly evolving job market. Across the biological, physical, and social sciences, one common approach to addressing this challenge is to create bootcamps, which are introductory short courses for new graduate students. This National Science Foundation Research Traineeship (NRT) award in the Innovations in Graduate Education (IGE) Track to the University of California - San Diego will expand on the bootcamp approach and simultaneously exploit the growing movement for the creation of computational notebooks by augmenting Jupyter Notebook, a web-based notebook with novel online facilities for data-centric programming training for graduate students in a wide range of disciplines. This has the potential to improve the efficacy of training graduate students in data-centric programming and expand its impact by making new instructional facilities widely available via the web.Building on open-source Jupyter Notebook software and widely deployed educational tools the investigators have developed to support tutoring (Python Tutor), feedback (PeerStudio), discussion (Talkabout), and activity capture (ChronoViz), the project will augment Jupyter Notebook to assist in training new graduate students in data-centric programming. This project will iteratively design, pilot, and evaluate the augmented notebooks and associated new companion curricula in bootcamps and ongoing classes to validate the approach, and make the resulting system, tailored to specific discipline requirements, available online to be widely shared, evolved, and extended in bootcamps, graduate classes, and online courses. In addition, project members will participate in the UC San Diego STARS (Summer Training for Academic Research Success) outreach program and involve high school students from the innovative Preuss School on campus and other high schools in the area. To extend impact beyond publication, education, and local outreach, project members will work closely with the Project Jupyter team to form a community to further develop and evolve this approach for training students in data-centric programming and help fulfill the promise that increased sharing of data and analyses holds for advancing open scientific collaboration and reproducible science.The NSF Research Traineeship (NRT) Program is designed to encourage the development and implementation of bold, new, potentially transformative models for STEM graduate education training. The Innovations in Graduate Education Track is dedicated solely to piloting, testing, and evaluating novel, innovative, and potentially transformative approaches to graduate education.

每一个研究领域都面临着以越来越快的速度、数量和种类到达的数据洪流。前所未有的数据规模、数据积累的加速以及学科界限的消失，带来了令人兴奋的研究和发展机会，但也对传统的研究生教育提出了挑战。几乎每个学科的核心挑战是确保学生拥有越来越多的数据密集型研究所需的计算技能，以及竞争激烈和快速发展的就业市场所必需的计算技能。在生物、物理和社会科学领域，应对这一挑战的一种常见方法是创建训练营，这是为新研究生开设的入门性短期课程。这个国家科学基金会研究培训（NRT）奖在研究生教育创新（IGE）轨道到加州-圣地亚哥大学将扩大训练营的方法，同时利用日益增长的运动，通过增强笔记本电脑，一个基于网络的笔记本电脑，具有新颖的在线设施，用于为各种学科的研究生提供以数据为中心的编程培训。这有可能提高以数据为中心的编程培训研究生的效率，并通过网络广泛提供新的教学设施来扩大其影响。（Python Tutor），反馈（PeerStudio），讨论（Talkabout）和活动捕获（ChronoViz），该项目将增强Queryter Notebook，以帮助培训新的研究生以数据为中心的编程。该项目将在训练营和正在进行的课程中反复设计、试用和评估增强型笔记本电脑和相关的新配套课程，以验证该方法，并根据特定的学科要求定制所产生的系统，以便在训练营、研究生课程和在线课程中广泛共享、发展和扩展。此外，项目成员将参加加州大学圣地亚哥分校的STARS（夏季学术研究成功培训）外展计划，并让来自校园内创新的普鲁斯学校和该地区其他高中的高中生参与其中。为了将影响力扩大到出版、教育和当地推广之外，项目成员将与“数据中心”项目团队密切合作，形成一个社区，进一步发展和发展这种方法，以培训学生进行以数据为中心的编程，并帮助实现增加数据和分析共享的承诺，以促进开放的科学合作和可复制的科学。该计划旨在鼓励开发和实施大胆的，新的，潜在的变革性模型，用于STEM研究生教育培训。研究生教育创新轨道专门致力于试点，测试和评估新颖，创新和潜在的变革性研究生教育方法。

项目成果

Aiding Collaborative Reuse of Computational Notebooks with Annotated Cell Folding

通过带注释的单元折叠帮助计算笔记本的协作重用

• DOI: 10.1145/3274419
• 发表时间: 2018
• 期刊: Proceedings of the ACM on Human-Computer Interaction
• 作者: Rule, Adam;Drosos, Ian;Tabard, Aurélien;Hollan, James D.
• 通讯作者: Hollan, James D.

Towards a dynamic multiscale personal information space: beyond application and document centered views of information

迈向动态多尺度个人信息空间：超越以应用程序和文档为中心的信息视图

• DOI: 10.1145/3397537.3397542
• 发表时间: 2020
• 期刊: Programming '20
• 作者: Fox, Amy Rae;Guo, Philip;Klokmose, Clemens Nylandsted;Dalsgaard, Peter;Satyanarayan, Arvind;Xia, Haijun;Hollan, James D.
• 通讯作者: Hollan, James D.

DS.js: Turn Any Webpage into an Example-Centric Live Programming Environment for Learning Data Science

DS.js：将任何网页变成以示例为中心的实时编程环境，用于学习数据科学

• DOI: 10.1145/3126594.3126663
• 发表时间: 2017
• 期刊: ACM User Interface Software and Technology Symposium
• 作者: Zhang, Xiong;Guo, Philip J.
• 通讯作者: Guo, Philip J.

RePlay: Contextually Presenting Learning Videos Across Software Applications

RePlay：跨软件应用程序根据上下文呈现学习视频

• DOI: 10.1145/3290605.3300527
• 发表时间: 2019
• 期刊: CHI2019
• 作者: Fraser, C. Ailie;Ngoon, Tricia J.;Dontcheva, Mira;Klemmer, Scott
• 通讯作者: Klemmer, Scott

How Computer Science and Statistics Instructors Approach Data Science Pedagogy Differently: Three Case Studies

计算机科学和统计学教师如何以不同的方式处理数据科学教学法：三个案例研究

• DOI: 10.1145/3478431.3499384
• 发表时间: 2022
• 期刊: SIGCSE 2022: Proceedings of the 53rd ACM Technical Symposium on Computer Science Education
• 作者: Lau, Sam;Nolan, Deborah;Gonzalez, Joseph;Guo, Philip J.
• 通讯作者: Guo, Philip J.