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CyberTraining: DSE. The Code Maker: Computational Thinking for Engineers with Interactive, Contextual Learning

网络培训：DSE。

基本信息

批准号：
1730170
负责人：
Lorena Barba
金额：
$ 50万
依托单位：
George Washington University
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 2022-08-31
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=1730170&HistoricalAwards=false
关键词：
CyberTraining DSE.Code Maker Computational

项目摘要

The Code Maker is a new vision for educating engineers who can apply computational thinking to many endeavors. It is a program that embeds computational skills in the curriculum using learner-centered design, informed by the latest research in how people learn. The project will develop the curriculum and materials for interactive learning of computing, in context. The philosophy is to move from "learning to code" toward "coding to learn," so that computing becomes a natural tool for the new engineer to solve problems, investigate nature, design and build projects. The Code Maker serves the national interest by training engineers that are effective users of cyberinfrastructure. It serves NSF's mission - to promote the progress of science; to advance the national health, prosperity and welfare; to secure the national defense - by delivering needed intellectual infrastructure. The project is open source and open access. Locally, it builds community via maker-inspired activities and student support via learning assistants at the new George Washington (GW) STEM Works Lab. Outward-looking, the project will use an online platform to share the training widely, and will coach a close group of collaborators who bring the program to their respective institutions. The NSF funding will also support a thorough assessment of the program, continuous improvement, and dissemination of the results. The Code Maker will train computationally skilled engineers who are prepared to enter the workforce competitively, and ready to use computing effectively as a research tool if joining a graduate program in computational science and engineering.The Code Maker project will deliver eight or more learning modules, each consisting of a series of four or more lessons, written as a Jupyter Notebook. The modules will be available online and can be completed asynchronously or assigned as a graded course component. They will embed the learning in the existing courses of the engineering curriculum: mechanics, statistics, heat and mass transfer, and so on. Short term, the program will train 50 to 100 students at GW, impact similar numbers at partner institutions, and potentially reach hundreds via the online dissemination. The modules adopt a mastery-learning approach. The program will be supported by learning assistants and a program of maker-inspired events at a newly created space in the GW Library, the STEM Works Lab. It will use cloud infrastructure, both public and private: an instance of the Open edX learning platform on Amazon AWS that effectively allows running the program publicly as a MOOC; and a local JupyterHub server to eliminate installation friction and ensure a consistent compute environment for local students. The evaluation will apply a combination of 4-level training evaluation and a Technology Acceptance model.

Code Maker是一个新的愿景，旨在培养能够将计算思维应用于许多努力的工程师。这是一个采用以学习者为中心的设计将计算技能嵌入课程的项目，并参考了人们如何学习的最新研究。该项目将在上下文中为计算机的互动式学习开发课程和材料。其理念是从“从学习到编码”转向“从编码到学习”，这样计算就成为新工程师解决问题、研究自然、设计和构建项目的自然工具。代码制造者通过培训成为网络基础设施有效用户的工程师来服务于国家利益。它服务于NSF的使命——促进科学的进步；促进国家健康、繁荣和福利；通过提供必要的智力基础设施来确保国防安全。该项目是开源和开放访问的。在当地，它通过创客活动建立社区，并通过新乔治华盛顿（GW） STEM工作实验室的学习助理提供学生支持。从外部看，该项目将利用一个在线平台广泛分享培训内容，并将指导一组关系密切的合作者，他们将该项目带到各自的机构。NSF的资金还将支持对项目的全面评估、持续改进和结果的传播。代码制造者将培养计算技能熟练的工程师，他们准备进入有竞争力的劳动力市场，并准备好有效地使用计算作为研究工具，如果加入计算科学和工程的研究生课程。Code Maker项目将提供八个或更多的学习模块，每个模块由四个或更多的课程组成，以Jupyter Notebook的形式编写。这些模块将在网上提供，可以异步完成或作为分级课程的组成部分分配。他们将把所学内容嵌入工程课程的现有课程中：力学、统计学、热学和传质学等。短期内，该项目将在乔治华盛顿大学培训50至100名学生，影响到合作院校的类似人数，并可能通过在线传播影响到数百名学生。该模块采用掌握式学习方法。该项目将得到学习助理的支持，并在乔治华盛顿大学图书馆的一个新创建的空间，即STEM工作实验室，举办一个创客启发活动项目。它将使用公共和私有云基础设施：亚马逊AWS上的Open edX学习平台实例，可以有效地将该课程作为MOOC公开运行；和本地JupyterHub服务器，以消除安装摩擦，并确保本地学生的计算环境一致。评估将采用4级培训评估和技术接受模型的组合。