Collaborative Research: CyberTraining: Implementation: Medium: FOUNT: Scaffolded, Hands-On Learning for a Data-Centric Future

协作研究：网络培训：实施：媒介：FOUNT：支架式实践学习，打造以数据为中心的未来

• 批准号: 2230077
• 负责人: Katarzyna Keahey
• 金额: $ 26.7万
• 依托单位: University of Chicago
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-10-01 至 2025-09-30
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2230077&HistoricalAwards=false
• 关键词: Collaborative; Research; CyberTraining; Implementation; Medium

Data informs decisions throughout our lives, and its importance keeps growing in a data-centric society and future. Scientists, educators, students, and the workforce at large require advanced skills to learn how to manage and process massive amounts of data efficiently and accurately. The nation's future as a global leader of innovations depends on having a large, versatile, and adaptable data-proficient workforce. Training this workforce, however, is challenging and requires significant hands-on skills in data systems where the constantly evolving hardware architectures, networking technologies, or changing price-performance ratios create unprecedented opportunities but also an urgent need for thorough and ongoing education in topics ranging from data acquisition, computer networking, storage systems, machine learning and data analytics, and visualization.This project develops a FOUNT of scaffolded, educational modules, or courselets, in the rapidly developing field of data systems, that provide shared educational content executable on Chameleon and other open clouds and testbeds. The courselets are based on the concept of literate programming and enable students to explore concepts and methods taught in the classroom via hands-on exercises – and then modify and extend those exercises in various ways to deepen their understanding and explore new ideas. Students can find relevant courselets through a content hub, integrated with open clouds and testbeds, so that they can deploy them “with one click”, making exploration-based learning readily available. Ultimately, the project aims to translate its experience of creating, teaching, supporting, and improving courselets into a set of best practices, and build a vibrant community of students, teachers – and contributors across all types of academic institutions, and thereby create a model of digital sharing that will improve availability of digital educational content to all members of our society.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

数据在我们的一生中为决策提供信息，在以数据为中心的社会和未来，其重要性不断增长。科学家、教育工作者、学生和广大劳动力需要先进的技能来学习如何高效、准确地管理和处理大量数据。美国作为全球创新领导者的未来取决于拥有一支庞大、多才多艺、适应性强、精通数据的员工队伍，然而，培训这支员工队伍具有挑战性，需要掌握数据系统方面的大量实践技能，其中硬件架构、网络不断发展。技术，或改变性价比比率创造了前所未有的机会，但也迫切需要对数据采集、计算机网络、存储系统、机器学习和数据分析以及可视化等主题进行全面和持续的教育。该项目开发了一系列脚手架、教育模块或课程，在快速发展的数据系统领域，提供可在 Chameleon 和其他开放云和测试平台上执行的共享教育内容。这些课程基于文学编程的概念，使学生能够通过实践探索课堂上教授的概念和方法。练习——然后通过各种方式修改和扩展这些练习，以加深理解并探索新的想法。学生可以通过内容中心找到相关的课程，并与开放云和测试床集成，以便他们可以“一键”部署，进行探索。最终，该项目旨在将其创建、教学、支持和改进课程的经验转化为一套最佳实践，并建立一个由学生、教师和所有类型学术机构的贡献者组成的充满活力的社区。 ，从而创建一个数字共享模型，该模型将改善为我们社会的所有成员提供数字教育内容。该奖项反映了 NSF 的法定使命，并通过使用基金会的智力价值和更广泛的影响审查标准进行评估，被认为值得支持。