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.

数据在我们的生活中为决策提供信息，在以数据为中心的社会和未来，数据的重要性不断增长。科学家、教育工作者、学生和广大员工都需要高级技能来学习如何高效、准确地管理和处理海量数据。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、精通数据的劳动力队伍。然而，培训这些劳动力是具有挑战性的，需要大量的数据系统实践技能，其中不断发展的硬件体系结构、网络技术或不断变化的性价比创造了前所未有的机会，但也迫切需要从数据采集、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彻底和持续的教育。该项目在快速发展的数据系统领域开发了大量脚手架、教育模块或课程，提供可在变色龙和其他开放云和测试床上执行的共享教育内容。这些课程基于识字编程的概念，使学生能够通过动手练习探索课堂上教授的概念和方法-然后以各种方式修改和扩展这些练习，以加深他们的理解和探索新的想法。学生可以通过内容中心找到相关的课程，与开放的云和试验床相结合，这样他们就可以“一键”部署它们，让基于探索的学习变得唾手可得。最终，该项目旨在将其在创建、教学、支持和改进课程方面的经验转化为一系列最佳实践，并在所有类型的学术机构中建立一个由学生、教师和贡献者组成的充满活力的社区，从而创建一个数字共享的模式，从而改善我们社会所有成员的数字教育内容的可用性。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。