Collaborative Research: CyberTraining: Implementation: Medium: Training Users, Developers, and Instructors at the Chemistry/Physics/Materials Science Interface

协作研究：网络培训：实施：媒介：在化学/物理/材料科学界面培训用户、开发人员和讲师

• 批准号: 2321104
• 负责人: Francesco Paesani
• 金额: $ 33.33万
• 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: 2024
• 资助国家: 美国
• 起止时间: 2024-01-01 至 2027-12-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2321104&HistoricalAwards=false
• 关键词: Collaborative; Research; CyberTraining; Implementation; Medium

The training of students and researchers in computational tools and techniques is a significant challenge in the current educational system, which tends to prioritize analytical theory and experimental practice. This challenge is particularly prominent in interdisciplinary fields such as the study of chemical reactivity, materials interfaces, and materials modeling. Conventional approaches that rely on single-tool and single-application methods limit the range of applications and hinder innovation in academia and industry. This project proposes a comprehensive approach to address these limitations by offering formal and informal training events, including schools, workshops, course modules, and hackathons. The approach emphasizes the integration of users, developers, and instructors through feedback loops and community-building activities. The primary objectives are to establish a robust community of materials modeling developers and to enhance computational training at both undergraduate and graduate levels. The project seeks to recruit and train future leaders in materials modeling, foster community engagement, and promote coding literacy across disciplines.The project proposes a four-pronged approach involving formal (schools, workshops, course modules) and informal (hackathons) training events that address research training and more fundamental undergraduate/graduate training in computational methods for data analysis and materials modeling. The approach envisions a strong connection between users, developers, and instructors, encompassing feedback loops and community-building activities. The goal is to form a robust US-based community of developers for materials modeling and, generally, STEM code development. The project will achieve its aims by providing learners with various backgrounds exposure to state-of-the-art techniques and skills, showing them how to overcome the challenges of complexity by combining theories and algorithms or by unbiased learning of patterns. It will foster community-building among learners, developers, and instructors at different stages of their careers in multiple successive events designed to create a cohesive and sustainable environment where research and educational developments can grow beyond the project's duration. Using computational tools as functional components of discipline-specific curricula and adopting informal learning events allows the project to overcome common barriers given by feelings of non-belonging and low self-confidence.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.

在当前倾向于优先考虑分析理论和实验实践的教育体系中，对学生和研究人员进行计算工具和技术的培训是一项重大挑战。这一挑战在化学反应性、材料界面和材料建模等跨学科领域尤为突出。依赖单一工具和单一应用方法的传统方法限制了应用范围并阻碍了学术界和工业界的创新。该项目提出了一种综合方法，通过提供正式和非正式的培训活动（包括学校、研讨会、课程模块和黑客马拉松）来解决这些限制。该方法强调通过反馈循环和社区建设活动整合用户、开发人员和教师。主要目标是建立一个强大的材料建模开发人员社区，并加强本科生和研究生水平的计算培训。该项目旨在招募和培训材料建模方面的未来领导者，促进社区参与，并提高跨学科的编码素养。该项目提出了一种四管齐下的方法，包括正式（学校、研讨会、课程模块）和非正式（黑客马拉松）培训活动，解决数据分析和材料建模计算方法方面的研究培训和更基础的本科生/研究生培训。该方法设想了用户、开发人员和教师之间的紧密联系，包括反馈循环和社区建设活动。目标是在美国形成一个强大的材料建模开发者社区，以及一般而言的 STEM 代码开发社区。该项目将通过为不同背景的学习者提供最先进的技术和技能，向他们展示如何通过结合理论和算法或通过公正的模式学习来克服复杂性的挑战来实现其目标。它将在多个连续的活动中促进处于职业生涯不同阶段的学习者、开发人员和教师之间的社区建设，旨在创造一个有凝聚力和可持续的环境，使研究和教育发展能够在项目持续时间之外继续发展。使用计算工具作为特定学科课程的功能组成部分并采用非正式学习活动，使该项目能够克服因无归属感和缺乏自信而造成的常见障碍。该奖项反映了 NSF 的法定使命，并被认为值得通过以下方式获得支持：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。