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

在目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个重大挑战。这一挑战在化学反应、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，阻碍了学术界和工业界的创新。该项目提出了一种全面的方法，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、开发人员和讲师。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，并促进跨学科的编程能力。该项目提出了一种四管齐下的方法，涉及正式(学校、研讨会、课程模块)和非正式(黑客松)培训活动，涉及研究培训和更基本的本科生/研究生数据分析和材料建模计算方法培训。该方法设想了用户、开发人员和讲师之间的紧密联系，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开发人员社区，用于材料建模和一般的STEM代码开发。该项目将通过为不同的学习者提供接触最先进的技术和技能的不同背景来实现其目标，向他们展示如何通过结合理论和算法或通过公正地学习模式来克服复杂性的挑战。它将在学习者、开发人员和教师职业生涯的不同阶段通过多个连续的活动促进社区建设，旨在创造一个连贯和可持续的环境，使研究和教育发展可以在项目持续时间之外增长。使用计算工具作为特定学科课程的功能组件，并采用非正式的学习活动，使该项目能够克服由于不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。

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.