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: 2321103
• 负责人: Michele Pavanello
• 金额: $ 33.3万
• 依托单位: Rutgers University Newark
• 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=2321103&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.

在计算工具和技术方面对学生和研究人员的培训是当前教育系统的重大挑战，该系统倾向于优先考虑分析理论和实验实践。在跨学科领域（例如化学反应性，材料界面和材料建模的研究）中，这一挑战尤为突出。依靠单芯和单次申请方法的常规方法限制了应用程序和行业的应用范围和阻碍创新。该项目提出了一种全面的方法来解决这些限制，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。该方法通过反馈循环和社区建设活动强调用户，开发人员和讲师的整合。主要目标是建立强大的材料建模开发人员社区，并在本科和研究生级别增强计算培训。该项目旨在招募和培训未来的领导者在材料建模，促进社区参与并促进跨学科的编码素养。该项目提出了涉及正式（学校，讲习班，课程模块）和非正式（Hackathons）培训活动的四管齐下的方法，以探讨研究培训和更多基本研究培训以及对计算机分析和材料模型的研究生/研究生培训。该方法设想了用户，开发人员和讲师之间的密切联系，包括反馈循环和社区建设活动。目的是建立一个基于美国的强大开发人员社区，用于材料建模，并且通常是STEM代码开发。该项目将通过为学习者提供各种背景的最先进技术和技能，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。它将在其职业生涯的不同阶段的学习者，开发人员和讲师之间在多个连续的活动中促进社区建设，旨在创造一个凝聚力和可持续的环境，研究和教育发展可以超越项目的持续时间。使用计算工具作为学科特异性课程的功能组成部分，并采用非正式的学习活动，可以通过非信仰和低自信心的感觉来克服常见的障碍。该奖项反映了NSF的法定任务，并通过该基金会的智力优点和广泛的影响来评估NSF的法定任务，并被认为是值得的。