| NSF Org: |
OAC Office of Advanced Cyberinfrastructure (OAC) |
| Recipient: |
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| Initial Amendment Date: | August 31, 2023 |
| Latest Amendment Date: | August 31, 2023 |
| Award Number: | 2321102 |
| Award Instrument: | Standard Grant |
| Program Manager: |
Sharmistha Bagchi-Sen
shabagch@nsf.gov (703)292-8104 OAC Office of Advanced Cyberinfrastructure (OAC) CSE Directorate for Computer and Information Science and Engineering |
| Start Date: | January 1, 2024 |
| End Date: | December 31, 2027 (Estimated) |
| Total Intended Award Amount: | $333,621.00 |
| Total Awarded Amount to Date: | $333,621.00 |
| Funds Obligated to Date: |
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| History of Investigator: |
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| Recipient Sponsored Research Office: |
1910 UNIVERSITY DR BOISE ID US 83725-0001 (208)426-1574 |
| Sponsor Congressional District: |
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| Primary Place of Performance: |
1910 UNIVERSITY DR BOISE ID US 83725-0001 |
| Primary Place of
Performance Congressional District: |
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| Unique Entity Identifier (UEI): |
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| Parent UEI: |
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| NSF Program(s): | CyberTraining - Training-based |
| Primary Program Source: |
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| Program Reference Code(s): |
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| Program Element Code(s): |
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| Award Agency Code: | 4900 |
| Fund Agency Code: | 4900 |
| Assistance Listing Number(s): | 47.070 |
ABSTRACT
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.
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