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Collaborative Research: Promoting Computational Literacy in Biochemistry and Molecular Biology Education
NSF
About This Grant
This project aims to serve the national interest by preparing faculty members to teach students the computational skills they need to join the workforce, ready to take on the next generation of scientific challenges. "Big data" fields (where the amount of data is too large to be analyzed with Excel), such as bioinformatics, computational biology, protein design, and drug design, all rely on computational skills. In addition, using computers as research and information tools is recognized by the American Society of Biochemistry and Molecular Biology (ASBMB) as a necessary skill for Biochemistry and Molecular Biology (BMB) curricula. Thus, developing computational literacy in BMB students is important for the next generation of scientists to fully participate in evolving scientific fields. This project is designed to identify the computational needs of the BMB community and to develop and deliver virtual workshops and coding exercises related to BMB fields. These workshops and videos will be made freely available on sites such as GitHub and YouTube to increase the reach of this project beyond those who are able to attend the live, virtual workshops. There is currently no single source of information or exercises to train BMB faculty to teach computational literacy through coding exercises. Likewise, no tools currently exist to assess the needs and attitudes of the BMB community towards building computational literacy. The project team plans to develop a series of coding exercises and workshop materials freely accessible via GitHub and YouTube, which are designed to train BMB faculty to teach coding using Google Colab, an easy-to-use, AI-assisted coding environment. The project team plans to host three types of virtual workshops that will each be delivered twice during the project: Introductory, Learning to Code, and Teaching with Code. Workshop sessions will include topics such as working with dataframes, plotting, protein sequence analysis, and preparing to teach with live coding. This project plans to identify the evolving needs of the BMB community, provide insights into the current uses of computation in BMB curricula, and create widely accessible workshops and materials tailored to the BMB community. This will enable instructors to integrate computation effectively into their courses and will establish a foundational understanding of computational literacy in BMB curricula. Thus, this project plans to serve to advance computational literacy in BMB education and adjacent fields, such as biology and chemistry, to better prepare the next generation of scientists to tackle important biological problems using computational tools. The NSF IUSE: EDU Program supports research and development projects to improve the effectiveness of STEM education for all students. Through the Engaged Student Learning track, the program supports the creation, exploration, and implementation of promising practices and tools. 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.
Focus Areas
Eligibility
How to Apply
Up to $318K
2028-09-30
One-time $749 fee · Includes AI drafting + templates + PDF export
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