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Data Science Education in Undergraduate Physics: Lessons Learned from a Community of Practice

Published

Author(s)

Karan Shah, Julie Butler, Alexis Knaub, Anil Zenginoglu, William Ratcliff, Mohammad Soltanieh-ha

Abstract

It is becoming increasingly important that physics educators equip their students with the skills to work with data effectively. However, many educators may lack the necessary training and expertise in data science to teach these skills. To address this gap, we created the Data Science Education Community of Practice (DSECOP), bringing together graduate students and physics educators from different institutions and backgrounds to share best practices and lessons learned from integrating data science into undergraduate physics education. In this article, we present insight and experiences from this community of practice, highlighting key strategies and challenges in incorporating data science into the introductory physics curriculum. Our goal is to provide guidance and inspiration to educators who seek to integrate data science into their teaching, helping to prepare the next generation of physicists for a data-driven world. # 2024 Published under an exclusive license by American Association of Physics Teachers.
Citation
American Journal of Physics
Volume
92

Keywords

education, data science, physics

Citation

Shah, K. , Butler, J. , Knaub, A. , Zenginoglu, A. , Ratcliff, W. and Soltanieh-ha, M. (2024), Data Science Education in Undergraduate Physics: Lessons Learned from a Community of Practice, American Journal of Physics, [online], https://doi.org/10.1119/5.0203846, https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=957340 (Accessed December 13, 2024)

Issues

If you have any questions about this publication or are having problems accessing it, please contact reflib@nist.gov.

Created September 1, 2024, Updated November 21, 2024