Data science education in undergraduate physics: Lessons learned from a community of practice

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.

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Institutions

Publication Details

Journal
American Journal of Physics
Published
2024-08-22
DOI
https://doi.org/10.1119/5.0203846
Citations
3
Primary Topic
Scientific Computing and Data Management
Type
article
Field-Weighted Citation Impact
3.15

Funders

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article

Data science education in undergraduate physics: Lessons learned from a community of practice

J. Corey Butler, Karan Shah, Anıl Zenginoğlu, Mohammad Soltanieh-ha et al.
3 citations
American Journal of Physics
Scientific Computing and Data Management
3.15
article

Data science education in undergraduate physics: Lessons learned from a community of practice

J. Corey Butler, Karan Shah, Anıl Zenginoğlu, Mohammad Soltanieh-ha, Alexis V. Knaub, William Ratcliff
article en
3 citations

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.

American Journal of PhysicsVol. 92(9)
University of Mount Union (US), Boston University (US), National Institute of Standards and Technology (US), Helmholtz-Zentrum Dresden-Rossendorf (DE), American Association of Physics Teachers (US), Center for Advanced Systems Understanding (DE), NIST Center for Neutron Research (US), University of Maryland, College Park (US)
National Science Foundation, American Physical Society
Quality Education
Openalex Percentile: Top 7%
Scientific Computing and Data Management
3.15
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