91-6 Cracking the Code: An Evidence-Based Approach to Teaching Python in an Undergraduate Earth Science Setting

Session: Current Advances in Geoscience Education Research

Presenting Author:

Katy Christensen

Authors:

Christensen, Katy Marie ¹, Campbell, Ethan C.², Nuwer, Mikelle³, Ahuja, Amrita⁴, Boram, Owen⁵, Liu, Junzhe⁶, Miller, Reese⁷, Osuna, Isabelle⁸, Riser, Stephen C.⁹

(1) Institute of Arctic and Alpine Resarch, University of Colorado Boulder, Boulder, Colorado, USA, (2) Polar Science Center, University of Washington Seattle, Seattle, Washington, USA, (3) School of Oceanography, University of Washington Seattle, Seattle, WA, USA, (4) University of Washington Seattle, Seattle, Washington, USA, (5) University of Washington Seattle, Seattle, Washington, USA, (6) lamont-doherty earth observatory, Columbia University, Palisades, New York, USA, (7) University of Washington Seattle, Seattle, Washington, USA, (8) School of Earth and Atmospheric Sciences, Georgia Tech, Atlanta, Georgia, USA, (9) School of Oceanography, University of Washington Seattle, Seattle, Washington, USA,

Abstract:

Modern earth science research requires the manipulation, visualization, and interpretation of an ever-growing volume of data. For these analyses, scientific programming has become an essential tool that must be taught in every geoscience curriculum. However, few discipline-specific instructional approaches have been documented and assessed for their effectiveness in equipping geoscience undergraduate students with coding skills. Here we report on an evidence-based redesign of an introductory Python programming course, taught fully remotely in 2020 in the School of Oceanography at the University of Washington. Fundamental Python syntax and commonly used functions from climate-related disciplines were taught using cloud-based notebooks. Key components of the course included a flipped structure, active learning activities, an individualized final research project, and a focus on creating an accessible learning environment. By analyzing data from survey responses, online learning platforms, student work, assessments, and a focus group, we conclude that this instructional design facilitated learning and supported self-guided scientific inquiry. Students with less or no prior exposure to coding achieved similar success as peers with more experience, an outcome likely mediated by higher engagement with course resources. We believe that the constructivist approach to teaching introductory programming and data literacy that we present could be broadly applicable across the earth sciences and in other scientific domains.

Geological Society of America Abstracts with Program. Vol. 57, No. 6, 2025

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