Introducing Students to Scientific Python for Atmospheric Science

Arms, Sean C.; Chastang, Julien; Grover, Maxwell; Thielen, Jonathan E.; Wilson, Mark; Dirks, Douglas

doi:10.1175/bams-d-20-0069.1

Cited by 3 publications

(2 citation statements)

References 6 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Even in courses that more extensively utilize programming within activity modules, such as those distributed by Project EDDIE (Environmental Data-Driven Inquiry and Exploration), pre-written code is usually provided to students (O'Reilly et al, 2022). In this void, brief but intensive hands-on workshops like those offered by Software Carpentry (https://software-carpentry.org; Wilson, 2016), Data Carpentry (https://datacarpentry.org/; Irving, 2019), and scientific societies (e.g., Arms et al, 2020) have provided crucial training to young scientists. These short workshops, however, give learners limited opportunities to apply new coding skills to their own research in a supervised setting.…”

Section: Introductionmentioning

confidence: 99%

Cracking the code: An evidence-based approach to teaching Python in an undergraduate earth science setting

Campbell,

Christensen,

Nuwer

et al. 2023

Preprint

View full text Add to dashboard Cite

Scientific programming has become increasingly essential for manipulating, visualizing, and interpreting the large volumes of data acquired in earth science research. Yet few domain-specific instructional approaches have been documented and assessed for their effectiveness in equipping geoscience undergraduate students with coding and data literacy 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. Key components included a flipped structure, activities infused with active learning, an individualized final research project, and a focus on creating an accessible learning environment. Cloud-based notebooks were used to teach fundamental Python syntax as well as functions from packages widely used in climate-related disciplines. By analyzing quantitative and qualitative student metrics from online learning platforms, surveys, assignments, and a student focus group, we conclude that the instructional design facilitated student learning and supported self-guided scientific inquiry. Students with less or no prior exposure to coding achieved similar success to peers with more previous experience, an outcome likely mediated by high engagement with course resources. We believe that the constructivist approach to teaching introductory programming and data analysis that we present could be broadly applicable across the earth sciences and in other scientific domains.

show abstract

Section: Introductionmentioning

confidence: 99%

Cracking the code: An evidence-based approach to teaching Python in an undergraduate earth science setting

Campbell,

Christensen,

Nuwer

et al. 2023

Preprint

View full text Add to dashboard Cite

show abstract

“…By doing that we follow the "make it right -then make it fast" philosophy, placing clarity as our primary goal. Python is frequently used in atmospheric science in general [57] and in RT code development in particular (e.g. refer to websites of libRadtran, 9 SASKTRAN, 10 or XRTM 11 ), but mostly as an interface or wrapper to an RT solver traditionally developed in Fortran and/or C [58].…”

Section: Introductionmentioning

confidence: 99%