Moving a Flipped Class Online To Teach Python to Biomedical Ph.D. Students during COVID-19 and Beyond

ABSTRACT While quantitative analytical skills have always been a part of modern biomedical training, the big data revolution and digital research environment have increased the importance of computational approaches for biomedical graduate education. To address this growing need, Ph.D. programs have...

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Autores principales:	Nathalie A. Vladis, Bradley I. Coleman
Formato:	article
Lenguaje:	EN
Publicado:	American Society for Microbiology 2021
Materias:	flipped classroom remote teaching quantitative training graduate education Python problem-based learning Special aspects of education LC8-6691 Biology (General) QH301-705.5
Acceso en línea:	https://doaj.org/article/2021cf69dd2d4ca1b7255c758961087c
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spelling	oai:doaj.org-article:2021cf69dd2d4ca1b7255c758961087c2021-11-15T15:04:51ZMoving a Flipped Class Online To Teach Python to Biomedical Ph.D. Students during COVID-19 and Beyond10.1128/jmbe.00099-211935-78851935-7877https://doaj.org/article/2021cf69dd2d4ca1b7255c758961087c2021-09-01T00:00:00Zhttps://journals.asm.org/doi/10.1128/jmbe.00099-21https://doaj.org/toc/1935-7877https://doaj.org/toc/1935-7885ABSTRACT While quantitative analytical skills have always been a part of modern biomedical training, the big data revolution and digital research environment have increased the importance of computational approaches for biomedical graduate education. To address this growing need, Ph.D. programs have explored ways to integrate quantitative training into their existing curricula. However, these attempts have been hindered by limitations on total instructional time, faculty perceptions, and scalability. Here, we describe a flipped approach that combined a preexisting online course with group problem solving sessions to effectively and efficiently teach biomedical Ph.D. students key concepts in the use of the Python programming language for research. Following the COVID-19 related shutdowns in March 2020, we successfully adapted this approach to an all-online version where the formerly in-person problem-solving sessions occurred in small groups over Zoom. We found that students in both in-person and remote flipped formats showed increased confidence using Python and related this to their thesis research. Following the shift to the fully remote format, the lack of a physically present instructor seemed to increase students’ reliance on their classmates, which in turn promoted peer learning and support. This flexible, scalable approach to computational training may address the needs of many biomedical Ph.D. programs.Nathalie A. VladisBradley I. ColemanAmerican Society for Microbiologyarticleflipped classroomremote teachingquantitative traininggraduate educationPythonproblem-based learningSpecial aspects of educationLC8-6691Biology (General)QH301-705.5ENJournal of Microbiology & Biology Education, Vol 22, Iss 2 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	flipped classroom remote teaching quantitative training graduate education Python problem-based learning Special aspects of education LC8-6691 Biology (General) QH301-705.5
spellingShingle	flipped classroom remote teaching quantitative training graduate education Python problem-based learning Special aspects of education LC8-6691 Biology (General) QH301-705.5 Nathalie A. Vladis Bradley I. Coleman Moving a Flipped Class Online To Teach Python to Biomedical Ph.D. Students during COVID-19 and Beyond
description	ABSTRACT While quantitative analytical skills have always been a part of modern biomedical training, the big data revolution and digital research environment have increased the importance of computational approaches for biomedical graduate education. To address this growing need, Ph.D. programs have explored ways to integrate quantitative training into their existing curricula. However, these attempts have been hindered by limitations on total instructional time, faculty perceptions, and scalability. Here, we describe a flipped approach that combined a preexisting online course with group problem solving sessions to effectively and efficiently teach biomedical Ph.D. students key concepts in the use of the Python programming language for research. Following the COVID-19 related shutdowns in March 2020, we successfully adapted this approach to an all-online version where the formerly in-person problem-solving sessions occurred in small groups over Zoom. We found that students in both in-person and remote flipped formats showed increased confidence using Python and related this to their thesis research. Following the shift to the fully remote format, the lack of a physically present instructor seemed to increase students’ reliance on their classmates, which in turn promoted peer learning and support. This flexible, scalable approach to computational training may address the needs of many biomedical Ph.D. programs.
format	article
author	Nathalie A. Vladis Bradley I. Coleman
author_facet	Nathalie A. Vladis Bradley I. Coleman
author_sort	Nathalie A. Vladis
title	Moving a Flipped Class Online To Teach Python to Biomedical Ph.D. Students during COVID-19 and Beyond
title_short	Moving a Flipped Class Online To Teach Python to Biomedical Ph.D. Students during COVID-19 and Beyond
title_full	Moving a Flipped Class Online To Teach Python to Biomedical Ph.D. Students during COVID-19 and Beyond
title_fullStr	Moving a Flipped Class Online To Teach Python to Biomedical Ph.D. Students during COVID-19 and Beyond
title_full_unstemmed	Moving a Flipped Class Online To Teach Python to Biomedical Ph.D. Students during COVID-19 and Beyond
title_sort	moving a flipped class online to teach python to biomedical ph.d. students during covid-19 and beyond
publisher	American Society for Microbiology
publishDate	2021
url	https://doaj.org/article/2021cf69dd2d4ca1b7255c758961087c
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Moving a Flipped Class Online To Teach Python to Biomedical Ph.D. Students during COVID-19 and Beyond

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