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...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
American Society for Microbiology
2021-09-01
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| Series: | Journal of Microbiology & Biology Education |
| Subjects: | |
| Online Access: | https://journals.asm.org/doi/10.1128/jmbe.00099-21 |
| _version_ | 1818824734329012224 |
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| author | Nathalie A. Vladis Bradley I. Coleman |
| author_facet | Nathalie A. Vladis Bradley I. Coleman |
| author_sort | Nathalie A. Vladis |
| collection | DOAJ |
| 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. |
| first_indexed | 2024-12-19T00:00:35Z |
| format | Article |
| id | doaj.art-2021cf69dd2d4ca1b7255c758961087c |
| institution | Directory Open Access Journal |
| issn | 1935-7877 1935-7885 |
| language | English |
| last_indexed | 2024-12-19T00:00:35Z |
| publishDate | 2021-09-01 |
| publisher | American Society for Microbiology |
| record_format | Article |
| series | Journal of Microbiology & Biology Education |
| spelling | doaj.art-2021cf69dd2d4ca1b7255c758961087c2022-12-21T20:46:27ZengAmerican Society for MicrobiologyJournal of Microbiology & Biology Education1935-78771935-78852021-09-0122210.1128/jmbe.00099-21Moving a Flipped Class Online To Teach Python to Biomedical Ph.D. Students during COVID-19 and BeyondNathalie A. Vladis0Bradley I. Coleman1Department of Biomedical Informatics, Harvard Medical School, Boston, Massachusetts, USACurriculum Fellows Program, Harvard Medical School, Boston, Massachusetts, USAABSTRACT 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.https://journals.asm.org/doi/10.1128/jmbe.00099-21flipped classroomremote teachingquantitative traininggraduate educationPythonproblem-based learning |
| spellingShingle | Nathalie A. Vladis Bradley I. Coleman Moving a Flipped Class Online To Teach Python to Biomedical Ph.D. Students during COVID-19 and Beyond Journal of Microbiology & Biology Education flipped classroom remote teaching quantitative training graduate education Python problem-based learning |
| title | 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_short | 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 |
| topic | flipped classroom remote teaching quantitative training graduate education Python problem-based learning |
| url | https://journals.asm.org/doi/10.1128/jmbe.00099-21 |
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