The experience of teaching introductory programming skills to bioscientists in Brazil
Autor(a) principal: | |
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Data de Publicação: | 2021 |
Outros Autores: | , , , , , , , , , , , , , , , , , , , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Institucional da UNESP |
Texto Completo: | http://dx.doi.org/10.1371/journal.pcbi.1009534 http://hdl.handle.net/11449/229949 |
Resumo: | Computational biology has gained traction as an independent scientific discipline over the last years in South America. However, there is still a growing need for bioscientists, from different backgrounds, with different levels, to acquire programming skills, which could reduce the time from data to insights and bridge communication between life scientists and computer scientists. Python is a programming language extensively used in bioinformatics and data science, which is particularly suitable for beginners. Here, we describe the conception, organization, and implementation of the Brazilian Python Workshop for Biological Data. This workshop has been organized by graduate and undergraduate students and supported, mostly in administrative matters, by experienced faculty members since 2017. The workshop was conceived for teaching bioscientists, mainly students in Brazil, on how to program in a biological context. The goal of this article was to share our experience with the 2020 edition of the workshop in its virtual format due to the Coronavirus Disease 2019 (COVID- 19) pandemic and to compare and contrast this year's experience with the previous in-person editions. We described a hands-on and live coding workshop model for teaching introductory Python programming. We also highlighted the adaptations made from in-person to online format in 2020, the participants' assessment of learning progression, and general workshop management. Lastly, we provided a summary and reflections from our personal experiences from the workshops of the last 4 years. Our takeaways included the benefits of the learning from learners' feedback (LLF) that allowed us to improve the workshop in real time, in the short, and likely in the long term. We concluded that the Brazilian Python Workshop for Biological Data is a highly effective workshop model for teaching a programming language that allows bioscientists to go beyond an initial exploration of programming skills for data analysis in the medium to long term. Copyright: |
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The experience of teaching introductory programming skills to bioscientists in BrazilComputational biology has gained traction as an independent scientific discipline over the last years in South America. However, there is still a growing need for bioscientists, from different backgrounds, with different levels, to acquire programming skills, which could reduce the time from data to insights and bridge communication between life scientists and computer scientists. Python is a programming language extensively used in bioinformatics and data science, which is particularly suitable for beginners. Here, we describe the conception, organization, and implementation of the Brazilian Python Workshop for Biological Data. This workshop has been organized by graduate and undergraduate students and supported, mostly in administrative matters, by experienced faculty members since 2017. The workshop was conceived for teaching bioscientists, mainly students in Brazil, on how to program in a biological context. The goal of this article was to share our experience with the 2020 edition of the workshop in its virtual format due to the Coronavirus Disease 2019 (COVID- 19) pandemic and to compare and contrast this year's experience with the previous in-person editions. We described a hands-on and live coding workshop model for teaching introductory Python programming. We also highlighted the adaptations made from in-person to online format in 2020, the participants' assessment of learning progression, and general workshop management. Lastly, we provided a summary and reflections from our personal experiences from the workshops of the last 4 years. Our takeaways included the benefits of the learning from learners' feedback (LLF) that allowed us to improve the workshop in real time, in the short, and likely in the long term. We concluded that the Brazilian Python Workshop for Biological Data is a highly effective workshop model for teaching a programming language that allows bioscientists to go beyond an initial exploration of programming skills for data analysis in the medium to long term. Copyright:Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)Sao Carlos Institute of Physics University of Sao PauloDepartment of Genetics Luiz de Queiroz College of Agriculture University of Sao PauloDepartment of General and Applied Biology Sao Paulo State UniversityCenter of the Study of Social Insects Department of General and Applied Biology Institute of Biosciences of Rio Claro Sao Paulo State UniversityRibeirao Preto Medical School University of Sao PauloDepartment of Computer Science Federal University of Sao CarlosSchool of Natural Sciences Universidad del RosarioComputational Evolutionary and Systems Biology Lab Center for Nuclear Energy in Agriculture University of Sao PauloRegulatory Systems Biology Lab Center for Nuclear Energy in Agriculture University of Sao PauloBarretos Cancer HospitalPaulista School of Medicine Federal University of Sao PauloDepartment of Genetics Evolution Microbiology and Immunology Institute of Biology University of CampinasGenomics for Climate Change Research Center University of CampinasRoche Sequencing SolutionsDepartment of Infectious Diseases and Public Health Jockey Club College of Veterinary Medicine and Life Sciences City University of Hong KongInstitute of Biological Sciences Federal University of ParáDepartment of Informatics and Statistics Federal University of Santa CatarinaDepartment of Genetics and Evolution Federal University of Sao CarlosSchool of Pharmaceutical Sciences of Ribeirao Preto University of Sao PauloInstitute of Biology State University of CampinasDepartment of General and Applied Biology Sao Paulo State UniversityCenter of the Study of Social Insects Department of General and Applied Biology Institute of Biosciences of Rio Claro Sao Paulo State UniversityUniversidade de São Paulo (USP)Universidade Estadual Paulista (UNESP)Universidade Federal de São Carlos (UFSCar)Universidad del RosarioBarretos Cancer HospitalUniversidade Estadual de Campinas (UNICAMP)Roche Sequencing SolutionsCity University of Hong KongUniversidade Federal do Pará (UFPA)Universidade Federal de Santa Catarina (UFSC)Zuvanov, LuízaGarcia, Ana Letycia BassoCorrer, Fernando HenriqueBizarria, Rodolfo [UNESP]Da Costa Filho, Ailton PereiraDa Costa, Alisson HayasiThomaz, Andréa T.Pinheiro, Ana Lucia MendesRiano-Pachón, Diego MauricioWinck, Flavia VischiEsteves, Franciele Grego [UNESP]Margarido, Gabriel Rodrigues AlvesCasagrande, Giovanna Maria StanfocaFrajacomo, Henrique CordeiroMartins, LeonardoCavalheiro, Mariana FeitosaGrachet, Nathalia GrafDa Silva, Raniere Gaia CostaCerri, RicardoRamos, Rommel Thiago JucaDe Medeiros, Simone Daniela SartorioTavares, Thayana VieiraDos Santos, Renato Augusto Correa2022-04-29T08:36:47Z2022-04-29T08:36:47Z2021-11-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articlehttp://dx.doi.org/10.1371/journal.pcbi.1009534PLoS Computational Biology, v. 17, n. 11, 2021.1553-73581553-734Xhttp://hdl.handle.net/11449/22994910.1371/journal.pcbi.10095342-s2.0-85119916823Scopusreponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengPLoS Computational Biologyinfo:eu-repo/semantics/openAccess2022-04-29T08:36:47Zoai:repositorio.unesp.br:11449/229949Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-08-05T21:03:27.395926Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false |
dc.title.none.fl_str_mv |
The experience of teaching introductory programming skills to bioscientists in Brazil |
title |
The experience of teaching introductory programming skills to bioscientists in Brazil |
spellingShingle |
The experience of teaching introductory programming skills to bioscientists in Brazil Zuvanov, Luíza |
title_short |
The experience of teaching introductory programming skills to bioscientists in Brazil |
title_full |
The experience of teaching introductory programming skills to bioscientists in Brazil |
title_fullStr |
The experience of teaching introductory programming skills to bioscientists in Brazil |
title_full_unstemmed |
The experience of teaching introductory programming skills to bioscientists in Brazil |
title_sort |
The experience of teaching introductory programming skills to bioscientists in Brazil |
author |
Zuvanov, Luíza |
author_facet |
Zuvanov, Luíza Garcia, Ana Letycia Basso Correr, Fernando Henrique Bizarria, Rodolfo [UNESP] Da Costa Filho, Ailton Pereira Da Costa, Alisson Hayasi Thomaz, Andréa T. Pinheiro, Ana Lucia Mendes Riano-Pachón, Diego Mauricio Winck, Flavia Vischi Esteves, Franciele Grego [UNESP] Margarido, Gabriel Rodrigues Alves Casagrande, Giovanna Maria Stanfoca Frajacomo, Henrique Cordeiro Martins, Leonardo Cavalheiro, Mariana Feitosa Grachet, Nathalia Graf Da Silva, Raniere Gaia Costa Cerri, Ricardo Ramos, Rommel Thiago Juca De Medeiros, Simone Daniela Sartorio Tavares, Thayana Vieira Dos Santos, Renato Augusto Correa |
author_role |
author |
author2 |
Garcia, Ana Letycia Basso Correr, Fernando Henrique Bizarria, Rodolfo [UNESP] Da Costa Filho, Ailton Pereira Da Costa, Alisson Hayasi Thomaz, Andréa T. Pinheiro, Ana Lucia Mendes Riano-Pachón, Diego Mauricio Winck, Flavia Vischi Esteves, Franciele Grego [UNESP] Margarido, Gabriel Rodrigues Alves Casagrande, Giovanna Maria Stanfoca Frajacomo, Henrique Cordeiro Martins, Leonardo Cavalheiro, Mariana Feitosa Grachet, Nathalia Graf Da Silva, Raniere Gaia Costa Cerri, Ricardo Ramos, Rommel Thiago Juca De Medeiros, Simone Daniela Sartorio Tavares, Thayana Vieira Dos Santos, Renato Augusto Correa |
author2_role |
author author author author author author author author author author author author author author author author author author author author author author |
dc.contributor.none.fl_str_mv |
Universidade de São Paulo (USP) Universidade Estadual Paulista (UNESP) Universidade Federal de São Carlos (UFSCar) Universidad del Rosario Barretos Cancer Hospital Universidade Estadual de Campinas (UNICAMP) Roche Sequencing Solutions City University of Hong Kong Universidade Federal do Pará (UFPA) Universidade Federal de Santa Catarina (UFSC) |
dc.contributor.author.fl_str_mv |
Zuvanov, Luíza Garcia, Ana Letycia Basso Correr, Fernando Henrique Bizarria, Rodolfo [UNESP] Da Costa Filho, Ailton Pereira Da Costa, Alisson Hayasi Thomaz, Andréa T. Pinheiro, Ana Lucia Mendes Riano-Pachón, Diego Mauricio Winck, Flavia Vischi Esteves, Franciele Grego [UNESP] Margarido, Gabriel Rodrigues Alves Casagrande, Giovanna Maria Stanfoca Frajacomo, Henrique Cordeiro Martins, Leonardo Cavalheiro, Mariana Feitosa Grachet, Nathalia Graf Da Silva, Raniere Gaia Costa Cerri, Ricardo Ramos, Rommel Thiago Juca De Medeiros, Simone Daniela Sartorio Tavares, Thayana Vieira Dos Santos, Renato Augusto Correa |
description |
Computational biology has gained traction as an independent scientific discipline over the last years in South America. However, there is still a growing need for bioscientists, from different backgrounds, with different levels, to acquire programming skills, which could reduce the time from data to insights and bridge communication between life scientists and computer scientists. Python is a programming language extensively used in bioinformatics and data science, which is particularly suitable for beginners. Here, we describe the conception, organization, and implementation of the Brazilian Python Workshop for Biological Data. This workshop has been organized by graduate and undergraduate students and supported, mostly in administrative matters, by experienced faculty members since 2017. The workshop was conceived for teaching bioscientists, mainly students in Brazil, on how to program in a biological context. The goal of this article was to share our experience with the 2020 edition of the workshop in its virtual format due to the Coronavirus Disease 2019 (COVID- 19) pandemic and to compare and contrast this year's experience with the previous in-person editions. We described a hands-on and live coding workshop model for teaching introductory Python programming. We also highlighted the adaptations made from in-person to online format in 2020, the participants' assessment of learning progression, and general workshop management. Lastly, we provided a summary and reflections from our personal experiences from the workshops of the last 4 years. Our takeaways included the benefits of the learning from learners' feedback (LLF) that allowed us to improve the workshop in real time, in the short, and likely in the long term. We concluded that the Brazilian Python Workshop for Biological Data is a highly effective workshop model for teaching a programming language that allows bioscientists to go beyond an initial exploration of programming skills for data analysis in the medium to long term. Copyright: |
publishDate |
2021 |
dc.date.none.fl_str_mv |
2021-11-01 2022-04-29T08:36:47Z 2022-04-29T08:36:47Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://dx.doi.org/10.1371/journal.pcbi.1009534 PLoS Computational Biology, v. 17, n. 11, 2021. 1553-7358 1553-734X http://hdl.handle.net/11449/229949 10.1371/journal.pcbi.1009534 2-s2.0-85119916823 |
url |
http://dx.doi.org/10.1371/journal.pcbi.1009534 http://hdl.handle.net/11449/229949 |
identifier_str_mv |
PLoS Computational Biology, v. 17, n. 11, 2021. 1553-7358 1553-734X 10.1371/journal.pcbi.1009534 2-s2.0-85119916823 |
dc.language.iso.fl_str_mv |
eng |
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eng |
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PLoS Computational Biology |
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info:eu-repo/semantics/openAccess |
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openAccess |
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Scopus reponame:Repositório Institucional da UNESP instname:Universidade Estadual Paulista (UNESP) instacron:UNESP |
instname_str |
Universidade Estadual Paulista (UNESP) |
instacron_str |
UNESP |
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UNESP |
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Repositório Institucional da UNESP |
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Repositório Institucional da UNESP |
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Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP) |
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1808129279248039936 |