The experience of teaching introductory programming skills to bioscientists in Brazil

Detalhes bibliográficos
Autor(a) principal: Zuvanov, Luíza
Data de Publicação: 2021
Outros Autores: 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
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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spelling 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
language eng
dc.relation.none.fl_str_mv PLoS Computational Biology
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.source.none.fl_str_mv Scopus
reponame:Repositório Institucional da UNESP
instname:Universidade Estadual Paulista (UNESP)
instacron:UNESP
instname_str Universidade Estadual Paulista (UNESP)
instacron_str UNESP
institution UNESP
reponame_str Repositório Institucional da UNESP
collection Repositório Institucional da UNESP
repository.name.fl_str_mv Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)
repository.mail.fl_str_mv
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