Combining low-code development with ChatGPT to novel no-code approaches: a focus-group study

Bibliographic Details
Main Author: Martins, José
Publication Date: 2023
Other Authors: Branco, Frederico, Mamede, Henrique
Format: Article
Language: eng
Source: Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
Download full: http://hdl.handle.net/10198/28847
Summary: Low-code tools are a trend in software development for business solutions due to their agility and ease of use. There are a certain number of vendors with such solutions. Still, in most Western countries, there is a clear need for the existence of greater quantities of certified and experienced professionals to work with those tools. This means that companies with more resources can attract and maintain those professionals, whilst other smaller organizations must rely on an endless search for this scarce resource. We will present and validate a model designed to transform ChatGPT into a low-code developer, addressing the demand for a more skilled human resource solution. This innovative tool underwent rigorous validation via a focus group study, engaging a panel of highly experienced experts. Their invaluable insights and feedback on the proposed model were systematically gathered and meticulously analysed.
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spelling Combining low-code development with ChatGPT to novel no-code approaches: a focus-group studyLow-codeNo-codeArtificial intelligenceSoftware modelsChatGPTLLMLow-code tools are a trend in software development for business solutions due to their agility and ease of use. There are a certain number of vendors with such solutions. Still, in most Western countries, there is a clear need for the existence of greater quantities of certified and experienced professionals to work with those tools. This means that companies with more resources can attract and maintain those professionals, whilst other smaller organizations must rely on an endless search for this scarce resource. We will present and validate a model designed to transform ChatGPT into a low-code developer, addressing the demand for a more skilled human resource solution. This innovative tool underwent rigorous validation via a focus group study, engaging a panel of highly experienced experts. Their invaluable insights and feedback on the proposed model were systematically gathered and meticulously analysed.ElsevierBiblioteca Digital do IPBMartins, JoséBranco, FredericoMamede, Henrique2023-10-30T14:49:09Z20232023-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10198/28847engMartins, José; Branco, Frederico; Mamede, Henrique (2023). Combining low-code development with ChatGPT to novel no-code approaches: a focus-group study. Intelligent Systems with Applications. ISSN 2667-3053. 20, p. 2002892667-305310.1016/j.iswa.2023.200289info:eu-repo/semantics/openAccessreponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiainstacron:RCAAP2025-02-25T12:20:11Zoai:bibliotecadigital.ipb.pt:10198/28847Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireinfo@rcaap.ptopendoar:https://opendoar.ac.uk/repository/71602025-05-28T11:47:38.469640Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiafalse
dc.title.none.fl_str_mv Combining low-code development with ChatGPT to novel no-code approaches: a focus-group study
title Combining low-code development with ChatGPT to novel no-code approaches: a focus-group study
spellingShingle Combining low-code development with ChatGPT to novel no-code approaches: a focus-group study
Martins, José
Low-code
No-code
Artificial intelligence
Software models
ChatGPT
LLM
title_short Combining low-code development with ChatGPT to novel no-code approaches: a focus-group study
title_full Combining low-code development with ChatGPT to novel no-code approaches: a focus-group study
title_fullStr Combining low-code development with ChatGPT to novel no-code approaches: a focus-group study
title_full_unstemmed Combining low-code development with ChatGPT to novel no-code approaches: a focus-group study
title_sort Combining low-code development with ChatGPT to novel no-code approaches: a focus-group study
author Martins, José
author_facet Martins, José
Branco, Frederico
Mamede, Henrique
author_role author
author2 Branco, Frederico
Mamede, Henrique
author2_role author
author
dc.contributor.none.fl_str_mv Biblioteca Digital do IPB
dc.contributor.author.fl_str_mv Martins, José
Branco, Frederico
Mamede, Henrique
dc.subject.por.fl_str_mv Low-code
No-code
Artificial intelligence
Software models
ChatGPT
LLM
topic Low-code
No-code
Artificial intelligence
Software models
ChatGPT
LLM
description Low-code tools are a trend in software development for business solutions due to their agility and ease of use. There are a certain number of vendors with such solutions. Still, in most Western countries, there is a clear need for the existence of greater quantities of certified and experienced professionals to work with those tools. This means that companies with more resources can attract and maintain those professionals, whilst other smaller organizations must rely on an endless search for this scarce resource. We will present and validate a model designed to transform ChatGPT into a low-code developer, addressing the demand for a more skilled human resource solution. This innovative tool underwent rigorous validation via a focus group study, engaging a panel of highly experienced experts. Their invaluable insights and feedback on the proposed model were systematically gathered and meticulously analysed.
publishDate 2023
dc.date.none.fl_str_mv 2023-10-30T14:49:09Z
2023
2023-01-01T00:00:00Z
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://hdl.handle.net/10198/28847
url http://hdl.handle.net/10198/28847
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv Martins, José; Branco, Frederico; Mamede, Henrique (2023). Combining low-code development with ChatGPT to novel no-code approaches: a focus-group study. Intelligent Systems with Applications. ISSN 2667-3053. 20, p. 200289
2667-3053
10.1016/j.iswa.2023.200289
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Elsevier
publisher.none.fl_str_mv Elsevier
dc.source.none.fl_str_mv reponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia
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