Combining low-code development with ChatGPT to novel no-code approaches: a focus-group study
Main Author: | |
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Publication Date: | 2023 |
Other Authors: | , |
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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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 |
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info:eu-repo/semantics/openAccess |
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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 |
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