Chatbots in science education: A scoping review of early empirical evidence

Chatbots are making a strong entry into education, supporting both students and teachers. This study aims to deepen the understanding of the educational use of chatbots in science education, including their advantages and limitations. A scoping review of the articles published up to January 1, 2025,...

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Detalhes bibliográficos
Autores: Calvo Utrilla, Mario, Paños Martínez, María Esther, Ruiz Gallardo, José Reyes
Formato: artículo
Fecha de publicación:2025
País:España
Recursos:Universidad de Castilla-La Mancha
Repositorio:RUIdeRA. Repositorio Institucional de la UCLM
OAI Identifier:oai:ruidera.uclm.es:10578/45565
Acesso em linha:https://doi.org/10.1007/s10956-025-10260-x
https://hdl.handle.net/10578/45565
Access Level:acceso abierto
Palavra-chave:Artificial intelligence
Chatbots
ChatGPT
Science teaching
Scoping review
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spelling Chatbots in science education: A scoping review of early empirical evidenceCalvo Utrilla, MarioPaños Martínez, María EstherRuiz Gallardo, José ReyesArtificial intelligenceChatbotsChatGPTScience teachingScoping reviewChatbots are making a strong entry into education, supporting both students and teachers. This study aims to deepen the understanding of the educational use of chatbots in science education, including their advantages and limitations. A scoping review of the articles published up to January 1, 2025, was conducted following PRISMA guidelines across the Web of Science, Scopus, and ERIC databases, using search terms related to science education and chatbots. From an initial pool of 608 articles, 40 met all inclusion criteria. Most of the selected studies were exploratory (32.5%), with fewer intervention-based designs. Chatbots in science education are promising tools but are still in their early stages, and this could explain the large number of exploratory studies found. ChatGPT is the most studied and has demonstrated excellent linguistic capabilities but needs to improve its scientific accuracy and analytical skills. Tutoring students is the most commonly found application of chatbots. They also have the potential to support teachers by reducing their workload, although empirical data are needed to confirm this. Integrating Artificial Intelligence literacy and critical thinking skills into curricula, alongside comprehensive teacher professional development, is crucial for the effective and responsible use of chatbots in science education.Springer202520252025info:eu-repo/semantics/articleapplication/pdfapplication/pdfhttps://doi.org/10.1007/s10956-025-10260-xhttps://hdl.handle.net/10578/45565reponame:RUIdeRA. Repositorio Institucional de la UCLMinstname:Universidad de Castilla-La ManchaInglés2022-GRIN-34471info:eu-repo/semantics/openAccessoai:ruidera.uclm.es:10578/455652026-05-27T07:36:41Z
dc.title.none.fl_str_mv Chatbots in science education: A scoping review of early empirical evidence
title Chatbots in science education: A scoping review of early empirical evidence
spellingShingle Chatbots in science education: A scoping review of early empirical evidence
Calvo Utrilla, Mario
Artificial intelligence
Chatbots
ChatGPT
Science teaching
Scoping review
title_short Chatbots in science education: A scoping review of early empirical evidence
title_full Chatbots in science education: A scoping review of early empirical evidence
title_fullStr Chatbots in science education: A scoping review of early empirical evidence
title_full_unstemmed Chatbots in science education: A scoping review of early empirical evidence
title_sort Chatbots in science education: A scoping review of early empirical evidence
dc.creator.none.fl_str_mv Calvo Utrilla, Mario
Paños Martínez, María Esther
Ruiz Gallardo, José Reyes
author Calvo Utrilla, Mario
author_facet Calvo Utrilla, Mario
Paños Martínez, María Esther
Ruiz Gallardo, José Reyes
author_role author
author2 Paños Martínez, María Esther
Ruiz Gallardo, José Reyes
author2_role author
author
dc.subject.none.fl_str_mv Artificial intelligence
Chatbots
ChatGPT
Science teaching
Scoping review
topic Artificial intelligence
Chatbots
ChatGPT
Science teaching
Scoping review
description Chatbots are making a strong entry into education, supporting both students and teachers. This study aims to deepen the understanding of the educational use of chatbots in science education, including their advantages and limitations. A scoping review of the articles published up to January 1, 2025, was conducted following PRISMA guidelines across the Web of Science, Scopus, and ERIC databases, using search terms related to science education and chatbots. From an initial pool of 608 articles, 40 met all inclusion criteria. Most of the selected studies were exploratory (32.5%), with fewer intervention-based designs. Chatbots in science education are promising tools but are still in their early stages, and this could explain the large number of exploratory studies found. ChatGPT is the most studied and has demonstrated excellent linguistic capabilities but needs to improve its scientific accuracy and analytical skills. Tutoring students is the most commonly found application of chatbots. They also have the potential to support teachers by reducing their workload, although empirical data are needed to confirm this. Integrating Artificial Intelligence literacy and critical thinking skills into curricula, alongside comprehensive teacher professional development, is crucial for the effective and responsible use of chatbots in science education.
publishDate 2025
dc.date.none.fl_str_mv 2025
2025
2025
dc.type.none.fl_str_mv info:eu-repo/semantics/article
format article
dc.identifier.none.fl_str_mv https://doi.org/10.1007/s10956-025-10260-x
https://hdl.handle.net/10578/45565
url https://doi.org/10.1007/s10956-025-10260-x
https://hdl.handle.net/10578/45565
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv 2022-GRIN-34471
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv Springer
publisher.none.fl_str_mv Springer
dc.source.none.fl_str_mv reponame:RUIdeRA. Repositorio Institucional de la UCLM
instname:Universidad de Castilla-La Mancha
instname_str Universidad de Castilla-La Mancha
reponame_str RUIdeRA. Repositorio Institucional de la UCLM
collection RUIdeRA. Repositorio Institucional de la UCLM
repository.name.fl_str_mv
repository.mail.fl_str_mv
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