Systematic and Bibliometric Review on the Impact of Chatbots in Higher Education.

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In recent years, the use of chatbots in higher education has grown significantly, driven by advances in artificial intelligence and its ability to optimize teaching and learning processes. This paper presents a systematic literature review aimed at identifying the main trends, approaches, and findin...

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Detalles Bibliográficos
Autores: Gómez, Á.H., D., Gamboa-Cruzado, J., A.H., Velásquez-Vásquez, J., Ayala-Jara, C., López-Ramírez, B.C.
Formato: artículo
Fecha de Publicación:2025
Institución:Universidad Nacional de Cajamarca
Repositorio:UNC-Institucional
Lenguaje:inglés
OAI Identifier:oai:repositorio.unc.edu.pe:20.500.14074/9864
Enlace del recurso:http://hdl.handle.net/20.500.14074/9864
https://doi.org/10.13053/cys-29-4-6116
Nivel de acceso:acceso abierto
Materia:Chatbots, higher education
artificial intelligence
systematic literature review (SLR)
education
intelligent bots
learning
https://purl.org/pe-repo/ocde/ford#5.03.01
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spelling Gómez, Á.H.D.Gamboa-Cruzado, J.Gómez, Á.H.A.H.Velásquez-Vásquez, J.Ayala-Jara, C.López-Ramírez, B.C.2026-02-24T14:58:01Z2026-02-24T14:58:01Z2025http://hdl.handle.net/20.500.14074/9864https://doi.org/10.13053/cys-29-4-6116In recent years, the use of chatbots in higher education has grown significantly, driven by advances in artificial intelligence and its ability to optimize teaching and learning processes. This paper presents a systematic literature review aimed at identifying the main trends, approaches, and findings related to the use of chatbots in higher education. An exhaustive search was conducted across five highly reputable academic databases (Scopus, EBSCOhost, ScienceDirect, Taylor & Francis Online, and ARDI), yielding an initial total of 42,188 documents. After applying strict inclusion and exclusion criteria, 69 scientific papers were selected for detailed analysis. The findings reveal that the most widely used programming language in the development of educational chatbots is R (45.2%), followed by Python and Java (22.5% each). In addition, 66.6% of the analyzed papers were published in Q1 journals, reflecting high-quality academic output in this field. These results confirm the growing interest in the application of chatbots in higher education and open new lines of research focused on pedagogical integration, assessment of academic impact, and the enhancement of personalized learning through conversational artificial intelligence.application/pdfengInstituto Politecnico Nacional.https://www.scopus.com/pages/publications/105027741600urn:issn:14055546Computacion y Sistemas 2025; 29(4): 2171-2194info:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by/4.0/Chatbots, higher educationartificial intelligencesystematic literature review (SLR)educationintelligent botslearninghttps://purl.org/pe-repo/ocde/ford#5.03.01Systematic and Bibliometric Review on the Impact of Chatbots in Higher Education.info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionreponame:UNC-Institucionalinstname:Universidad Nacional de Cajamarcainstacron:UNCORIGINALSystematic_and_Bibliometric_Review_on_th.pdfSystematic_and_Bibliometric_Review_on_th.pdfapplication/pdf591101http://repositorio.unc.edu.pe/bitstream/20.500.14074/9864/1/Systematic_and_Bibliometric_Review_on_th.pdfe9d06dca1512e65b0995fa65be9e85afMD5120.500.14074/9864oai:repositorio.unc.edu.pe:20.500.14074/98642026-02-26 11:22:42.089Universidad Nacional de Cajamarcarepositorio@unc.edu.pe
dc.title.es_PE.fl_str_mv Systematic and Bibliometric Review on the Impact of Chatbots in Higher Education.
title Systematic and Bibliometric Review on the Impact of Chatbots in Higher Education.
spellingShingle Systematic and Bibliometric Review on the Impact of Chatbots in Higher Education.
Gómez, Á.H.
Chatbots, higher education
artificial intelligence
systematic literature review (SLR)
education
intelligent bots
learning
https://purl.org/pe-repo/ocde/ford#5.03.01
title_short Systematic and Bibliometric Review on the Impact of Chatbots in Higher Education.
title_full Systematic and Bibliometric Review on the Impact of Chatbots in Higher Education.
title_fullStr Systematic and Bibliometric Review on the Impact of Chatbots in Higher Education.
title_full_unstemmed Systematic and Bibliometric Review on the Impact of Chatbots in Higher Education.
title_sort Systematic and Bibliometric Review on the Impact of Chatbots in Higher Education.
author Gómez, Á.H.
author_facet Gómez, Á.H.
D.
Gamboa-Cruzado, J.
A.H.
Velásquez-Vásquez, J.
Ayala-Jara, C.
López-Ramírez, B.C.
author_role author
author2 D.
Gamboa-Cruzado, J.
A.H.
Velásquez-Vásquez, J.
Ayala-Jara, C.
López-Ramírez, B.C.
author2_role author
author
author
author
author
author
dc.contributor.author.fl_str_mv Gómez, Á.H.
D.
Gamboa-Cruzado, J.
Gómez, Á.H.
A.H.
Velásquez-Vásquez, J.
Ayala-Jara, C.
López-Ramírez, B.C.
dc.subject.es_PE.fl_str_mv Chatbots, higher education
artificial intelligence
systematic literature review (SLR)
education
intelligent bots
learning
topic Chatbots, higher education
artificial intelligence
systematic literature review (SLR)
education
intelligent bots
learning
https://purl.org/pe-repo/ocde/ford#5.03.01
dc.subject.ocde.es_PE.fl_str_mv https://purl.org/pe-repo/ocde/ford#5.03.01
description In recent years, the use of chatbots in higher education has grown significantly, driven by advances in artificial intelligence and its ability to optimize teaching and learning processes. This paper presents a systematic literature review aimed at identifying the main trends, approaches, and findings related to the use of chatbots in higher education. An exhaustive search was conducted across five highly reputable academic databases (Scopus, EBSCOhost, ScienceDirect, Taylor & Francis Online, and ARDI), yielding an initial total of 42,188 documents. After applying strict inclusion and exclusion criteria, 69 scientific papers were selected for detailed analysis. The findings reveal that the most widely used programming language in the development of educational chatbots is R (45.2%), followed by Python and Java (22.5% each). In addition, 66.6% of the analyzed papers were published in Q1 journals, reflecting high-quality academic output in this field. These results confirm the growing interest in the application of chatbots in higher education and open new lines of research focused on pedagogical integration, assessment of academic impact, and the enhancement of personalized learning through conversational artificial intelligence.
publishDate 2025
dc.date.accessioned.none.fl_str_mv 2026-02-24T14:58:01Z
dc.date.available.none.fl_str_mv 2026-02-24T14:58:01Z
dc.date.issued.fl_str_mv 2025
dc.type.es_PE.fl_str_mv info:eu-repo/semantics/article
dc.type.version.es_PE.fl_str_mv info:eu-repo/semantics/publishedVersion
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status_str publishedVersion
dc.identifier.uri.none.fl_str_mv http://hdl.handle.net/20.500.14074/9864
dc.identifier.doi.es_PE.fl_str_mv https://doi.org/10.13053/cys-29-4-6116
url http://hdl.handle.net/20.500.14074/9864
https://doi.org/10.13053/cys-29-4-6116
dc.language.iso.es_PE.fl_str_mv eng
language eng
dc.relation.ispartof.es_PE.fl_str_mv https://www.scopus.com/pages/publications/105027741600
urn:issn:14055546
Computacion y Sistemas 2025; 29(4): 2171-2194
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dc.publisher.es_PE.fl_str_mv Instituto Politecnico Nacional.
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instname:Universidad Nacional de Cajamarca
instacron:UNC
instname_str Universidad Nacional de Cajamarca
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institution UNC
reponame_str UNC-Institucional
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