Publicación:
Una revisión bibliométrica de estudios sobre la aceptación de las tecnologías de inteligencia artificial en la enseñanza y el aprendizaje en la educación superior.

dc.contributor.authorCaycho Salas, Beatriz Del Carmen
dc.contributor.authorTrinidad Loli, Nicéforo Ladislao
dc.contributor.authorMorales Romero, Guillermo Pastor
dc.contributor.authorCarlos Hernán Flores-Velásquez
dc.contributor.authorSoledad Olivares-Zegarra
dc.contributor.authorCarlos Dávila-Ignacio
dc.contributor.authorJosé Antonio Arévalo-Tuesta
dc.contributor.authorIrma Aybar-Bellido
dc.contributor.authorMaritza Arones
dc.contributor.authorFlorcita Aldana-Trejo
dc.date.accessioned2025-08-15T15:28:06Z
dc.date.issued2024
dc.description.abstractThe growing incorporation of artificial intelligence (AI) tools in higher education (HE) has led to the use of indicators that allow the real impact of these tools to be identified in the teaching and learning process. In this sense, this study developed a bibliometric review on the acceptance of AI technologies in HE, providing an analysis of indicators on scientific production, with the aim of identifying prevalent thematic areas and knowledge gaps. From a methodological point of view, this study was carried out using a quantitative approach with a descriptive level, utilising 56 publications drawn from the Scopus database. The results show a sustained evolution with a growing trend in scientific production since 2021. The most predominant thematic area is evaluation of the acceptance of AI technologies in HE, making greater use of the Technology Acceptance Model (TAM) and the Unified Acceptance and Use of Technology theory (UTAUT). Therefore, it was concluded that the existing literature shows a sustained interest in investigating the acceptance of AI technologies due to the importance of determining the impact generated by their applications in different contexts or scenarios of the reality of HE in regard to the extent that AI technology is developed. This is because, on some occasions, its application does not necessarily lead to meeting the expectations raised in the teaching and learning processes. Finally, the gaps that need to be addressed in future research are "cultural and contextual diversity in AI acceptance", "emerging models of AI acceptance", and "critical elements influencing the acceptance of AI technologies", in HE. © Authors.
dc.identifier.doi10.26803/ijlter.23.3.14
dc.identifier.scopus2-s2.0-85189133708
dc.identifier.urihttps://cris.une.edu.pe/handle/001/655
dc.identifier.uuid6ed61b74-2803-4b47-8110-cf71a1e1da1e
dc.language.isoen
dc.publisherSociety for Research and Knowledge Management
dc.relation.citationissue3
dc.relation.citationvolume23
dc.relation.ispartofInternational Journal of Learning, Teaching and Educational Research
dc.rightshttp://purl.org/coar/access_right/c_abf2
dc.subjectartificial intelligence
dc.subjectbibliometric review
dc.subjecthigher education
dc.subjecttechnology acceptance
dc.titleUna revisión bibliométrica de estudios sobre la aceptación de las tecnologías de inteligencia artificial en la enseñanza y el aprendizaje en la educación superior.
dc.typehttp://purl.org/coar/resource_type/c_dcae04bc
dspace.entity.typePublication
oaire.citation.endPage292
oaire.citation.startPage275
organization.acronymFACE-UNE
organization.acronymFAC-UNE
organization.acronymFAC-UNE
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person.affiliation.nameFacultad de Ciencias Empresariales
person.affiliation.nameFacultad de Ciencias
person.affiliation.nameFacultad de Ciencias
person.identifier.orcid0000-0002-6959-1043
person.identifier.orcid0000-0002-0630-6348
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relation.isAuthorOfPublication.latestForDiscoverycca3352c-11dc-478b-b7d0-701e8cad279f

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