Exploring the nexus of academic integrity and artificial intelligence in higher education: a bibliometric analysis

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dc.article.number24
dc.catalogadorpva
dc.contributor.authorAvello Sáez, Daniela Margot
dc.contributor.authorAranguren Zurita, Samuel
dc.date.accessioned2025-09-29T19:34:15Z
dc.date.available2025-09-29T19:34:15Z
dc.date.issued2025
dc.date.updated2025-08-31T00:06:03Z
dc.description.abstractBackground Artificial intelligence has created new opportunities in higher education, enhancing teaching and learning methods for both students and educators. However, it has also posed challenges to academic integrity. Objective To describe the evolution of scientific production on academic integrity and artificial intelligence in higher education. Methodology A bibliometric analysis was carried out using VOSviewer software and the Bibliometrix package in R. A total of 467 documents published between 2017 and 2025, retrieved from the Web of Science database, were analyzed. Results The analysis reveals a rapid expansion of the field, with an annual growth rate of 71.97%, concentrated in journals specializing in education, academic ethics, and technology. The field has evolved from a focus on the use of artificial intelligence in dishonest practices to the study of its integration in higher education. Four main lines of research were identified: the impact and adoption of artificial intelligence, implications for students, academic dishonesty, and associated psychological factors. Conclusions The field is at an early stage of development but is expanding rapidly, albeit with fragmented evolution, limited collaboration between research teams, and high editorial dispersion. The analysis shows a predominance of descriptive approaches, leaving room for the development of theoretical frameworks. Originality or value This study provides an overview and updated of the evolution of research on artificial intelligence and academic integrity, identifying trends, collaborations, and conceptual gaps. It highlights the need to promote theoretical reflection to guide future practice and research on the ethical use of artificial intelligence in higher education.
dc.fechaingreso.objetodigital2025-08-31
dc.format.extent14 páginas
dc.fuente.origenBiomed Central
dc.identifier.citationInternational Journal for Educational Integrity. 2025 Aug 29;21(1):24
dc.identifier.doi10.1007/s40979-025-00199-2
dc.identifier.issn1833-2595
dc.identifier.urihttps://doi.org/10.1007/s40979-025-00199-2
dc.identifier.urihttps://repositorio.uc.cl/handle/11534/105816
dc.information.autorucDepartamento de Ciencias de la Salud; Avello Sáez, Daniela Margot; S/I; 1219045
dc.issue.numero1
dc.language.isoen
dc.nota.accesocontenido completo
dc.publisherSpringer Nature
dc.revistaInternational Journal for Educational Integrity
dc.rightsacceso abierto
dc.rights.holderThe Author(s)
dc.rights.licenseAttribution-NonCommercial-NoDerivatives 4.0 International
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subjectAcademic integrity
dc.subjectArtificial intelligence
dc.subjectHigher education
dc.subjectBibliometric analysis
dc.subjectAcademic dishonesty
dc.subject.ddc370
dc.subject.deweyEducaciónes_ES
dc.subject.ods04 Quality education
dc.subject.odspa04 Educación de calidad
dc.titleExploring the nexus of academic integrity and artificial intelligence in higher education: a bibliometric analysis
dc.typeartículo de revisión
dc.volumen21
sipa.codpersvinculados1219045
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