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dc.contributor.authorBannister, Peter
dc.contributor.authorAlcalde Peñalver, Elena
dc.contributor.authorSantamaría Urbieta, Alexandra
dc.date2023
dc.date.accessioned2024-02-13T15:24:49Z
dc.date.available2024-02-13T15:24:49Z
dc.identifier.citationBannister, P., Alcalde Peñalver, E. and Santamaría Urbieta, A. (2023), "Transnational higher education cultures and generative AI: a nominal group study for policy development in English medium instruction", Journal for Multicultural Education, Vol. ahead-of-print No. ahead-of-print. https://doi.org/10.1108/JME-10-2023-0102es_ES
dc.identifier.issn2053-535X
dc.identifier.urihttps://reunir.unir.net/handle/123456789/16061
dc.description.abstractPurpose: This purpose of this paper is to report on the development of an evidence-informed framework created to facilitate the formulation of generative artificial intelligence (GenAI) academic integrity policy responses for English medium instruction (EMI) higher education, responding to both the bespoke challenges for the sector and longstanding calls to define and disseminate quality implementation good practice. Design/methodology/approach: A virtual nominal group technique engaged experts (n = 14) in idea generation, refinement and consensus building across asynchronous and synchronous stages. The resulting qualitative and quantitative data were analysed using thematic analysis and descriptive statistics, respectively. Findings: The GenAI Academic Integrity Policy Development Blueprint for EMI Tertiary Education is not a definitive mandate but represents a roadmap of inquiry for reflective deliberation as institutions chart their own courses in this complex terrain. Research limitations/implications: If repeated with varying expert panellists, findings may vary to a certain extent; thus, further research with a wider range of stakeholders may be necessary for additional validation. Practical implications: While grounded within the theoretical underpinnings of the field, the tool holds practical utility for stakeholders to develop bespoke policies and critically re-examine existing frameworks. Social implications: As texts produced by students using English as an additional language are at risk of being wrongly accused of GenAI-assisted plagiarism, owing to the limited efficacy of text classifiers such as Turnitin, the policy recommendations encapsulated in the blueprint aim to reduce potential bias and unfair treatment of students. Originality/value: The novel blueprint represents a step towards bridging concerning gaps in policy responses worldwide and aims to spark discussion and further much-needed scholarly exploration to this end.es_ES
dc.language.isoenges_ES
dc.publisherJournal for Multicultural Educationes_ES
dc.relation.urihttps://www.emerald.com/insight/content/doi/10.1108/JME-10-2023-0102/full/htmles_ES
dc.rightsrestrictedAccesses_ES
dc.subjectacademic integrity policy developmentes_ES
dc.subjectEnglish as a medium of instructiones_ES
dc.subjectgenerative artificial intelligencees_ES
dc.subjecthigher educationes_ES
dc.subjectnominal group techniquees_ES
dc.subjectScopuses_ES
dc.subjectEmerginges_ES
dc.titleTransnational higher education cultures and generative AI: a nominal group study for policy development in English medium instructiones_ES
dc.typeArticulo Revista Indexadaes_ES
reunir.tag~ARIes_ES
dc.identifier.doihttps://doi.org/10.1108/JME-10-2023-0102


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