Generative Artificial Intelligence Policy: A Qualitative UNESCO Framework Analysis.
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| Title: | Generative Artificial Intelligence Policy: A Qualitative UNESCO Framework Analysis. |
|---|---|
| Authors: | Adarkwah, Michael Agyemang1, Ercan, Amine Merve1, Schneider, Käthe1, Bayar, Ekin1 |
| Source: | Journal of University Teaching & Learning Practice. 2026 2nd Quarter, Vol. 23 Issue 2, p1-38. 38p. |
| Subject Terms: | *Generative artificial intelligence, *Higher education, *Education ethics, *Diversity & inclusion policies, Policy analysis, Sustainability |
| Company/Entity: | UNESCO |
| Abstract: | Generative artificial intelligence’s (GenAI) emergence has compelled higher education leadership to design robust policies that foster safe and responsible integration and promote academic integrity. However, there is a lack of knowledge and evaluation of how higher education institutions comprehensively regulate GenAI usage. This study employed a qualitative policy analysis technique to examine the GenAI policies of thirty (30) highly ranked universities according to the Quacquarelli Symonds (QS) ranking across the top ten countries for AI preparedness. UNESCO's eight-component GenAI framework served as a lens for evaluating the robustness of the policies. The study’s findings reveal significant disparities in policy implementation. Specifically, although core ethical and governance principles are widely embraced, key issues like inclusion, equity, and sustainability, such as internet access, gender parity in AI, and environmental impact, are often overlooked. Nordic countries and New Zealand cover UNESCO’s elements more fully than some higher-ranked AI Preparedness Index (AIPI) countries, indicating that AIPI ranking does not guarantee strong GenAI policies. Notably, no public policies were found for German universities and Tallinn University of Technology. The study underscores the necessity for higher education leaders to develop more inclusive and future-oriented policies that integrate social equity, interdisciplinary experimentation, and sustainability considerations. Future studies can replicate this research by focusing on the long-term impact of the policies on university operations such as assessment, teaching, learning, research, academic performance. [ABSTRACT FROM AUTHOR] |
| Copyright of Journal of University Teaching & Learning Practice is the property of Open Access Publishing Association and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Education Research Complete |
| FullText | Links: – Type: pdflink Text: Availability: 0 |
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| Header | DbId: ehh DbLabel: Education Research Complete An: 194591160 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Generative Artificial Intelligence Policy: A Qualitative UNESCO Framework Analysis. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Adarkwah%2C+Michael+Agyemang%22">Adarkwah, Michael Agyemang</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AR" term="%22Ercan%2C+Amine+Merve%22">Ercan, Amine Merve</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AR" term="%22Schneider%2C+Käthe%22">Schneider, Käthe</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AR" term="%22Bayar%2C+Ekin%22">Bayar, Ekin</searchLink><relatesTo>1</relatesTo> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Journal+of+University+Teaching+%26+Learning+Practice%22">Journal of University Teaching & Learning Practice</searchLink>. 2026 2nd Quarter, Vol. 23 Issue 2, p1-38. 38p. – Name: Subject Label: Subject Terms Group: Su Data: *<searchLink fieldCode="DE" term="%22Generative+artificial+intelligence%22">Generative artificial intelligence</searchLink><br />*<searchLink fieldCode="DE" term="%22Higher+education%22">Higher education</searchLink><br />*<searchLink fieldCode="DE" term="%22Education+ethics%22">Education ethics</searchLink><br />*<searchLink fieldCode="DE" term="%22Diversity+%26+inclusion+policies%22">Diversity & inclusion policies</searchLink><br /><searchLink fieldCode="DE" term="%22Policy+analysis%22">Policy analysis</searchLink><br /><searchLink fieldCode="DE" term="%22Sustainability%22">Sustainability</searchLink> – Name: SubjectCompany Label: Company/Entity Group: Su Data: <searchLink fieldCode="DE" term="%22UNESCO%22">UNESCO</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: Generative artificial intelligence’s (GenAI) emergence has compelled higher education leadership to design robust policies that foster safe and responsible integration and promote academic integrity. However, there is a lack of knowledge and evaluation of how higher education institutions comprehensively regulate GenAI usage. This study employed a qualitative policy analysis technique to examine the GenAI policies of thirty (30) highly ranked universities according to the Quacquarelli Symonds (QS) ranking across the top ten countries for AI preparedness. UNESCO's eight-component GenAI framework served as a lens for evaluating the robustness of the policies. The study’s findings reveal significant disparities in policy implementation. Specifically, although core ethical and governance principles are widely embraced, key issues like inclusion, equity, and sustainability, such as internet access, gender parity in AI, and environmental impact, are often overlooked. Nordic countries and New Zealand cover UNESCO’s elements more fully than some higher-ranked AI Preparedness Index (AIPI) countries, indicating that AIPI ranking does not guarantee strong GenAI policies. Notably, no public policies were found for German universities and Tallinn University of Technology. The study underscores the necessity for higher education leaders to develop more inclusive and future-oriented policies that integrate social equity, interdisciplinary experimentation, and sustainability considerations. Future studies can replicate this research by focusing on the long-term impact of the policies on university operations such as assessment, teaching, learning, research, academic performance. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Journal of University Teaching & Learning Practice is the property of Open Access Publishing Association and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
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| RecordInfo | BibRecord: BibEntity: Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 38 StartPage: 1 Subjects: – SubjectFull: Generative artificial intelligence Type: general – SubjectFull: Higher education Type: general – SubjectFull: Education ethics Type: general – SubjectFull: Diversity & inclusion policies Type: general – SubjectFull: Policy analysis Type: general – SubjectFull: Sustainability Type: general – SubjectFull: UNESCO Type: general Titles: – TitleFull: Generative Artificial Intelligence Policy: A Qualitative UNESCO Framework Analysis. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Adarkwah, Michael Agyemang – PersonEntity: Name: NameFull: Ercan, Amine Merve – PersonEntity: Name: NameFull: Schneider, Käthe – PersonEntity: Name: NameFull: Bayar, Ekin IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 04 Text: 2026 2nd Quarter Type: published Y: 2026 Identifiers: – Type: issn-print Value: 14499789 Numbering: – Type: volume Value: 23 – Type: issue Value: 2 Titles: – TitleFull: Journal of University Teaching & Learning Practice Type: main |
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