- Spivakovsky, Aleksandr (orcid.org/0000-0001-7574-4133), Omelchuk, S. (orcid.org/0000-0002-0323-7922), Kobets, Vitaliy (orcid.org/0000-0002-4386-4103), Valko, Nataliia (orcid.org/0000-0003-0720-3217) and Malchykova, Daria S. (orcid.org/0000-0002-7197-8722) (2023) Institutional policies on artificial intelligence in university learning, teaching and research Information Technologies and Learning Tools, 5 (97). pp. 181-202. ISSN 2076-8184
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Співаковський Олександр Володимирович.pdf - Published Version Download (962kB) |
Abstract
Generative artificial intelligence is rapidly transforming the educational process and the scientific work of students, lecturers, researchers and administrators of higher education institutions. There are limited and contradictory recommendations for the use of artificial intelligence in the educational process and in the educational programmes of higher education institutions. To define the scope of AI application, there is a need to develop institutional policies for higher education institutions, which will allow the academic community to determine the appropriate scope of AI application in the educational process and prevent the use of AI in areas where ethical norms are violated. The purpose of the article is to summarise and systematise the experience of forming institutional policies for the application of artificial intelligence in education, training and research in higher education institutions using the experience of Kherson State University. The article presents the developed institutional policies for students, lecturers and researchers with recommended and not recommended initiatives for the use of AI in the educational process and research at Kherson State University. The purpose of these institutional policies was to create an inclusive environment of modern digital tools for involving of lecturers of non-professional specialties and define the framework for the use of artificial intelligence in education, teaching, and research of all subjects (participants) of educational activity. The recommendations are aimed at empowering all participants to select educational components creatively and at improving the efficiency of the educational process and research activities through the use of AI tools. Issues requiring further research regarding generative platforms lie in three thematic areas: knowledge base; transparency and ethics; digital transformation of organizations and societies. It is also relevant to create an educational environment that encourages the interaction and dissemination of positive practice of digital transformation of all participants of the educational process.
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