Challenges of generative artificial intelligence for the higher education system

Problem statement . The theoretical and technological challenges of using generative artificial intelligence (AI) in the higher education system of the Russian Federation are briefly discussed. Methodology. System-structural and system-activity approaches are used. Content analysis and thematic moni...

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Main Author: Andrey I. Kapterev
Format: Article
Language:English
Published: Peoples’ Friendship University of Russia (RUDN University) 2023-12-01
Series:RUDN Journal of Informatization in Education
Subjects:
Online Access:https://journals.rudn.ru/informatization-education/article/viewFile/37118/22843
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author Andrey I. Kapterev
author_facet Andrey I. Kapterev
author_sort Andrey I. Kapterev
collection DOAJ
description Problem statement . The theoretical and technological challenges of using generative artificial intelligence (AI) in the higher education system of the Russian Federation are briefly discussed. Methodology. System-structural and system-activity approaches are used. Content analysis and thematic monitoring of generative АI technologies were carried out, its constructive, cognitive and pedagogical features were revealed. Results. The features of generative AI are analyzed. The digital transformation of education is shown through a rethinking of the key roles of teachers in the digital era in the direction of educational engineering and the development of creative competencies of students. A generalized description of the challenges of generative AI in relation to universities is given. Several possible ways of identifying and neutralizing the use of generative AI by students in the implementation of practical tasks are suggested. The ways of solving the problems of using generative AI for universities are substantiated: a) cloud computing and the use of ready-made models; b) cooperation with industry experts; c) the use of interdisciplinary approaches; d) encouraging experimentation, creativity and team building; e) providing ongoing support and mentoring; f) solving ethical problems of using generative AI in higher education. Conclusion. It is proved that the paradigm of “educational engineering”, including the use of generative AI, focuses on the development of creative design and design competencies of students and teachers.
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spelling doaj.art-1dcc23c38bcb488c9514a4c2a26e10332023-12-20T08:50:41ZengPeoples’ Friendship University of Russia (RUDN University)RUDN Journal of Informatization in Education2312-86312312-864X2023-12-0120325526410.22363/2312-8631-2023-20-3-255-26421012Challenges of generative artificial intelligence for the higher education systemAndrey I. Kapterev0https://orcid.org/0000-0002-2556-8028Moscow City UniversityProblem statement . The theoretical and technological challenges of using generative artificial intelligence (AI) in the higher education system of the Russian Federation are briefly discussed. Methodology. System-structural and system-activity approaches are used. Content analysis and thematic monitoring of generative АI technologies were carried out, its constructive, cognitive and pedagogical features were revealed. Results. The features of generative AI are analyzed. The digital transformation of education is shown through a rethinking of the key roles of teachers in the digital era in the direction of educational engineering and the development of creative competencies of students. A generalized description of the challenges of generative AI in relation to universities is given. Several possible ways of identifying and neutralizing the use of generative AI by students in the implementation of practical tasks are suggested. The ways of solving the problems of using generative AI for universities are substantiated: a) cloud computing and the use of ready-made models; b) cooperation with industry experts; c) the use of interdisciplinary approaches; d) encouraging experimentation, creativity and team building; e) providing ongoing support and mentoring; f) solving ethical problems of using generative AI in higher education. Conclusion. It is proved that the paradigm of “educational engineering”, including the use of generative AI, focuses on the development of creative design and design competencies of students and teachers.https://journals.rudn.ru/informatization-education/article/viewFile/37118/22843digital transformation of educationhigher professional educationchallengesways to solve problems
spellingShingle Andrey I. Kapterev
Challenges of generative artificial intelligence for the higher education system
RUDN Journal of Informatization in Education
digital transformation of education
higher professional education
challenges
ways to solve problems
title Challenges of generative artificial intelligence for the higher education system
title_full Challenges of generative artificial intelligence for the higher education system
title_fullStr Challenges of generative artificial intelligence for the higher education system
title_full_unstemmed Challenges of generative artificial intelligence for the higher education system
title_short Challenges of generative artificial intelligence for the higher education system
title_sort challenges of generative artificial intelligence for the higher education system
topic digital transformation of education
higher professional education
challenges
ways to solve problems
url https://journals.rudn.ru/informatization-education/article/viewFile/37118/22843
work_keys_str_mv AT andreyikapterev challengesofgenerativeartificialintelligenceforthehighereducationsystem