Challenges of generative artificial intelligence for the higher education system

Abstract

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.