Assessing the prospects for using artificial intelligence in higher education system

Introduction. The article deals with the problem of improving the quality of higher education in the context of its computerization. The purpose of the article is to describe the new structure of higher education, based on the principle of a neural network, as well as to identify the prospects of digital transformation for universities, when a wide range of administrative and educational functions might be performed by artificial intelligence. Materials and Methods. The study uses structural modeling in order to build a higher education system that functions as a neural network based on theoretical analysis and reviewing of scholarly literature on the methodology of teaching in high-ranking foreign universities. The author also employs the UTAUT (Unified theory of acceptance and use of technology) model to identify students’ attitudes towards the prospects for the introduction of artificial intelligence in higher education. Results. The paper proposes and describes a new intellectual structure of the higher education system. A distinctive feature of this structure is that employers should become the main evaluators of graduates’ education outcomes. Employers’ feedback is supposed to be provided for universities, adjusting the higher education system to continuously changing market requirements. The advantage of transforming the higher education system according to the principles of neural network functioning will bring a considerable increase in the quality of preparing top-level professionals, and therefore, real prospects for restructuring the national economy will be provided, when GDP growth is ensured not by increasing the amount of exporting raw materials, but by high-tech production. The results of students’ survey conducted and processed using the UTAUT model showed that the younger generation has a positive attitude towards the introduction of AI in the educational process: they are attracted by new prospects in obtaining knowledge and are not afraid of the risks associated with it. Conclusions. The paper concludes that Russian universities, by switching to the new model of higher education, based on a neural network, will be able to dramatically improve the quality of education and become world leaders in the field of preparing top-level professionals, as currently in foreign universities, artificial intelligence manages only a limited range of functions. A distinctive feature of the proposed model is complete digitalization and automation of all routine work at universities, decreasing methodological and reporting load for academic staff, as well as transferring the main teaching load from classrooms to laboratories for a deeper students’ involvement in research activities.