Generative Artificial Intelligence in Higher Education: A Review of Theoretical Approaches and Application Practices

The article presents the results of summarizing and systematizing scientific and practical research on the main directions of implementing generative artificial intelligence (GenAI) tools into the higher educational process by national scientific and pedagogical community, and the problems accompanying this process. The technological breakthrough in machine learning has significantly expanded the areas of artificial intelligence application. It has also necessitated a well-grounded assessment of the GenAI technologies potential for their most expedient integration into higher education, as well as the search for optimal and safe ways for teachers and students to interact with them.

The study is based on an analytical review of the publications devoted to the theoretical and applied problems of introducing GenAI tools in Russian universities. The total of 270 articles published between 2020 and 2024 and included in the List of peer-reviewed scientific publications approved by the Higher Attestation Commission (HAC) were analyzed. Methods of qualitative and quantitative content analysis, contextual analysis, and analytical grouping, as well as various mathematical methods, were applied.

The analysis showed that authors are mainly focused on summarizing the experience of using GenAI in the educational process within the scope of a specific academic discipline, educational program, or a separate area of a university’s activities. High research activity is evident in relation to problems associated with assessing the capabilities of GenAI and its specific services in teaching different disciplines. At the same time, scientists are primarily interested in such functions as the personalization of the educational process, educational outcomes assessment, and the training courses and individual classes design.

Particular attention is paid by researchers both to assessing the GenAI tools prevalence in educational practice and to the theoretical and empirical justification of a set of psychological, organizational, and pedagogical conditions that ensure the successful GenAI integration. Finally, the most intensive GenAI implementation is carried out in foreign languages teaching.

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