METHODOLOGICAL ASPECTS OF ARTIFICIAL INTELLIGENCE INTEGRATION INTO RESEARCH ACTIVITIES OF UNDERGRADUATE AND GRADUATE UNIVERSITY STUDENTS

This article presents a comprehensive analysis of the methodological aspects of integrating artificial intelligence (AI) technologies into the educational and research activities of undergraduate and graduate students at higher education institutions. The study draws on a triad of complementary sources: an analytical review of existing scientific publications systematizing the potential and risks of AI, a specialized study devoted to the dialectic influence of neural networks on students' cognitive development, and the author’s methodological developments in the form of developed and tested cognitive-activity strategies. The methodological framework includes content analysis, comparative and contrastive analysis, and systems analysis, ensuring a thorough analysis of the material. The central focus of the study is a detailed analysis of the dialectical AI influence on the cognitive development of young researchers, identifying and thoroughly characterizing potential benefits, including the development of metacognitive skills, enhanced capacity for complex analysis by reducing cognitive load, and stimulation of interdisciplinary thinking. In contrast, serious risks are systematized: the erosion of fundamental research competencies, the risk of intellectual passivity, the development of an «illusion of competence», and the distortion of knowledge-building processes. Particular attention is paid to the methodological aspects of transforming the educational process in the context of the new digital reality, including the changing roles of teachers and students. Specific recommendations are formulated, including the development of AI literacy as a key competency and the implementation of cognitive-activity strategies aimed at developing research autonomy and critical thinking. The article emphasizes the need to shift the educational paradigm from prohibitive measures to the constructive integration of AI, where the tool is viewed not as a replacement for thinking, but as a means to expand it and optimize the research process in higher education.