Keyword: «university education»

The issue of the artificial intelligence influence on the academic performance and quality of student learning has become particularly relevant in recent years due to the rapid development of this technology and its widespread use. Today, both the positive effects of integrating artificial intelligence into the educational process and possible negative consequences, including a decrease in student motivation and a deterioration in the quality of knowledge acquisition, are actively studied. However, there are still disagreements among researchers and educators regarding the nature and consequences of artificial intelligence-based technologies impact on the educational process. The main objective of this work is to analyze the key aspects of the generative artificial intelligence influence on student academic performance, cognitive activity and quality of learning. The objectives of the work included assessing the current status of artificial intelligence in education, identifying the possible impact of this technology on the effectiveness of academic work and students' cognitive activity, and developing recommendations on how to use generative artificial intelligence in education. The work is based on systems, competence-based, axiological and activity-based approaches. The results of the work include recommendations for the implementation of generative artificial intelligence technology in the educational process based on the analysis of relevant research on the topic over the past 5 years, as well as our own empirical research. The results show the ambiguity of the perception of the latest generation digital technologies role in education, the lack of uniform criteria for assessing the artificial intelligence impact on the educational process and the need for further scientific and practical work in this area. The theoretical significance of the work lies in identifying contradictions related to the use of generative artificial intelligence in educational institutions. The practical significance of the study is expressed in the proposed measures to optimize the educational process, taking into account the peculiarities of student interaction with neural networks, aimed at improving the quality of education and eliminating potential risks.