THE CULTURE OF ACADEMIC INTEGRITY IN THE CONTEXT OF THE USE OF ARTIFICIAL INTELLIGENCE IN EDUCATION

Abstract

The article provides a comprehensive analysis of the possibilities and limitations of applying artificial intelligence in higher education from the perspectives of both scholars and students. The study identifies key directions for improving the culture of academic integrity amid the rapid spread of intelligent learning technologies. The purpose of the paper is to summarize the most appropriate models for integrating AI into the educational process while preserving ethical standards of contemporary university education. It is established that the use of AI enables deeper individualization of learning by constructing personalized educational trajectories tailored to the needs and abilities of each student. The involvement of intelligent systems contributes to the renewal of teaching methods, enhancement of assessment approaches, and development of didactic materials adapted to students’ level of preparation, thus improving learning efficiency. Academic integrity in the study is viewed as a multidimensional characteristic of scientific and educational activities, implying honest, responsible, and transparent performance of all stages of work in accordance with professional and ethical norms. Its foundations include the principles of honesty, accuracy, openness, respect, and responsibility. The article demonstrates that fostering integrity-oriented behavior requires systematic educational activities: lectures, seminars, trainings, and thematic events that promote students’ awareness of the significance of ethical norms in learning. At the same time, the university environment must ensure the preparation of educators for working with intelligent technologies and improving students’ digital literacy, including understanding the principles of AI functioning and areas of its appropriate use. Special attention is given to the need to reassess traditional knowledge-assessment formats. Educators are encouraged to implement evaluation methods that reduce risks of misconduct and stimulate analytical thinking, collaboration, and oral communication. The conclusions highlight the importance of establishing clear university-level policies for AI use that take into account the dynamics of technological change, as well as the need for regular professional development of educators and the inclusion of topics on the ethical use of intelligent systems in academic courses to maintain a responsible learning environment.