Organizing student research work in light of generative artificial intelligence technologies

The aim of this research is to develop and justify a comprehensive approach to organizing student research work with the implementation of generative artificial intelligence (AI) technologies, contributing to increased efficiency of such work and the formation of necessary researcher competencies. The article presents an analysis of regulatory legal documents and scientific studies on the use of AI in scientific activities, including student research, and identifies factors and principles influencing the optimal integration of these technologies into the educational process. Based on the analysis, an approach to organizing student research work using generative AI was developed and tested, including teaching materials for students and advanced training programs for teachers, taking into account the analysis of the risks of using AI. The scientific novelty of the work lies in the fact that the optimal integration of generative AI into student research work requires a comprehensive approach based on normative, technical, competence-based, research, and relevant factors, as well as the principles of efficiency, controllability, and transparency, allowing to maintain a balance between the advantages of new technologies and the development of students' research competencies with clear regulation of the use of AI, training of teachers and students. The result of the research is the identification of factors and principles for the implementation of AI and the systematization of risks associated with the use of AI at the stages of scientific research, which are incorporated into the development and testing of the approach, ensuring increased efficiency of scientific work, strengthened control over substantive and ethical aspects, and transparency of the use of AI tools by students.