This article examines the potential of assessing students' research performance using artificial intelligence (AI). The author analyzes the limitations and potential of integrating AI into scientific training, focusing on state standards (GOSTs) regulating the use of AI in students' research. It is demonstrated that the combination of AI tools and traditional methods provides dual monitoring of students' completed work, with AI automating the process and the teacher (supervisor) evaluating the research paper or assignment. A description of AI platforms suitable for integration into the educational process is provided (Study AI and Kemp AI are Russian platforms, Preplexity is an international platform, and NotebookLM is an experimental Google platform). The potential of AI for automating assessment, reflection, and improving the objectivity of assessing students' research performance is identified. It is demonstrated that the use of individual AI tools contributes to the effectiveness of students' research. Pedagogical approaches to using AI in education are developed, and the main methods and criteria for assessing students' research performance are defined.
higher education; assessment; automation; artificial intelligence; methods; criteria; efficiency improvement; information platforms.