DEVELOPMENT OF A METHODOLOGY FOR USING NEURAL NETWORKS TO ELIMINATE GAPS IN STUDENTS' KNOWLEDGE OF STATISTICAL ANALYSIS

The purpose of the study is to develop an approach to eliminate gaps in students' knowledge of statistical analysis in a course on artificial intelligence methods. Neural networks were used in the design and implementation of the methodological technology. The pedagogical experiment was conducted in the academic years 2023-2024 and 2024-2025 among third-year students of the department 09.03.02 Information Systems and Technologies of the Sholom-Aleichem Priamursky State University. The results of the study showed that the use of neural networks effectively helps to fill gaps in knowledge in statistical analysis, improves understanding of the material and increases students' motivation. Context generation with the help of experiments made it possible to link the theoretical aspects of statistics with the practical tasks of artificial intelligence, which contributed to the development of self-learning skills and the application of knowledge in practice. The proposed methodology can be recommended for integration into the educational process not only in disciplines related to artificial intelligence methods, but also in other courses where data management skills are needed.