INTELLIGENT LEARNING SYSTEMS

This article is devoted to the problem of introducing intelligent systems into the educational process. The article reflects the problems and prospects for the development of intelligent learning systems. The article presents a brief analysis of existing models of recommender systems in education, an analysis of models of recommender systems, according to the operating principle. The implementation of a recommender system includes processing data on students and courses, as well as the interaction of the system and the user, which allows users to receive personalized recommendations. The article provides an example of developing a recommender learning system. In general, the article touches upon the problems of developing artificial intelligence technologies in the educational process. The relevance of introducing RIS into the educational process is due to the growth in the volume of educational data and the complexity of their manual processing. The need for personalized learning to improve academic performance. Development of distance and blended learning, where digital tools play a key role. The ability to automatically monitor and predict student performance. Research and development of recommendation systems in education not only improves the effectiveness of learning, but also creates more adaptive educational technologies for the future. Using artificial intelligence methods, such systems are able to analyze data on students' knowledge and preferences, offering optimal educational resources and interaction formats.