Ai-based personalized e-learning of university students: current state of the problem

Personalization of student learning is an important direction in the development of a student-centered education model. It can be implemented both through direct interaction and in a mediated format within an electronic information-and-educational environment. One way to personalize e-learning is using artificial intelligence (AI) technologies. Machine learning algorithms, chatbots and voice assistants, virtual and augmented reality technologies enable the automation of data collection and data analysis, provide instant feedback and recommendations, create authentic learning environments, determine optimal learning strategies. However, despite all the advantages, the implementation of AI-based personalized e-learning faces technical and financial difficulties, lack of necessary digital competencies among educators, as well as insufficient theoretical foundations. The aim of this article is to identify and describe the characteristics of the current state of the problem of AI-based personalized e-learning for university students. The article defines the normative and legal guidelines for the use of AI in personalization of university students’ learning; examines the current state of the problem in the theory and practice of education; conducts a comprehensive assessment of factors directly and indirectly influencing the AI-based personalized of e-learning for university students; taking into account the identified factors, outlines the perspectives for the application of AI in personalized e-learning for students. To achieve the obtained results, different theoretical and empirical methods such as literature and electronic source analysis, content analysis, documentation analysis, SWOT analysis are applied.