Application of Artificial Intelligence in Higher Education Institutions: Foreign Experience

The purpose of this article is to study the application of artificial intelligence in higher education institutions in foreign countries. The article provides an overview of various tools for using artificial intelligence in the educational environment, reveals examples of successful implementation of digital technologies in higher education institutions, and outlines the shortcomings that should be taken into account when introducing artificial intelligence into educational practice. Methodology. The study used a set of complementary methods based on the principles of general scientific methodology: theoretical methods of analysis, synthesis and generalisation of works corresponding to the stated topic. Theoretical analysis allowed the identification of theoretical concepts, models and technologies used to support the educational process. The method of synthesis enabled the information obtained to be put into a systematic and comprehensible form. By synthesising different sources and data, a general idea of how artificial intelligence can be used in modern education was formed. The method of synthesis helped to build a system of existing knowledge and experience in this area and identify new areas of research. Results. The creation of individualised experiences using artificial intelligence and machine learning has been shown to tailor learning to the individual characteristics of the student, increasing the effectiveness of training. Personalised learning technologies are used to improve the learning process through data mining and the provision of personalised information. Personalised learning can also use methods such as games and virtual activities to make the learning process more interesting and engaging. Disadvantages include insufficient technological development, lack of personal contact, limited AI in the curriculum, limited creativity and flexibility of systems, algorithmic discrimination and loss of skills. Despite these shortcomings, it is noted that the use of intelligent learning systems and adaptive technologies allows for the personalisation of learning based on the individual characteristics of each student, which contributes to more effective training. It is important to find an optimal balance between the traditional approach to learning and the use of the latest learning technologies that will contribute to successful and productive learning. Practical implications include the importance of personalising learning with the help of intelligent systems, the need to find a balance between traditional and modern methods, taking into account the shortcomings of technology implementation, continuing research and developing partnerships for the successful implementation of artificial intelligence in educational practice. Value/Оriginality. The paper proposes specific methods and examples of artificial intelligence application in education, analyses the shortcomings of this process and provides practical recommendations for its further improvement.