THE USE OF ARTIFICIAL INTELLIGENCE TO INDIVIDUALIZE STUDENT LEARNING IN HIGHER EDUCATION

Abstract

The paper is devoted to the study of the possibilities and effects of using artificial intelligence technologies to individualize the educational process in higher education. Based on the analysis of Russian and international research projects and implementation experience, it has been shown that intelligent adaptive learning systems ensure up to 92% accuracy in predicting learning outcomes, increase students' academic performance by 18%, and boost engagement in the learning process by 25%. The paper examines the architectural solutions of intelligent platforms for personalizing education, including the domestic development MIOS (an intelligent platform for managing learning activity) and a system of adaptive learning based on neural networks, which has been tested in five Russian universities. Special attention is paid to the issue of students' readiness for personalized learning: a survey of 1,211 students from 38 Russian universities showed that only 45–60% of respondents express readiness for this model of education, which imposes additional requirements for preparing students to interact with intelligent systems.