THEORETICAL AND METHODOLOGICAL BASIS OF DESIGNING AN ADAPTIVE DIGITAL EDUCATION SYSTEM BASED ON ARTIFICIAL INTELLIGENCE
DOI:
https://doi.org/10.47390/SPR1342V6I3Y2026N53Keywords:
artificial intelligence, adaptive learning, digital learning environment, information and communication technologies, personalized learning, educational effectiveness, learning process management, digital transformation in education, machine learning, automated assessment system.Abstract
This article explores the theoretical and methodological foundations for designing an adaptive digital learning system based on artificial intelligence technologies. In the context of digital transformation in education, the issues of individualizing the learning process, real-time monitoring of students’ knowledge levels, and improving mechanisms for managing educational activities are analyzed. Within the framework of the study, a conceptual model of adaptive learning based on artificial intelligence algorithms (machine learning, data analysis, and predictive methods) has been developed. The proposed model enables dynamic adaptation of learning content by considering students’ knowledge levels, learning pace, error dynamics, and individual characteristics. The results of the experimental study demonstrate that the implementation of an AI-based adaptive system significantly improves learning outcomes, enhances students’ independent learning skills, and increases overall educational effectiveness. The research findings contribute to the development of pedagogical mechanisms for designing and implementing intelligent digital learning environments.
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