Models of Artificial Intelligence Integration in the Educational Process for Enhancing Individualized Learning of Secondary Education Students

Abstract

The article is dedicated to exploring the opportunities and challenges of integrating artificial intelligence (AI) into secondary education as a means of enhancing the quality of the educational process, providing a personalized approach, and developing key competencies in learners. The article highlights the relevance of AI in school education for adapting learning trajectories according to students’ knowledge levels and individual needs, thus better preparing them to meet the demands of the modern information society. The purpose of the article is to analyze AI technologies applicable for personalized learning, assess their impact on knowledge acquisition, motivation, and learners’ ability for independent study, as well as to identify key challenges and risks associated with their implementation. The research employs theoretical analysis methods, including the evaluation of modern adaptive platforms and recommendation systems, as well as empirical methods involving surveys among educational process participants who work with personalized technologies. The research findings reveal the primary advantages of using AI in secondary education, such as the adaptation of task complexity and learning pace to meet individual learner needs, positively influencing learning quality, motivation levels, and self-confidence. Key issues have also been identified, including risks related to data privacy protection, limitations of technical infrastructure, and dependency on automated decisions, which may hinder the development of critical thinking and independence. The article also addresses measures to overcome technical and pedagogical challenges, such as infrastructure development and ensuring equal access to technology in various educational institutions. The conclusions concluded that for the effective implementation of artificial intelligence in secondary education, it is necessary to apply a comprehensive approach, which involves ensuring reliable data protection, training teachers to use artificial intelligence, as well as creating platforms with flexible settings to support students with different levels of training. The prospects for further research include improving AI adaptation algorithms, developing methods for monitoring their effectiveness, and studying the long-term impact of AI on learners’ cognitive skill's development.