AI-Driven Personalization in Education

The swift development in areas like machine learning, natural language processing, and data-driven computation has made artificial intelligence a revolutionary concept in contemporary learning. In this chapter, three critical pedagogical aspects facilitated by the application of AI in modern education are analyzed. They are adaptive learning systems, which personalize the content and its delivery pace; automated assessment systems, which provide a detailed evaluation of students' achievements; and intelligent tutoring systems, which simulate individual assistance of teachers. Evidence based on the empirical research conducted from 2014 to 2024 is collected in order to discuss learning results achieved through AI use, as well as its design and implementation issues. Key aspects of the discussed learning systems and studies focused on them are presented in comparative tables. Special attention is paid to the ethical and social implications associated with this phenomenon.