Personalized Educational Technologies and Artificial Intelligence Development—Trends, Present and Future

Abstract

Over the past few years, a substantial amount of research has been conducted on the use of artificial intelligence (AI) in education. The latest AI achievements are very important for education because they expand access and can support personalization of learning at a new level. Personalized educational technologies leverage data analytics, machine learning, and adaptive learning algorithms to tailor educational content, learning pathways, and assessment methods to the individual needs, preferences, and abilities of learners. This review analyzes and classifies the recent advances in intelligent technologies that support the personalization of e-learning from a technological perspective. During our literature search, we used major academic search engines and digital libraries (such as Google Scholar, Scopus, IEEE Xplore, and Web of Science) together with bibliometric analysis tools to identify relevant and reputable scientific publications on the use of artificial intelligence in personalized e-learning. We comprehensively discuss the strengths, drawbacks, and the state of current use of each type of intelligent technology in personalized education. This paper also examines current trends in AI-driven personalized education, including the use of machine learning, learning analytics, adaptive assessment, ontologies, and Generative AI applications and tools. Furthermore, the study explores future directions in personalized learning, highlighting the potential of integrating advanced AI models and technologies to enable real-time personalized learning support. The findings suggest that AI-powered personalized educational technologies have the potential to significantly improve education by creating more inclusive, efficient, and learner-centered experiences.