AI-based learning transformation in secondary schools: A systematic literature review study

Abstract

This study examines the evolution of research on artificial intelligence (AI) in secondary school learning over the past few years. Using a Systematic Literature Review (SLR) method, 4,558 Scopus-indexed publications from 2019 to 2024 were analysed. The screening process adhered to the PRISMA framework, and VOSviewer was utilised to conduct bibliometric mapping, encompassing collaboration patterns, topic trends, and keyword groupings. Results indicate five dominant research themes. One cluster is heavily represented by medical and clinical research, which appears because many AI tools emerging in education originate from medical applications, such as simulations, automated assessment, and immersive technologies. The most relevant cluster focuses on adaptive learning, personalization, and data-driven curriculum design—areas directly connected to the context of secondary education. This review helps build a clearer conceptual map of AI-based learning innovation. Its key limitation is the exclusive use of Scopus; therefore, future studies should integrate additional databases for broader coverage.