Artificial intelligence in education: a systematic review of personalized learning trends and future directions

2Citations
Citations of this article
75Readers
Mendeley users who have this article in their library.

This article is free to access.

Abstract

Purpose: The objective of this research is to compile a thorough review of existing literature, highlighting how artificial intelligence and personalized learning have shaped emerging research opportunities. Research methodology: This study employs the PRISMA review protocol alongside a meta-literature review to analyze pertinent works sourced from the Scopus database, spanning the years 2013 to 2025. Findings: The study examines the progress and deficiencies in the integration of artificial intelligence and personalized learning in education. It underscores a transition in global research priorities from dominant regions such as China, USA and Europe to broader Asia, signaling new opportunities for educational improvement. However, the findings reveal that the swift expansion of AI, combined with persistent concerns about educational standards in developing countries, may create additional institutional pressures that influence the effectiveness of education. Implications: The findings from this review present significant implications for research, practice, and policy. For educators and academic institutions, the results highlight the necessity of professional development that goes beyond technical proficiency, emphasizing pedagogical integration and digital literacy. Furthermore, policymakers are urged to develop ethical frameworks for AI implementation in education, addressing critical issues such as data privacy, algorithmic bias, and unequal access. Originality: The significance of this study lies in its effort to bridge a gap in the existing literature by systematically analyzing and reviewing research on Artificial Intelligence and Personalized Learning using PRISMA and meta-literature review methodologies. This comprehensive analysis offers researchers a clearer understanding of key developments and emerging trends within the field. Moreover, it identifies promising avenues for future inquiry and serves as a foundational reference for subsequent investigations.

Cite

CITATION STYLE

APA

Ikram, M., Hanefar, S. B. M., Saleem, S. M. U., & Zulfiqar, F. (2026). Artificial intelligence in education: a systematic review of personalized learning trends and future directions. Frontiers in Education. Frontiers Media SA. https://doi.org/10.3389/feduc.2026.1782626

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free