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Mapping Research Trends in AI-Driven Personalized Learning Pathways: A Scoping Review
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Author(s): Mohammed Adi Al Battashi (University of Malaya, Malaysia), Mohamad A. M. Adnan (Academy of Islamic Studies, Malaysia), Asyraf Isyraqi Bin Jamil (Academy of Islamic Studies, Malaysia)and Majid Adi Al-Battashi (Ministry of Education, Oman)
Copyright: 2026
Pages: 30
Source title:
Generators, Bots, and Tutors: Creative Approaches to Human-AI Synergy in Classroom Instruction
Source Author(s)/Editor(s): Bosede Iyiade Edwards (Universiti Sains Malaysia, Malaysia), Hassan Abuhassna (Sunway University, Malaysia), Damola Olugbade (University of South Africa, Pretoria, South Africa), Olayinka Anthony Ojo (University of Bolton, United Kingdom)and Wan Ahmad Jaafar Wan Yahaya (Universiti Sains Malaysia, Malaysia)
DOI: 10.4018/979-8-3373-0847-0.ch001
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Abstract
This study presents a bibliometric analysis and SLR of research trends in AI-driven (PLP), exploring the evolving landscape of how artificial intelligence transforms education through adaptive, learner-centric models. By systematically analyzing academic publications from the past five years using data extracted from the Scopus database and tools like VOSviewer, the study maps the growth, key contributors, and emerging trends in the field. It identifies influential authors, leading institutions, and prevalent sources, while also examining the distribution of publications across countries and over time. The analysis of this study highlights predominant methodologies, AI-powered learning models, and sample types frequently employed in empirical studies, providing a comprehensive understanding of how AI technologies are utilized to enhance personalized learning experiences. Moreover, key findings reveal the challenges in implementing AI-driven solutions and underscore the importance of interdisciplinary collaboration among education, computer science, and psychology to drive innovation.
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