Intelligent Learning Pathways: A Customizable LMS Framework for Modern Education

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Authors: Ean H. Lim, Manoranjitham Muniandy, Kah W. Cheang, Tong-Yuen Chai, Yong Tien Fui, Kok Hui Meian
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Abstract

The advancement of technology in education has opened new avenues for customized learning experiences, enhancing student engagement and learning outcomes. This research presents an “Intelligent Learning Pathways” model, a customizable Learning Management System (LMS) framework designed to meet the diverse needs of modern educational institutions. The problem addressed is the limitation of conventional LMS platforms, which often lack adaptive, student-centered pathways and real-time data insights to support individual learning journeys. The objective of the research is to develop a flexible, data-driven LMS framework that integrates Artificial Intelligence (AI) and machine learning algorithms to create tailored learning pathways, optimizing content delivery based on students’ performance, preferences, and learning styles. The methodology combines user-centric design principles with predictive analytics, enabling the system to adjust content dynamically. Testing involved deployment in a university setting with over 500 students, measuring engagement rates, learning progress, and satisfaction. Results indicate a significant increase in student engagement and learning outcomes, with 85% of participants reporting a more customized learning experience. The research concludes that incorporating intelligent algorithms in LMS can transform educational delivery, making it adaptive and customized, thereby meeting the unique needs of diverse students.

Fields of Study & Subjects

Intelligent Tutoring Systems and Adaptive Learning Online Learning and Analytics Artificial Intelligence in Education

Publication details

Journal / source
International Journal of Information and Education Technology
Volume
16
Issue
2
Pages
436–445
Publication date
1 January 2026
Language
EN