AI-Based Online Learning Recommendation System for Personalised Education

Abstract

The rapid expansion of online learning platforms has created unprecedented access to educational resources; however, it has also introduced significant challenges, including contentoverload,inappropriatecourseselection,andlowlearner engagement.Learnersfrequentlystruggletoidentifycoursesthat align with their current skill levels, learning objectives, and careeraspirations,resultingininefficientlearningpathsandhigh dropout rates. To address these challenges, this paper proposes an artificial intelligence-based online learning recommendation system that personalises learning experiences through intelligent,data-driventechniques.Theproposedsystemanalyses diverse learner data, including demographic information, academic background, learning behaviour, interaction history, and assessment performance. By applying machine learning anddata analysis techniques, the system constructs comprehensive learner profiles and dynamically identifies individual skill gaps. Based on these insights, personalised course recommendations are generated to enhance learner engagement, improve learning efficiency, and support continuous skill development.