Learning Preference-Based Resource Recommendation System

Abstract

"Students may struggle to find the most suitable type of online resource to fit their learning style. An online resource recommendation system that considers the student's learning style could be a helpful solution. This project aims to create a web-based solution that provides accurate recommendations for learning resources based on the student. E-learning systems have become a popular method for education and training due to the widespread availability of the internet. Despite this, many studies have highlighted the need for personalization in these systems. Currently, many e-learning platforms still offer a onesize-fits-all approach to students, failing to cater to the diverse learning preferences of their users. Personalization in e-learning refers to the customization of the educational experience for each individual user. This includes features such as adaptive interaction, adaptive course delivery, content search and assembly, and adaptive collaborative assistance. The problem of lack of personalization in e-learning systems is well documented and a topic of much research. This document aims to provide an overview of the background of this issue and the existing works related to it. The author also plans to introduce a solution to this problem and outline the steps they intend to take to address the challenges faced in implementing."