In personalized learning, each student gets a customized learning plan according to their
pace of learning, instructional preferences, learning objects, etc. Hence the content …

E-learning recommender systems are becoming more popular due to the massive learning
materials available online and the changing pedagogy. A content recommender system in …

Massive Open Online Courses (MOOCs) have significantly impacted the basic education
industry since 2012. Online platforms enable learners to connect with the instructors present …

This article introduces a recommendation system that merges a knowledge-based (attribute-
based) approach with collaborative filtering, specifically addressing the challenges of the …

Students come to learning with unique styles, paces, and interests. Educators are mindful of
this phenomenon and strive to create learning experiences that cater to these differences …

Purpose: Purpose of this research is to carry out survey on Recommendation systems
techniques in Big Data Analytics. This article presents designing of recommender systems …

Recommender systems have been acknowledged as efficacious tools for managing
information overload. Nevertheless, conventional algorithms adopted in such systems …

Purpose: Purpose of this research is to carry out survey on Recommendation systems
techniques in Big Data Analytics. This article presents designing of recommender systems …

This study aims to apply a Recommendation System with Content Based Filtering method
with Jaccard Similarity and Cosine Similarity algorithms on the E-Learning Platform …

Recommendation systems are widespread with the big data hosted on the internet and the
users who actively access them. The recommendation model implemented here uses the …