Location-based clustering and collaborative filtering for mobile learning

Abstract

This paper presents a new m-learning model described as location-based collaborative M-learning (LCM). This new model exploits location information of mobile users and implements two main operations; k-means for clustering mobile users, and location-based collaborative filtering (CF) to provide learning items recommendations to clustered users. A comprehensive evaluation methodology was utilised to validate the proposed model in terms of complexity, performance and learning items' recommendations quality. Results have confirmed successful implementation of the proposed LCM model during different mobile users' settings. It was shown that LCM structure efficiently reduces processing overload and time required for users' clustering and learning content authoring, and improves learning items recommendations' accuracy.