An ontology-based architecture for context recommendation system in E-learning and mobile-learning applications

Distant learning is an alternative way of education that offers a remote learning experience without being in a traditional classroom. With the emergence of mobile devices, distant learning is passing from electronic learning (e-learning) to mobile learning (m-learning) which makes learning even more widely available. This availability has put emphasis on the need of having platforms that are delivering learning contents corresponding to learner's learning environment. With the huge amount of learning materials available on the internet, it's become difficult to find the suitable ones. Although, recommendation systems can be the solution for this problem. However, these systems are still less used in e-learning and m-earning in comparison with other fields (e-commerce, social media…). Hence, to make these systems more relevant and performant, in this paper we propose to take benefits from semantic web technologies by proposing to add a semantic layer in 3-tiers classical web application's architecture. This layer will hold three ontologies: The Learning Context Ontology is a domain knowledge for gathering the learning context information (Profile, Social interactions, learning activities, and device specifications), The Learning Content Ontology is the Learning Object Ontology, and the Learning Design Ontology is the ontology to hold the sequenced learning activities. The OWL Rules filtering will be used as a recommendation technique.