Towards Recommendation Using Learners’ Interest in Social Learning Environment

Abstract

Social networkings are relatively recent innovations. Literature on other social technologies in education strongly suggests that such technologies can be educationally beneficial to teachers and learners in supporting the sharing of resources, enhancing motivation, and facilitating reflection, social interaction and knowledge building. However, thus far there have been few empirical studies detailing application of social networking technology in educational contexts based on learners’ interests. This study proposes an automatic learning environment based on the analysis of the social interactions that takes place between users-users and users-resources, the analysis is based on the history of interactions made by learners within the environment to deduce their interests in relation to a module, learners with similar interests will then be assigned to the same learning group in order to propose recommendations regarding their preferences, interests and needs. This system ensures that these recommendations will certainly improve the learning process by providing students with the best learning practices, the desirable collaborators, and the relevant resources that fit better their needs. This study showed that the recommended resources are interesting, approachable, adaptable, and divers for users with several interests.