Learner’s Annotative Activity as a Data Source of Personalized Web Services Recommendation

Abstract

Since information retrieval for relevant learning resources to support teachers or learners is a pivotal activity in Technology enhanced learning (TEL), the deployment of recommender systems has attracted increased interest. In this paper, we propose an approach of recommendation of web services from the annotative activity of the learner to assist him in his learning activity. This process of recommendation is based on two preparatory phases: the phase of modelling learner’s personality profile through analysis of annotation digital traces in learning environment realized through a profile constructor module and the phase of discovery of web services which can meet the goals of annotations made by the learner via the web service discovery module. The evaluation of these two main modules (web service discovery module & profile constructor module) through empirical studies realized on groups of learners based on the Student’s t-test showed significant results.