Linked data driven visual analytics for tracking learners in a PLE

Abstract

In this work we introduce necessary steps and planned actions for implementation of analytical application with purpose on analyzing and visualizing information gathered by tracking user behavior and actions in our educational system called Personal Learning Environment (PLE)5. Furthermore we present a novel Semantic Web driven approach, for modeling of learning and activity based context using eligible domain specific ontologies, as well as for retrieving modeled data depending on the value of interests demonstrated by learner himself. We intend on closing the learning analytic cycle [Clo12] for PLE and for that purpose we are defining the requirements and implementation steps of analytic dashboard which shall give us necessary knowledge for improvement.