SmartLAK: A big data architecture for supporting learning analytics services

In this paper, we present a big data software architecture that uses an ontology, based on the Experience API specification, to semantically represent the data streams generated by the learners when they undertake the learning activities of a course, e.g., in a course. These data are stored in a RDF database to provide a high performance access so learning analytics services can process the large amount of data generated in a virtual learning environment. These services provide valuable information to teachers and instructors such as predict the learner's performance, discover the real learning paths, extract the learner's behavior patterns and so on. The proposed architecture has been validated in the Educational Technology undergraduate course of the Degree in Pedagogy at the Faculty of Education of the University of Santiago de Compostela.