Published by Pablo Hermoso de Mendoza González
25/02/2013
Learning Analytics by nature relies on computational information processing activities intended to extract from raw
data some interesting aspects that can be used to obtain insights into the behaviours of learners, the design of learning
experiences, etc. There is a large variety of computational techniques that can be employed, all with interesting properties, but it is the interpretation of their results that really forms the core of the analytics process. In this paper, we look at a specic data mining method, namely sequential pattern extraction, and we demonstrate an approach that exploits available linked open data for this interpretation task. Indeed, we show through a case study relying on data about students' enrolment in course modules how
linked data can b...