Data sharing for Learning Analytics - Designing conceptual artefacts and processes to foster interoperability

Abstract

Learning Analytics is based on data from the digital traces left by learning activities. In the controlled environment of a research lab combining data from different sources does not pose many problems. However, when scaling up learning analytics for general use in schools and universities data sharing and interoperability become major challenges. These issues are now being addressed in standardisation settings, both internationally and nationally. A case study of a Norwegian standards project shows that there are considerable conceptual issues emerging when stakeholders representing different interests start working towards consensus on these issues. Based on the case study this paper contributes with a number of conceptual constructs and a process that will make it easier to reach consensus about different aspects related to access to and exchange of data from different sources relevant for analysis of learning and the contexts in which learning occurs.