EXCALIBUR LA - An Extendable and Scalable Infrastructure Build for Learning Analytics

IEEE International Conference on Advanced Learning Technologies (ICALT), pp. 155–157

Abstract

As learning scenarios include more digital parts and often more than one online platform is used, Learning Analytics becomes more challenging to perform on these distributed data. In this paper, the Learning Analytics infrastructure EXCALIBUR LA is presented. It receives data from arbitrary platforms as xAPI statement, performs pro-active analyses by using various analytics engines and provides the analysis results via a REST API for each authorized platform. This concept allows to perform analyses adjusted to the needs of an institution and also to analyze data from multiple platforms combined.

Authors 2

1. Sven Judel Aachen Learning Technologies Research Group

   RWTH Aachen University

   Affiliation as printed

   RWTH Aachen University,Learning Technologies Research Group,Aachen,Germany

   Learning Technologies Research Group, RWTH Aachen University, Aachen, Germany

2. Ulrik Schroeder Aachen Learning Technologies Research Group

   RWTH Aachen University

   Affiliation as printed

   RWTH Aachen University,Learning Technologies Research Group,Aachen,Germany

   Learning Technologies Research Group, RWTH Aachen University, Aachen, Germany