Learning analytics framework for educational virtual worlds

This paper presents a learning analytics framework for 3D educational virtual worlds that focus on discovering learning flows and checking its conformance through process mining techniques. The core of this framework is an Opensim-based virtual world platform, known as OPENET4VE, that is compliant with the IMS Learning Design specification and that has the ability of monitoring and registering the events generated by students and teachers. Based on these event logs, process mining algorithms automatically extract the real learning flow of the course, allowing teachers to introduce changes in the learning flow initially proposed.

keywords: Learning analytics, Process mining, 3D Educationa l Virtual Worlds, IMS Learning Design, Petri nets.