Learning Analytics for sensor-based adaptive learning

The goal of the learning analytics approach is to make learning processes visible, to better understand ans support them. While learning analytics is often viewed from an institutional or instructor perspective, with the goal of obtaining metrics for learning, identifying problems, or improving teaching, learning analytics in a systemic view has great potential especially for learners and the targeted support of the learning process.

In the project LISA (“Learning Analytics for sensor-based adaptive learning”) this approach was explored and made usable. It focuses on learning analytics for the user and not – as in previous approaches – for the educational organization. The idea: if users are visualized their own learning behavior in the learning process and receive individual recommendations, they will organize their learning process better and achieve higher learning success. For this purpose, we integrated a dashboard as well as adaptive learning recommendations into PIIPE. Project partners were HTW Berlin, Humboldt-Universität zu Berlin, Leibnitz-Institut für Wissensmedien, SGM Solutions & Globale Media, and Promotion Software.