An open approach for learning educational data mining

Abstract

The Open Monitoring Environment (OME) allows a teacher to monitor, model and, thus, understand, the learning process based on the real data rising from an educational robotics class. The OME uses a novel educational data mining approach where teachers are empowered to create rules to extract pedagogically and contextually meaningful patterns of actions from a raw data flow. The OME has been tested in various educational robotics settings and our results indicate that the data mining approach in the OME is easily accessible even for users who are not computer science experts. We propose that the OME could be utilized in computer science education as a platform for empirical, hands-on approach for teaching and learning educational data mining.