CHOCOLATO: A Concrete and Helpful Ontology- Aware Collaborative Learning Authoring Tool

To develop intelligent systems to support collaborative learning (CL) is especially challenging in view of knowledge representation. Current knowledge concerning CL is based on various learning theories, which are always expressed in natural language and are particularly complex given the context of group learning where the synergy among learner’s interactions affect the learning processes and hence the learning outcomes. Without the explicit representation of learning theories it is difficult to support the design of group activities based on well-grounded theoretical knowledge. Our approach calls upon techniques of ontological engineering to make theories “understandable” both by computers and humans. We then propose techniques to reason on these theories to develop an intelligent support system that supports group formation, facilitates the design of CL activities, and minimizes the load of interaction analysis. This system is referred to as CHOCOLATO: A Concrete and Helpful Ontology-aware Collaborative Learning Authoring Tool. In this demonstration we will present one of its sub-systems called MARI – Main Adaptive Representation Interface that represents theories graphically to facilitate the design CL activities with theoretical justifications.