Use of the CANTOR system for collaborative learning in medical visual object recognition

This paper reports from a user requirement, design and evaluation study on supporting collaborative learning by visual perception in the medical education domain. Establishing the user requirements has been based on the Cognitive Systems Engineering approach. The user requirements laid the foundation for designing the software system CANTOR (Converging Agreement by Networking Telematics for Object Recognition) can briefly be described as a tool that support collaborative consensus making when classifying sets of medical images or objects in medical images. In evaluation experiments we have focused on the application of CANTOR in the early learning and training phase. We have assessed whether CANTOR can be used as a collaborative training tool in a qualitative and quantitative way. The evaluation experiments showed that using CANTOR seems to give a better learning effect than by using traditional methods.