| Abstract [eng] |
In the context of adaptive intellectual learning environment (VLE) possibility of using conceptual clustering algorithms is analyzed, trying to accomplish the ability of software agent to "feel" the changing environment and recognise the states it is in. Agent environment is understood as interface between the user of VLE and the students model, which is stored in the VLE and is constantly changing. Agents ability to "feel" is understood as agents ability to classify students, based on their knowledge level, which changes in the learning process. Using conceptual clustering algorithms found in the literature, we are trying to choose one which is most suited for the problem area, modifying it to model real data. |
