Learning Assistant - Personalizing Learning Paths in e-Learning Environments

The paper presents an agent called Learning Assistant, which is responsible for defining individual learning paths for pupils in e-learning environment. The Assistant is able to infer using metadata described pupils and didactic materials; this inference is a basis for building the individual learning path for each pupil. To build a learning path for a new pupil the agent uses information collected during introductory tests. A SOM neural network is used for grouping similar pupils. WebTeacher is e-learning environment in which Learning Assistant works. This environment is shortly presented in the paper. Next, we present the idea of personalization-we consider the individual´s pupil characteristic and a group of similar pupils characteristic. Data structures described didactic materials and pupils are also shortly explained. The performed experiments allow formulate some conclusions, they are described very shortly. Summary ends the paper.