Application of Inconsistency Resolution Methods in Intelligent Learning Systems
- 438 Downloads
This chapter deals with some applications of the methods for inconsistency resolution presented in previous chapters. Its subject is related to recommendation processes in intelligent learning systems. Using methods for rough classification, a model for representation of learner profiles, learning scenarios, and the choice of a proper scenario for a new learner is proposed. The recommendation mechanisms are based on consensus methods and clustering algorithms. Owing to them there is a possibility to adapt the learning path to learner profiles.
Unable to display preview. Download preview PDF.