Explicit intelligence in adaptive hypermedia : generic adaptation languages for learning preferences and styles

This paper deals with a new challenge in Adaptive Hypermedia and Web-based systems: finding the perfect adaptation language to express, independently from the domain model, the intelligent, adaptive behaviour of personalized Web courseware. The major requirements for the ideal language are: reuse, flexibility, high level semantics, and ease of use. To draw closer to this ideal language, we compare two such language proposals: LAG, a generic adaptation language, and a new XML adaptation language for learning styles in AHA!, LAG-XLS