Explicit Intelligence in Adaptive Hypermedia: Generic Adaptation Languages for Learning Preferences and Styles
نویسندگان
چکیده
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.
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تاریخ انتشار 2005