Adaptivity for knowledge content in the semantic web

Abstract

The focus of this report is the adaptivity issue for Learning Objects owned by Learning (Web) Services. We address this issue based on the Concept, Resource, Order, Product (CROP) Reference Architecture that we briefly review here. Based on the essentially recursive notion of a learning object in our CROP architecture, we propose that adaptivity of learning objects is best viewed as a property of the network of learning services and the learning objects they own, i.e. as an emergent property of learning service communication and collaboration. For such a communication and collaboration to be successful with respect to an adaptive response goal, we propose that (besides adopting a standard reference architecture for learning objects) a global model of learning styles needs to be agreed upon. We contribute in this direction by presenting a basis for a global model of learning styles, by elaborating a systematic classification of the learning styles dimensions proposed in various models, uncovering relationships of concept identity or subsumption and distinguishing between base and definable concepts.