This chapter analyses existing languages for the dynamic composition of distributed resources with particular emphasis on e-learning objects and services that may be exploited in a Learning Grid. The application of such languages has a paramount importance where heterogeneous services are distributed on the Grid and have to be dynamically composed according to learners needs and preferences and to teacher defined learning methods and strategies. The paper first explores education modelling languages, i.e. languages thought to manage workflows of learning activities (so learning-oriented but not specifically service-oriented); then it deepens services composition languages, i.e. languages thought for static or dynamic composition of Web Services of any nature (so service-oriented but not specifically learning-oriented). In both cases, the description of languages and related tools is followed by a comparison and by the definition of extensions needed in order to be fully exploitable in a Learning Grid environment.
Educational Modelling and Service Composition on the Learning Grid
GAETA, Angelo;MIRANDA, Sergio;ORCIUOLI, Francesco
2008
Abstract
This chapter analyses existing languages for the dynamic composition of distributed resources with particular emphasis on e-learning objects and services that may be exploited in a Learning Grid. The application of such languages has a paramount importance where heterogeneous services are distributed on the Grid and have to be dynamically composed according to learners needs and preferences and to teacher defined learning methods and strategies. The paper first explores education modelling languages, i.e. languages thought to manage workflows of learning activities (so learning-oriented but not specifically service-oriented); then it deepens services composition languages, i.e. languages thought for static or dynamic composition of Web Services of any nature (so service-oriented but not specifically learning-oriented). In both cases, the description of languages and related tools is followed by a comparison and by the definition of extensions needed in order to be fully exploitable in a Learning Grid environment.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.