A Proposed Architecture for Learning Object Selection and Discovery Based on WSMO

Recent researches combined the semantic web services paradigm with the search for e-learning resources. Meanwhile, more and more learning resources are generated by different courseware providers. This paper presents a learner selection and discovery architecture for distributed e-learning environments based on semantic Web services (SWS) to allow sharing, discovery, filtering and recommending relevant learning objects (LOs) based on learner profile through courseware providers. This paper presents an SWS architecture which is based on Web service modeling ontology (WSMO), and which uses the learning object metadata (LOM) standard to describe the learning object.