58 research outputs found
Qualitative Research In Online Language Learning - What Can It Do?
In this article we explore the theoretical foundations of qualitative research in online language learning. We will look at the distinction between offline and online language learning and discuss whether different ways of knowledge generation are appropriate for those different learning environments. Quantitative and qualitative methodologies will be examined and their fit with various learning theories evaluated. Fundamental theoretical differences between epistemologies supporting a realist ontology and those favouring relativist ontologies will be presented and set in the context of online and technology enhanced language learning research. Finally, we argue that a sociocultural framework, which goes beyond quantitative research approaches, is necessary to adequately understand the experiences of language learners and teachers who share a common interest in the new digital environments
A Semantic Web pragmatic approach to develop Clinical ontologies, and thus Semantic Interoperability, based in HL7 v2.xml messaging
The ISO/HL7 27931:2009 standard intends to establish a global interoperability framework for Healthcare applications. However, being a messaging related protocol, it lacks a semantic foundation for interoperability at a machine treatable level has intended through the Semantic Web. There is no alignment between the HL7 V2.xml message payloads and a meaning service like a suitable ontology. Careful application of Semantic Web tools and concepts can ease extremely the path to the fundamental concept of Shared Semantics. In this paper the Semantic Web and Artificial Intelligence tools and techniques that allow aligned ontology population are presented and their applicability discussed. We present the coverage of HL7 RIM inadequacy for ontology mapping and how to circumvent it, NLP techniques for semi-automated ontology population and discuss the current trends about knowledge representation and reasoning that concur to the proposed achievement
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