Traditional approaches to learning have often focused upon knowledge transfer strategies that have centred on textually-based engagements with learners, and dialogic methods of interaction with tutors. The use of virtual worlds, with text-based, voice-based and a feeling of 'presence' naturally is allowing for more complex social interactions and designed learning experiences and role plays, as well as encouraging learner empowerment through increased interactivity. To unpick these complex social interactions and more interactive designed experiences, this paper considers the use of virtual worlds in relation to structured learning activities for college and lifelong learners. This consideration necessarily has implications upon learning theories adopted and practices taken up, with real implications for tutors and learners alike. Alongside this is the notion of learning as an ongoing set of processes mediated via social interactions and experiential learning circumstances within designed virtual and hybrid spaces. This implies the need for new methodologies for evaluating the efficacy, benefits and challenges of learning in these new ways. Towards this aim, this paper proposes an evaluation methodology for supporting the development of specified learning activities in virtual worlds, based upon inductive methods and augmented by the four-dimensional framework reported in a previous study.The study undertaken aimed to test the efficacy of the proposed evaluation methodology and framework, and to evaluate the broader uses of a virtual world for supporting lifelong learners specifically in their educational choices and career decisions. The paper presents the findings of the study and considers that virtual worlds are reorganising significantly how we relate to the

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We explore flexible querying of RDF data, with the aim of making it possible to return data satisfying query conditions with varying degrees of exactness, and also to rank the results of a query depending on how "closely" they satisfy the query conditions. We make queries more flexible by logical relaxation of their conditions based on RDFS entailment and RDFS ontologies. We develop a notion of ranking of query answers, and present a query processing algorithm for incrementally computing the relaxed answer of a query. Our approach has application in scenarios where there is a lack of understanding of the ontology underlying the data, or where the data objects have heterogeneous sets of properties or irregular structures.

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