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Drawing on the experiences and context of others who have already used a particular resource can greatly facilitate that resource's reuse. Such reuse is essential when the resources in question are digital learning assets, services and models which are expensive both in terms of time and monetary expenditure to develop and use. When these resources are deployed in personalised settings, where each user may be delivered a tailored sequence of resources that uniquely suits their particular needs, gathering and federating a rich view of how these resources are being used becomes important. In this article we describe an approach to facilitating the federating of contextual usage data, which is compiled over the life cycle of a resource. Given that this data is likely to come from a range of different sources, our approach will need to be able to cope with the high level of heterogeneity expected in terms of its structure, syntax and semantics. We describe how such data may be used to support users in assessing the value of learning resources and facilitating their appropriate reuse.
Date of Conference: 3-5 Aug. 2011