Ruben Verborgh’s data

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Matches in dataset index for { ?s ?p "More and more users obtain new knowledge using e-learning systems, and often assess their understanding of this new knowledge using corresponding assessment items. However, the distribution of content items and assessment items in a learning object is tightly bound. To publish assessment items, independently of the corresponding content items, it is required to wrap these assessment items into separate learning objects, which introduces a large overhead. Moreover, current learning objects are closely coupled with their execution environment. A stand-alone and lightweight format to describe assessment items is needed. This way their publication is facilitated and their discoverability can be increased. This paper proposes some important features for such a format and introduces SERIF: a Semantic ExeRcise Interchange Format, whose underlying data model is based on the QTI data model. SERIF was applied successfully in three proof-of-concept applications, where we assessed how SERIF is (i) decoupled from the execution environment, and (ii) extendable to other content types and interaction types. Its machine-interpretability can allow for automatic discovery and combination of relevant assessment items."@en }

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