Recommendation of open educational resources. An approach based on linked open data

In an open and distributed platform as the Web there are problems associated with the heterogeneity and information overload. In this context, teaching community and learners may need some support to discover the Open Educational Resources best suited for their learning processes. In this paper, the authors propose the high-level design of a framework for the recommendation of learning content in a flexible way. In order to provide a personalized set of resources, an adaptive approach of filtering is used according to the data available of each user. To achieve this goal, the framework has been designed taking into account the best features provided by technologies of the Semantic Web in order to find online material.

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