An adjustable personalization of search and delivery of learning objects to learners

This paper describes a technical solution realizing an approach for personalized search of learning objects on the Web, which proposes a comparison of a learner (user) profile and learning object descriptions. This comparison is based not only on values of attributes of the learner profile and attributes of the learning object descriptions, but it also considers the importance of these attributes for the learner. In order to implement such a search we propose to develop ontological models of the learner and learning objects as well as approaches for determination and adjustment of the learner's preferences using corresponding ontologies. For this purpose we have selected criteria of estimation of suitability of learning objects to the learner profile and introduced coefficients of importance of these criteria, as well as a method for adjusting these coefficients.

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