Learner Modeling on the Semantic Web


Learners are assessed by several systems during their lifelong learning. Those systems can maintain fragments of information about a learner derived from his learning performance and/or assessment in that particular system. Customization services would perform better if they would be able to exchange as many relevant fragments of information about the learner as possible. This paper presents the conceptualization and implementation of a framework which provides a common base for the exchange of learner profiles between several sources

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oaioai:CiteSeerX.psu: time updated on 10/22/2014

This paper was published in CiteSeerX.

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