Detection of Online Learning Activity Scopes

During last ten years, online learning has been on the ascent as the advantages of access, accommodation, and quality learning are beginning to take shape. A key challenge is to identify learning activities and recognize how they participate in the learner’s progress. In this paper, we look at the way this problems becomes even more challenging when considering the full set of online activities carried out by a learner, as compared to what is achieved on specific online platforms that are dedicated to learning. We in particular show how the integration of linked data-based information can help resolve the issue of representing activities for the purpose of identifying the key topics on which a learner is focusing, in a hierarchical clustering method. We apply this approach in the context of the AFEL project, and show how it performs in realistic use cases of an online learner’s profile, comparing general browsing with the use of a dedicated learning platform.

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