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Recommender Systems Make Learning More Fun

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As part of the European Union TENCompetence project, the Centre for Learning Sciences and Technologies' Hendrik Drachsler searched for the most suitable way to recommend learning activities, considering the personal needs, preferences, and learning goals of community members.

Drachsler explored commercial navigation and recommendation systems and concluded that the specific behavior of community members required a combination of different recommendation techniques. Drachsler developed a prototype navigation system and ran experiments to determine if such a system offers additional value to informal learning communities. The project concluded that the system has a significantly positive influence on learning. The experiment group needed less time to complete the same number of learning activities, and participants in the group chose more personalized learning paths than members in a control group, primarily because they explored more learning paths.

A second experiment showed there was no noticeable difference between informal and traditional learners, but that informal learners were more satisfied with the experience. The results of the study led to a second prototype, called ReMashed, which shows how recommendation systems can benefit from the information gathered through Web 2.0 technology by life-long learners in a learning network. ReMashed recommends the most suitable sources using tags and evaluations from individual learners.

From Centre for Learning Sciences and Technology
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Abstracts Copyright © 2009 Information Inc., Bethesda, Maryland, USA


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