Title: Personal recommender systems for learners in lifelong learning networks: the requirements, techniques and model

Authors: Hendrik Drachsler, Hans G.K. Hummel, Rob Koper

Addresses: Educational Technology Expertise Centre, Open University of the Netherlands, Valkenburgerweg 177, 6419 AT Heerlen, The Netherlands. ' Educational Technology Expertise Centre, Open University of the Netherlands, Valkenburgerweg 177, 6419 AT Heerlen, The Netherlands. ' Educational Technology Expertise Centre, Open University of the Netherlands, Valkenburgerweg 177, 6419 AT Heerlen, The Netherlands

Abstract: This article argues that there is a need for Personal Recommender Systems (PRSs) in Learning Networks (LNs) in order to provide learners with advice on the suitable learning activities to follow. LNs target lifelong learners in any learning situation, at all educational levels and in all national contexts. They are community-driven because every member is able to contribute to the learning material. Existing Recommender Systems (RS) and recommendation techniques used for consumer products and other contexts are assessed on their suitability for providing navigational support in an LN. The similarities and differences are translated into specific requirements for learning and specific requirements for recommendation techniques. The article focuses on the use of memory-based recommendation techniques, which calculate recommendations based on the current data set. We propose a combination of memory-based recommendation techniques that appear suitable to realise personalised recommendation on learning activities in the context of e-learning. An initial model for the design of such systems in LNs and a roadmap for their further development are presented.

Keywords: lifelong learning networks; learning technology; personal recommender systems; PRSs; collaborative filtering; content-based recommendation; user profiling; navigational support; memory-based recommendation; personalised recommendation; e-learning; electronic learning; online learning.

DOI: 10.1504/IJLT.2008.019376

International Journal of Learning Technology, 2008 Vol.3 No.4, pp.404 - 423

Published online: 09 Jul 2008 *

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