Title: Combining social-based and information-based approaches for personalised recommendation on sequencing learning activities

Authors: Hans G.K. Hummel, Bert Van Den Berg, Adriana J. Berlanga, Hendrik Drachsler, Jose Janssen, Rob Nadolski, Rob Koper

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

Abstract: Lifelong learners who select learning activities to attain certain learning goals need to know which are suitable and in which sequence they should be performed. Learners need support in this way-finding process, and we argue that this could be provided by using Personalised Recommender Systems (PRSs). To enable personalisation, collaborative filtering could use information about learners and learning activities, since their alignment contributes to learning efficiency. A model for way-finding presents personalised recommendations in relation to information about learning goals, learning activities and learners. A PRS has been developed according to this model, and recommends to learners the best next learning activities. Both model and system combine social-based (i.e., completion data from other learners) and information-based (i.e., metadata from learner profiles and learning activities) approaches to recommend the best next learning activity to be completed.

Keywords: personalised recommender systems; PRS; collaborative filtering; sequencing; learner profiles; learning technology specifications; domain models; way-finding; sequencing learning; lifelong learning; learning goals; learning activities.

DOI: 10.1504/IJLT.2007.014842

International Journal of Learning Technology, 2007 Vol.3 No.2, pp.152 - 168

Published online: 12 Aug 2007 *

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