Open Universiteit

Please use this identifier to cite or link to this item:
Title: Combining Social- and Information-based Approaches for Personalised Recommendation on Sequencing Learning Activities
Authors: Hummel, Hans
Van den Berg, Bert
Berlanga, Adriana
Drachsler, Hendrik
Janssen, José
Nadolski, Rob
Koper, Rob
Keywords: collaborative filtering
personalised recommender systems
learner profile
domain model for way finding
learning technology specifications
Issue Date: 24-Nov-2006
Abstract: Lifelong learners who assign learning activities (from multiple sources) to attain certain learning goals throughout their lives need to know which learning activities are (most) suitable and in which sequence these should be performed. Learners need support in this way finding process (selection and sequencing), and we argue this could be provided by using personalised recommender systems. 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 has been developed that presents personalised recommendations in relation to information about learning goals, learning activities and learners. A personalised recommender system has been developed accordingly, and recommends learners on 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.
Description: Hummel, H. G. K., Van den Berg, E. J., Berlanga, A. J., Drachsler, H., Janssen, J., Nadolski, R.J., & Koper, E.J.R. (2007). Combining social- and information-based approaches for personalised recommendation on sequencing learning activities. International Journal of Learning Technology, 3(2), 152-168.
Appears in Collections:1. TENC: Publications and Preprints
1. LN: Publications and Preprints
Keur der Wetenschap

Files in This Item:
File Description SizeFormat 
IJLT 2007 proof_Hummel.pdf496.01 kBAdobe PDFView/Open

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.