Recommending Collaboratively Generated Knowledge

Weiqin Chen1, 2 and Richard Persen1

  1. Department of Information Science and Media Studies
    University of Bergen, POB 7802, N-5020 Bergen, Norway
    {weiqin.chen, richard.persen}@@infomedia.uib.no
  2. Faculty of Technology, Art and Design
    Oslo and Akershus university college of applied sciences
    POB 4, St. Olavs plass, NO-0130 Oslo, Norway

Abstract

With the development and adoption of information technologies in education, learners become active producer of knowledge. There is an increasing amount of content generated by learners in their learning process. These emerging learning objects (ELOs) could potentially be valuable as learning resources as well as for assessment purpose. However, the potentials also give rise to new challenges for indexing, sharing, retrieval and recommendation of such learning objects. In this research we have developed a recommender system for emerging learning objects generated in a collaborative knowledge building process and studied the implications and added values of the recommendations. We conducted two evaluations with learners to assess and improve the system´┐Żs design and study the quality and effects of the recommendations. From the evaluations, we received generally positive feedback and the results confirm the added values of the recommendations for the knowledge building process.

Key words

Recommender systems, collaborative knowledge, knowledge building, emerging learning objects

Digital Object Identifier (DOI)

https://doi.org/10.2298/CSIS111129017C

Publication information

Volume 9, Issue 2 (June 2012)
Year of Publication: 2012
ISSN: 1820-0214 (Print) 2406-1018 (Online)
Publisher: ComSIS Consortium

Full text

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How to cite

Chen, W., Persen, R.: Recommending Collaboratively Generated Knowledge. Computer Science and Information Systems, Vol. 9, No. 2, 871-892. (2012)