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Please use this identifier to cite or link to this item: http://hdl.handle.net/1820/1881

Title: Improving the Unreliability of Competence Information: an Argumentation to Apply Information Fusion in Learning Networks
Authors: Miao, Yongwu
Sloep, Peter
Hummel, Hans
Koper, Rob
Keywords: competences
learning network
information fusion
automated competence tracking
lifelong competence development
self-directed learning
competence profile
competence proficiency level
evidence record
competence record
Issue Date: 24-Mar-2009
Abstract: Automated competence tracking and management is crucial for an effective and efficient lifelong competence development in learning networks. In this paper, we systematically analyze the problem of unreliability of competence information in learning networks. In tracking the development of competences in learning networks, a large amount of competence information can be gathered from diverse sources and diverse types of sources. Individual information is more or less credible. This paper investigates information fusion technologies that may be applied to address the problem and that show promise as candidate solutions for achieving an improved estimate of competences by fusing information coming from multiple sources and diverse types of sources.
Description: Miao, Y., Sloep, P. B., Hummel, H., & Koper, R. (2009). Improving the Unreliability of Competence Information: an Argumentation to Apply Information Fusion in Learning Networks [Special issue]. International Journal of Continuing Engineering Education and Life-Long Learning (IJCEELL), 19(4/5/6), 366-380.
URI: http://hdl.handle.net/1820/1881
Appears in Collections:1. TENC: Publications and Preprints

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