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Going beyond your personal learning network, using recommendations and trust through a multimedia question-answering service for decision-support: A case study in the healthcare.

Holley, D., Santos, P., Dennerlein, S., Theiler, D., Cook, J., Treasure-Jones, T., Attwell, G., Kowald, D. and Lex, E., 2016. Going beyond your personal learning network, using recommendations and trust through a multimedia question-answering service for decision-support: A case study in the healthcare. Journal of Universal Computer Science, 22 (3), 340-359.

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Abstract

Social learning networks enable the sharing, transfer and enhancement of knowledge in the workplace that builds the ground to exchange informal learning practices. In this work, three healthcare networks are studied in order to understand how to enable the building, maintaining and activation of new contacts at work and the exchange of knowledge between them. By paying close attention to the needs of the practitioners, we aimed to understand how personal and social learning could be supported by technological services exploiting social networks and the respective traces reflected in the semantics. This paper presents a case study reporting on the results of two co-design sessions and elicits requirements showing the importance of scaffolding strategies in personal and shared learning networks. Besides, the significance of these strategies to aggregate trust among peers when sharing resources and decision-support when exchanging questions and answers. The outcome is a set of design criteria to be used for further technical development for a social semantic question and answer tool. We conclude with the lessons learned and future work.

Item Type:Article
ISSN:0948-695X
Additional Information:This paper is from a six month sabbatical with the EU Learning layers project http://learning-layers.eu/ All articles published in J.UCS so far (21 volumes) are accessible free of charge in compliance with our open access policy which was made possible through the generous support of Graz University of Technology, Austria.
Uncontrolled Keywords:social learning network ; multi-media; Semantic Networks, Question-answering systems, Decision support
Group:University Executive Team
ID Code:23900
Deposited By: Symplectic RT2
Deposited On:14 Jun 2016 11:02
Last Modified:14 Mar 2022 13:56

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