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

Patricia Santos, Sebastian Dennerlein, Dieter Theiler, John Cook, Tamsin Treasure-Jones, Debbie Holley, Micky Kerr, Graham Attwell, Dominik Kowald, Elisabeth Lex

Research output: Contribution to journalArticle

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.

Original languageEnglish
Pages (from-to)340-359
Number of pages20
JournalJournal of Universal Computer Science
Volume22
Issue number3
Publication statusPublished - 1 Jan 2016

Keywords

  • Decision support
  • Question-answering systems
  • Semantic networks

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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