Despotakis, D, Dimitrova, V, Lau, LMS et al. (3 more authors) (2013) Views in user generated content for enriching learning environments: a semantic sensing approach. In: Lane, HC, Yacef, K, Mastow, J and Pavlik, P, (eds.) Lecture Notes in Computer Science. International conference on Artificial Intelligence in Education, 09-13 Jul 2013, Memphis, USA. Springer , 121 - 130. ISBN 978-3-642-39111-8
Abstract
Social user-generated content (e.g. comments, blogs) will play a key role in learning environments providing a rich source for capturing diverse viewpoints; and is particularly beneficial in ill-defined domains that encompass diverse interpretations. This paper presents Views - a framework for capturing viewpoints from user-generated textual content following a semantic sensing approach. It performs semantic augmentation using existing ontologies and presents the resultant semantic spaces in a visual way. Views was instantiated for interpersonal communication and validated in a study with comments on job interview videos, achieving over 82% precision. The potential of Views for enriching learning environments is illustrated in an exploratory study by analysing micro-blogging content collected within a learning simulator for interpersonal communication. A group interview with simulator designers evinced benefits for gaining insights into learner reactions and further simulator improvement.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Editors: |
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Keywords: | Social content; semantic augmentation and analysis; viewpoints; interpersonal communication; simulated environments for learning |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Computing (Leeds) > Institute for Computational and Systems Science (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 25 Sep 2014 16:43 |
Last Modified: | 19 Dec 2022 13:27 |
Published Version: | http://dx.doi.org/10.1007/978-3-642-39112-5_13 |
Status: | Published |
Publisher: | Springer |
Identification Number: | 10.1007/978-3-642-39112-5_13 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:80231 |