An expert review of REVERIE and its potential for game-based learning
Doumanis, Ioannis, Porter, Stuart, Economou, Daphne and Smith, Serengul 
ORCID: https://orcid.org/0000-0003-0777-5637
(2015)
An expert review of REVERIE and its potential for game-based learning.
Workshop Proceedings of the 11th International Conference on Intelligent Environments.
In: The 11th International Conference on Intelligent Environments - IE'15, 13-14 July 2015, Prague.
ISBN 9781614995296.
[Conference or Workshop Item]
(doi:10.3233/978-1-61499-530-2-306)
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Abstract
REVERIE (REal and Virtual Engagement in Realistic Immersive Environments) is a research project with the aim to build a safe, collaborative, online environment which brings together realistic inter-personal communication and interaction. The REVERIE platform integrates cutting-edge technologies and tools, such as social networking services, spatial audio adaptation techniques, tools for creating personalized lookalike avatars, and artificial intelligence (A.I) detection features of the user’s affective state into two distinct use cases. The first shows how REVERIE can be used in educational environments with an emphasis on social networking and learning. The second aims to emulate the look and feel of real physical presence and interaction for entertainment and collaborative purposes. This paper presents an expert evaluation of the first use case by potential users of REVERIE (teachers and students). Finally, the potential of REVERIE for game-based learning is discussed and follow this with an overview of the actionable recommendations that emerged as a result of the expert review.
| Item Type: | Conference or Workshop Item (Paper) |
|---|---|
| Research Areas: | A. > School of Science and Technology > Computer Science > Intelligent Environments group |
| Item ID: | 17216 |
| Notes on copyright: | © 2015 The Authors.
This article is published online with Open Access by IOS Press and distributed under the terms of the Creative Commons Attribution Non-Commercial License. |
| Useful Links: | |
| Depositing User: | Serengul Smith |
| Date Deposited: | 10 Jul 2015 13:15 |
| Last Modified: | 29 Nov 2022 22:36 |
| URI: | https://eprints.mdx.ac.uk/id/eprint/17216 |
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