A Comparative Study of Platforms for Multi-User Virtual Environments

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Author(s): Arda Tezcan (Macquarie University, Australia)and Debbie Richards (Macquarie University, Australia)
Copyright: 2011
Pages: 34
Source title: Multi-Agent Systems for Education and Interactive Entertainment: Design, Use and Experience
Source Author(s)/Editor(s): Martin Beer (Sheffield Hallam University, UK), Maria Fasli (University of Essex, UK)and Debbie Richards (Macquarie University, Australia)
DOI: 10.4018/978-1-60960-080-8.ch008

Keywords: Agent Technologies / Artificial Intelligence / Computer Science & IT / Information Science Reference

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Abstract

Multi-User Virtual Environments (MUVEs) have been found to be engaging and provide an environment in which the elements of discovery, exploration and concept testing, fundamental to the field of science, can be experienced. Furthermore, MUVEs accommodate lifelike experiences with the benefit of the situated and distributed nature of cognition; they also provide virtual worlds to simulate the conditions that are not doable or practicable under real world circumstances making them very relevant to many other fields of study such as history, geography and foreign language learning. However, constructing MUVEs can be expensive and time consuming depending on the platform considered. Therefore, providing the most appropriate platform that requires minimal effort, cost and time will make MUVE deployment in the classroom faster and more viable. In this chapter, the authors provide a comparative study of prominent existing platforms for MUVEs that can be used to identify the right balance of functionality, flexibility, effort and cost for a given educational and technical context. A number of metrics are identified, described and used to enable the comparison. Platform assessment was done in four main metric groups: communication and interaction, characters, features and education. Communication and interaction metrics are used to assess how the communication and interaction is done within the examined platform. Character metrics are employed to measure avatar and agent affordances. Features metrics are defined to compare what the platform offers in terms of technology. Lastly, education metrics are used to identify the value of the associated platform for educational purposes.

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