Collaborative virtual gaming worlds in higher education

There is growing interest in the use of virtual gaming worlds in education, supported by the increased use of multi‐user virtual environments (MUVEs) and massively multi‐player online role‐playing games (MMORPGs) for collaborative learning. However, this paper argues that collaborative gaming worlds have been in use much longer and are much wider in scope; it considers the range of collaborative gaming worlds that exist and discusses their potential for learning, with particular reference to higher education. The paper discusses virtual gaming worlds from a theoretical pedagogic perspective, exploring the educational benefits of gaming environments. Then practical considerations associated with the use of virtual gaming worlds in formal settings in higher education are considered. Finally, the paper considers development options that are open to educators, and discusses the potential of Alternate Reality Games (ARGs) for learning in higher education. In all, this paper hopes to provide a balanced overview of the range of virtual gaming worlds that exist, to examine some of the practical considerations associated with their use, and to consider their benefits and challenges in learning and teaching in the higher education context

Virtual Reality Games for Motor Rehabilitation

This paper presents a fuzzy logic based method to track user satisfaction without the need for devices to monitor users physiological conditions. User satisfaction is the key to any product’s acceptance; computer applications and video games provide a unique opportunity to provide a tailored environment for each user to better suit their needs. We have implemented a non-adaptive fuzzy logic model of emotion, based on the emotional component of the Fuzzy Logic Adaptive Model of Emotion (FLAME) proposed by El-Nasr, to estimate player emotion in UnrealTournament 2004. In this paper we describe the implementation of this system and present the results of one of several play tests. Our research contradicts the current literature that suggests physiological measurements are needed. We show that it is possible to use a software only method to estimate user emotion