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As an alternative to real-world training, synthetic environments using virtual reality (VR) technology have found a number of applications in a range of fields (e.g. Stone 2002). One disadvantage of VR is that state of the art virtual environments are often costly to build and maintain (Lepouras & Vassilakis, 2005). A cheaper alternative to building training systems using virtual environment development toolkits is to use computer games technology.
Designed to educate, train and inform, systems that use such video game technology have been termed “serious games”. Acknowledging the motivational element of game-based learning (Moreno-Ger et al., 2008), serious games aim to reproduce the engagement generated during game play within the training environment. The objective is that this increased level of engagement will help the player of the game to develop knowledge, skills and attitudes that can be transferred from the game-playing environment to the real world (Bergeron, 2006).
With simulated visualisations, authentic problem solving and instant feedback, Ke (2009) highlights that computer games afford a realistic framework for experimentation and situated understanding and can therefore act as rich primers for active learning. In addition, the multisensory representations in computer games may also help in the construction and indexing of schema.
Using gaming technology may also be advantageous due to their ease of adaptation to create new content, using tools and source codes provided by the developers, their general robustness, and their ease of dissemination (Trenholme & Smith, 2008).
In the field of medicine, synthetic environments have long been employed as a training tool, specifically with the use of VR simulators for applications such as surgical skill training (e.g. Kundahl & Grancharov, 2009). Here games technology has also been proposed (e.g. Sliney & Murphy, 2008). These applications may not currently help train the motor skills employed in the surgical procedure, which may require specific and specialised input devices, but serious games may be appropriate to develop other medical skills. For example, the interactive trauma trainer (ITT) is a decision making trainer for a surgical procedure (Stone & Barker, 2006; Stone 2011). In the ITT, the user has to make appropriate decisions relating to the urgent treatment of an incoming virtual casualty. This involves making appropriate interventions, which have to be applied in less than 5 minutes in order to save the virtual casualty’s life. However, rather than replicate the dextrous surgical handling skills the user would already possess, the ITT employs a simple gaming interface, using a mouse control for viewpoint change, option selection and instrument acquisition. The purpose of the ITT serious game being to develop the decision-making skills of the surgeon and develop inter-personnel interaction skills within the surgical team.
Evaluation of training tools, such as simulators, often involves comparison of performance variables with real world metrics or by transfer of learning measures (Gopher et al.,1994, Lathan et al., 2002). Evaluations of the usability of simulators, virtual environments and virtual reality products and the methods employed for such evaluations have also been reported (Gabbard et al., 1999; Bowman et al., 2002; Karaseitanidis et al., 2006). These evaluations go some way to determining the likely effectiveness of the systems. However, a factor that may be overlooked during these evaluations is the acceptance of the technology by the user. Here, acceptability refers to constructs that affect the intention of the user to use the technology. Systems with low acceptability may well meet technical performance standards but may still not be widely adopted.