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Individual differences in navigating and experiencing presence in virtual environments

Research output: ThesisDoctoral Thesis

Publication date2004
Number of pages291
Awarding Institution
  • National University of Dublin
Award date20/04/2004
  • National University of Dublin
<mark>Original language</mark>English


The effort of making Virtual Environments (VEs) more useful and satisfactory to use lie at the core of usability research. Because of their development and widespread accessibility, VEs are being used by an ever-increasing diversity of users, whose individual differences impact on both task performance and level of satisfaction. This aspect raises a major challenge in terms of designing adaptive VEs, suitable not for the average user but for each individual user. One way to address this challenge is through the study of individual differences and their implications, which should lead to new effective ways to accommodate them.
Adaptivity reflects the system’s capability to automatically tailor itself to dynamically changing user behaviour. This capability is enabled by a user model, acquired on the basis of identifying the user’s patterns of behaviour.
This thesis addresses the issue of studying and accommodating individual differences with the purpose of designing adaptive VEs. The individual differences chosen to be investigated are those that impact particularly on two fundamental aspects underlying each interaction with a VE, namely navigation and sense of presence. Both these aspects are related to the perceived usability of VEs.
The impact that a set of factors like empathy, absorption, creative imagination
and willingness to be transported within the virtual world has on presence has been investigated and described through a prediction equation. Based on these findings, a set of guidelines has been developed for designing VEs able to accommodate these individual differences in order to support users to experience a higher level of presence.
The individual differences related to navigation within VE have been investigated in the light of discriminating between efficient versus inefficient search strategies. Building a user model of navigation affords not only a better understanding of user spatial behaviour, but also supports the development of an adaptive VE which could help low spatial users to improve their navigational skills by teaching them the efficient navigational rules and strategies.