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Can effects of social influence be elicited in virtual contexts, and if so, under which conditions can they be observed? Answering these questions has theoretical merit, as the answers can help broaden our understanding of the interaction mechanisms described by social psychology. The increasing popularity of immersive media in training applications, however, has made these questions of practical significance. Virtual reality (VR), in particular, is a weapon of choice in designing training and education simulations, as it can be used to generate highly realistic characters and environments. As a consequence, it is key to understand under which circumstances virtual 'others' can facilitate or impede performance and -especially -learning. In this study, we investigated the impact of virtual onlookers on an adapted Serial Reaction Time (SRT) task that was presented in VR. In each trial, participants responded to a series of spherical stimuli by tapping them with handheld controllers when they lit up. Depending on the experiment block, the sequence order was either the permutation of a fixed order (and therefore predictable given the first stimulus), or fully random (and therefore unpredictable). Participants were divided into three groups (audience variable), depending on the environment in which the task was set: a group without onlookers (none condition), a group with a computer-generated audience (CGI condition), and a group being watched by a prerecorded audience (filmed condition). Results showed that the presence of a virtual audience can hamper both overall performance and learning, particularly when the audience appears more realistic. This study further reinforces the notion that the effects of social influence transcend the physical presence of others, but rather extend to virtual audiences.

No abstract

The development of immersive technologies has brought with it the need to redefine the concept of quality of experience (QoE). Studies have explored QoE in virtual reality (VR) by adopting a top-down approach-these are solely based on existing frameworks and theory, and complemented with novel technical considerations. It can be argued that any QoE framework derived in this manner is limited, as its scope is fixed even prior to any data gathering process. To this end, the current study proposes a bottom-up approach, involving the user in the formulation of a broader QoE model. The repertory grid technique (RGT) was used to analyse and group 360 attributes, listed by participants as criteria they used in judging the quality of a VR experience. The advantage of RGT is that it has a holistic approach towards the interpretation of the user's experience combined with the precision of quantitative analysis. The study resulted in a QoE model that consists of three main groups of attributes (i.e., user, content, and system). Furthermore, the analysis showed that participants listed attributes related to their experience and appraisal of VR, and to the content that they viewed. In contrast, very few system-related attributes were mentioned. Finally, the current study discussed the RGT methodology-and user-driven approaches in general-as a complementary research approach to create a comprehensive and practical QoE model.

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