The Usability of Collaborative Virtual Environments and Methods for the Analysis of Interaction

Abstract

This paper describes two methods for analyzing interactions in collaborative virtual environments (CVEs): one whereby quantitative data are captured, interaction is categorized into a number of activities, and statistical analysis can be performed on frequencies and sequences of events. The other is based on the transcription of individual fragments of interaction, which are analyzed in terms of their key dynamics. The two methods each have their strengths and weaknesses, especially in terms of generalizability and the lessons we can derive from them. Both also point to different problems that need to be addressed in methods for analyzing interactionsuch analysis being, in turn, a precondition for improving the usability of CVEs. The paper concludes with an argument for a combination of the two methods, and some reflections about the relationship between the analysis of interaction and the usability of CVEs.

Investigating user experience in Second Life for collaborative learning

“…Representational fidelity and the embodied nature of interaction and communication have been proposed as learning affordances of CVEs (Dalgarno and Lee, 2010), while Schmeil and Eppler (2008) describe patterns of interaction and learning for Second Life, set in a framework for increasing ambition and design effort. Some studies of collaboration in CVEs have suggested that presence and user experience can be superior to conventional 2D interfaces since avatars improve the awareness of others and shared tasks (Schroeder et al, 2006;Tromp et al, 2003). Comparisons of performance between CVEs and real-world equivalents have nevertheless failed to show any clear advantage for virtual worlds; for example, in training medical students in interviewing skills for diagnosis, the VE performed as well as work with real patients but was less satisfying (Johnsen www.elsevier et al, 2010).…”

Mobile Group Dynamics in Large-Scale Collaborative Virtual Environments

“…The analysis of teamwork consisted of a combination of two methods based on those in [15]. The first method was quantitative, in which the communication and spatial positioning between participants were analyzed, and the results for the MGDs and control conditions were compared.…”

“…The first method was quantitative, in which the communication and spatial positioning between participants were analyzed, and the results for the MGDs and control conditions were compared. The second method was qualitative, an 'analysis of interaction fragments' [15] (p. 661), in which the paths of the core participants in the MGDs condition were analyzed to draw out patterns of interaction.…”

Collaboration Patterns in Mixed Reality Environments for a New Emergency Training Center

“…From current training practices, we understand that narratives and chains of activities need to be handled at such a center while there is simultaneously a need to understand how to determine the influence of (new) technologies. This paper combines two ideas: developing scenarios for a future training center, designing and performing a pilot study that is naturalistic (see Figure 1) and using an evaluation method for collaboration in mixed reality environments [1]. It contributes to defining the usefulness of certain scenarios for developing new ETCs [13].…”