Biblio

Mixed reality (MR) technologies are widely used in distributed collaborative learning scenarios and have made learning and training more flexible and intuitive. However, there are many challenges in the use of MR due to the difficulty in creating a physical presence, particularly when a physical task is being performed collaboratively. We therefore developed a novel MR system to overcomes these limitations and enhance the distributed collaboration user experience. The primary objective of this paper is to explore the potential of a MR-based hand gestures system to enhance the conceptual architecture of MR in terms of both visualization and interaction in distributed collaboration. We propose a synchronous prototype named MRCollab as an immersive collaborative approach that allows two or more users to communicate with a peer based on the integration of several technologies such as video, audio, and hand gestures.

Globally distributed collaboration requires cooperation and trust among team members. Current research suggests that informal, non-work related communication plays a positive role in developing cooperation and trust. However, the way in which teams connect, i.e. via a social network, greatly influences cooperation and trust development. The study described in this paper employs agent-based modeling and simulation to investigate the cooperation and trust development with the presence of informal, non-work-related communication in networked teams. Leveraging game theory, we present a model of how an individual makes strategic decisions when interacting with her social network neighbors. The results of simulation on a pseudo scale-free network reveal the conditions under which informal communication has an impact, how different network degree distributions affect efficient trust and cooperation development, and how it is possible to "seed" trust and cooperation development amongst individuals in specific network positions. This study is the first to use agent-based modeling and simulation to examine the relationships between scale-free networks' topological features (degree distribution), cooperation and trust development, and informal communication.