Project summary
There are many indications that digital learning environments such as simulations, videogames and virtual reality environments may provide a cognitive bridge between concrete experiences and scientific abstractions (Furness et al., 1997; Winn, 1993). Such a bridge is crucial for enabling students to cope with complex problem solving and other high order thinking skills that are at the core of scientific and technological learning (Resnik, 2002). Ellis (1983) argues that like any popular media, videogames have become the building blocks of children’s worlds. Children usually play in groups, and when they do not, they share their experiences socially. Hence, playing videogames cannot be properly understood as simply a human-machine interaction; rather it seems to be situated in social and cultural spheres that are perhaps more important than the game itself. Moreover, Gee (2003) argues that through informal game playing, children learn to participate in what he calls ‘semiotic domains’, which are shaped by children’s interactions with virtual agents and with each other. Similarly, Nijholt (2001) claims that developments in computer science (artificial intelligence, agent technology and graphics) have paved the way for the assimilation of smart agents within learning environments, as learners become more accustomed to such agents based on their prior videogame experience. However, the study of human-human/machine interactions within videogame learning environments and virtual reality environments is in its early stages (Adobbati et al., 2001; Gazit et al., 2003). We claim that, thus far, there have been few empirical studies which have systematically studied the processes of collaborative learning within videogame environments. The results of such studies would have meaningful implications for the design of effective smart agent interaction models.