Mobile technologies

Mobile technologies are powerful tools that allow individuals to immerse themselves into authentic scientific inquiries that will potentially lead to learning (Colella, 2000; Klopfer, Yoon & Rivas, 2004; Squire & Klopfer, 2007). While virtual learning environments may allow learners to explore these spaces through the use of an avatar, by interacting with simulations or with instructing teachable agents, learners are confined in a physical space, usually the computer laboratory. Colella (2000) notes that participatory simulations, or "life-sized, computer-supported simulations" (pg. 471) are microworlds that have underlying rules that constrain a user's actions. Participatory simulations moreover allow students to construct an understanding of the world by using their intuitions (Klopfer, Yoon & Rivas, 2004) and create a safe space where students can potentially learn from their failures (Squire & Klopfer, 2007). While the potential of mobile technologies are important, the lack of feedback and scaffolding may impact students' learning, as demonstrated by Squire and Klopfer (2007). While the idea of a sandbox may be interesting, free play in participatory simulations is arguably similar to the concept of pure discovery learning, where students receive no guidance from the instructor (cf. Mayer, 2004). In contrast, Colella's (2000) analysis of the disease simulation underscores the importance of framing these activities in a way that students are able to make sense findings although there was no analysis of the impact of researchers and facilitators in guiding student understanding. Regardless of these findings, mobile technologies can indeed be powerful learning tools, if designed carefully.

Model 3.1

With this in mind, I have not updated the old model, because I believe that it is still able to explain the interactions within this particular system/ecology. However, I have explicated certain aspects of the model and created two separate Participatory Simulation models which illustrate the interactions between students. In particular, I used Bourdieu's (1986) concept of capital to explain how aspects of our lifeworld or our interpretations of our experiences are influenced by not only by our individual characteristics but also by other structures that exist independent of us (e.g., economy, educational qualifications, class, race, gender, etc.). This is a vital component to explicate because our interactions with others and objects are influenced by our lifeworlds, but the lifeworld is also changed through our interactions with others and objects. Objects themselves are not value-free; what we see of things in the world dictate how we interact with them. The designed mobile technologies for instance are value-laden objects that have to be unpacked by students. At the same time, the role of the instructor cannot be taken out of any learning situation, if one wants to achieve better learning (see model 3.2).

Model 3.2

The elaboration of lifeworlds moreover, is useful when one tries to understand how a female student would approach mobile technologies, in contrast to a male student. Note that the outcome of such interactions affect our ways of thinking and being, which can be thought of outcomes or goals for a given activity. Using Klopfer, Yoon and Rivas' (2004), findings about increased students learning, the model illustrates that despite an apparent difference in attitudes towards games, females experienced learning gains, comparable to their  their male counterpart, as illustrated in model 3.3. Thus, we are able to focus on aspects of the object or activity design that may have resulted in this gain. Currently, the model is unable to pinpoint the various aspects within the system/design that has to be changed, but given that its focus is on the interactions between individuals and objects, perhaps another model or revision may be in order. Suggestions and feedback regarding this is welcomed!

Model 3.3