Within the context of pervasive learning as a response to the diminishing barriers between formal and informal, digital and physical spaces and real and virtual contexts, there is a need to address the mammoth challenge in advocating seamless learning conceptually, practically and technically. How can the transitions be fostered and optimised? There are various technologies that can be pedagogically repurposed to ensure feasibility in terms of the desired learning outcomes.
The objective behind pervasive and context aware systems is to deliver the most relevant and personalised set of services to the end-user in a timely and on-demand way. Most mobile/portable devices have embedded motion and environmental sensors. Potential for personalised and location/status/time based services is growing exponentially and makes the process of context data distribution very complex and demanding on technology resources such as wireless bandwidth, processing power, storage capacity and artificial intelligence functionality. The combination of sensor variables that might affect the context data needed by one individual creates complexity in its own right but when context sensitive applications may also need to factor in similar variables from other users in the same physical or temporal space it creates an even more demanding environment. There are some issues with such a pervasive systems in terms of connection reliability. It is important that the GPS signal and Wifi work well in order to understand the exact position of the learners. Current technologies for location tracking can have significant accuracy limitations, especially indoors.
Motivated to explore this further, I had an interesting discussion with the CEO of daVinci Studio, based locally in the West Midlands. He showcased their Beacon technology that could be part of an infrastructure that supports context-aware educational resources within the pervasive learning scenario. Bluetooth connection indoor provides the reliability that is much needed to ensure a seamless experience in and outdoor. Watch the interesting promotional video here.
I aim to look into this further. Contact me if you are interested in similar challenges.
 Paolo Bellavista, Antonio Corradi, Mario Fanelli, And Luca Foschini. A Survey of Context Data Distribution for Mobile Ubiquitous Systems. ACM Computing Surveys
 Schmitz, B., Klemke, R., & Specht, M. (2013). A Learning Outcome-Oriented Approach towards Classifying Pervasive Games for Learning using Game Design Patterns and Contextual Information. International Journal of Mobile and Blended Learning (IJMBL), 5(4), 59-71.
 Korhonen H., Saarenpää H., Paavilainen J. – Pervasive Mobile Games – a New Mindset for Players and Developers, Fun and Games 2008, LNCS 5294, pp. 21-32