Home › Theoretical and Architectural Support for Mobile Group Learning

Mobile phones and portable internet tablets have become the most popular computing devices in human history. Mobile devices are changing the ways that we complete our daily tasks and interact with people in the same way PCs have in the past thirty years. The high penetration rate of mobile devices provides both challenges and opportunities in learning. On one hand, researchers have been exploring the usage of mobile phones and PDAs as new education vehicles and numerous publications have been created; On the other hand, many mobile learning projects treat mobile devices as "smaller/cheaper PCs" and a major portion of research efforts focus on porting the existing educational applications for PCs to mobile devices, hence enabling "education anytime, anywhere".

Interestingly, the emergence of several "killer applications" in the mobile space does show that when designed properly, mobile applications can engage, motivate and entertain users in ways that are not possible on desktop computers. At least three common themes show up in almost every successful application - first, the introduction of social dynamics in the application logic; second, the active usage of context information (location, time, nearby people); third, proper incentive mechanism. In this project, we will analyze successful mobile social applications and games and document lessons and insights in this new field via design patterns. Such efforts will aid practice by speeding up the diffusion of new interaction techniques in mobile learning and presenting the information in a form more usable to educators. We will design and implement key architectural support for enabling mobile group learning applications, making it easier and faster to build high quality, domain-specific mobile group learning systems. Based on the platform we create, we plan to design, build and evaluate at least one group-based mobile learning application. Such efforts will allow us to do "learning by doing" and start iterating the implementation by running some small scale deployments.