Enabling on-the-fly learning for mobile ad-hoc wireless networks using Bayesian theory

Due to the rapid increase in the number of mobile devices available to consumers, there is a need to evaluate these devices and their various features to see where they fit into the current idea of mobile learning. The emergence of lifelong learners has created a need for a new approach to learning so that learning can occur easily in non-standard classroom environments. Mobile learning is a new idea for learning because of the ubiquitous presence of mobile devices in people's lives and the possibility of learning anywhere from anyone it allows access to. Many problems exist with m-learning that have prevented its widespread adoption, outside of tests and limited classroom use that have been researched but never resolved. This paper offers an analysis of a few categories of questions that are important to mobile learning and critiques a few papers that investigate these areas. It also presents a new methodology to enable on-the-fly learning using emerging technology such as ad-hoc networks.