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.