An initial framework for implementing and evaluating probabilistic adaptivity in mobile learning

The needs of mobile learners change dynamically with the various requirements of their wireless environments highlighting the need for implementing adaptivity in mobile learning. This paper introduces a new approach for adapting content in a mobile environment. This approach suggests adapting the delivery of granules of supplementary learning content to mobile devices using Bayesian belief networks. We describe a framework for producing content granules and controlling the preferences of adaptivity over various probabilistic techniques. The result will be a tool for the deployment and evaluation of adaptivity in a distributed mobile learning environment.