DISTRIBUTED CONTEXT AWARE DYNAMIC ADAPTATION MODEL FOR KNOWLEDGE ASSESSMENT IN E-LEARNING SYSTEM

The objective of the work is to propose a context driven dynamic adaptation model for knowledge assessment in E-Learning system through software as component. Most of the existing models deployed for Knowledge Management have focused on the contents of the assessment while giving less emphasis to the context with which the assessment services are to be rendered. A timed automaton has been proposed to accept the user requests for services navigating through the different rules resulting in a change in the behavioral states. The various states are then rewritten according to the runtime policy of application incorporating the uncertainties pertaining to the nature of services, content, time and policy changes. This context driven approach considers the nature of the application and its content along with the run time policy of different applications. An architectural framework with dynamic adaptation model has been implemented using PHP and MySQL Server and extensive testing has been carried out. Interesting inferences have been observed in terms of the session time and rewriting rules.