Dynamic assessment and customizable e-learning content generator

This paper proposes a framework to create customizable on - demand educational contents with automated assessment. This framework can sequence educational contents logically based on content dependency, both implicit dependency in domain ontology and/or explicit dependency in external specifications. Based on the dependency information, the framework can propose several alternative and ranked learning paths so that educators or learners can make intelligent decisions. A metric called "Learning Path Relevance" can be used to evaluate alternative learning paths. The framework also has a formal model to generate questions automatically from domain ontology for assessment. Using the proposed framework, it is possible to customize various learning modules for individuals with different backgrounds with automated assessment.