Scalable Authoring of Diagnostic Case Based Training Systems

Diagnostic Case Based Training Systems (D-CBT) enable learners to learn and practice in a realistic context: In medical education, D-CBT present virtual patients to the learners who are asked to diagnose these patients. D-CBT range from simple, easy-to-author and easy-to-use presentation systems to complex knowledge based systems. This book presents an approach for authors to easily create D-CBT from existing documents using well-known tools: Authors simply annotate and extend the documents to model the knowledge. These annotated documents are automatically transformed into training cases. A scalable knowledge representation is able to capture the content on multiple levels, from simple to highly structured knowledge. This technique of authoring allows easy start and fast development of training cases. Also, authors can iteratively add and structure knowledge to adapt training cases to their learners' needs. The presented system grows in influence: University of Wuerzburg uses it as eLearning platform for all students. The book also discusses the application of the same approach to other domains, especially to knowledge acquisition for the Semantic Web.