@phdthesis{Betz2005,
  author    = {Betz, Christian},
  title     = {Scalable authoring of diagnostic case based training systems},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-17885},
  school      = {Universit{\"a}t W{\"u}rzburg},
  year      = {2005},
  abstract  = {Diagnostic Case Based Training Systems (D-CBT) provide learners with a means to learn and exercise knowledge in a realistic context. In medical education, D-CBT Systems present virtual patients to the learners who are asked to examine, diagnose and state therapies for these patients. Due a number of conflicting and changing requirements, e.g. time for learning, authoring effort, several systems were developed so far. These systems range from simple, easy-to-use presentation systems to highly complex knowledge based systems supporting explorative learning. This thesis presents an approach and tools to create D-CBT systems from existing sources (documents, e.g. dismissal records) using existing tools (word processors): Authors annotate and extend the documents to model the knowledge. A scalable knowledge representation is able to capture the content on multiple levels, from simple to highly structured knowledge. Thus, authoring of D-CBT systems requires less prerequisites and pre-knowledge and is faster than approaches using specialized authoring environments. Also, authors can iteratively add and structure more knowledge to adapt training cases to their learners needs. The theses also discusses the application of the same approach to other domains, especially to knowledge acquisition for the Semantic Web.},
  subject      = {Computerunterst{\"u}tztes Lernen},
  language  = {en}
}