Decision Analysis Methods in OpenLabyrinth

Evaluation of decisions made when learners are navigating an OpenLabyrinth virtual patient case presents some challenges because of possible complex, branching nature of such cases. The complexity presents great richness in describing and tracking realistic decision opportunities but necessitates different approaches in assessing whether the learner made good choices. This paper explores some aspects of graph theory and path analysis, and presents some perspectives on calculating the probabilities that the pathway chosen was a good one. Standard setting approaches may be required to provide a benchmark against which to measure.