Abstrakt
Diagnostics-related errors made by medical students represent a considerable issue for the field, as they very often have negative consequences that reduce learning effectiveness. This study proposes a means of ameliorating problems with diagnostic reasoning and improving the learning process.
The description of a virtual case, containing necessary information, is used within a knowledge-based system for evaluation of medical students' diagnostic abilities. This system is grounded in a branch-oriented model, where every decision reveals part of the information about the patient in each iteration, depending on the diagnostician's choice, which supports evaluation of the flow of students' thoughts.
By fostering the acquisition of "negative knowledge" about typical cognitive errors in the medical reasoning process, the system helps eliminate learners' errors specific to any type of situation that the system might be set up to address in any given case. Descriptions of teachers' inputs, the process model, the evaluation procedure for student's performance, and a method for configuring virtual patient cases are provided.
Apart from the accuracy of the diagnosis, other aspects such as patients' comfort and the cost of the diagnosis are also taken into consideration when evaluating students' diagnostic process.