The training of healthcare professionals has traditionally been based on substantial direct student–patient contact. Effective practitioners need to be able to apply reasoning skills gained from exposure to a variety of cases in order to develop diagnostic and therapeutic accuracy.
Virtual patients can provide students with a reliable, safe and replicable environment to practice diagnostic skills and develop clinical reasoning. In particular, virtual patients have demonstrated their use in healthcare teaching, learning and assessment and throughout a wide range of designs for learning.
While virtual patients are a useful component of healthcare education, they are seldom affordable. The range of virtual patients being produced is limited, with many essentially automated versions of problem-based learning (PBL) cases. These cases only proceed in a single direction, which prevents users from tracking down ‘wrong paths’ by immediate correction. This inflexibility limits the development of clinical reasoning, and is both unrealistic and unengaging. In real life there are often several ways to tackle a problem, but such multiple route scenarios can be very time consuming to model.
This presentation will demonstrate how UNBC is employing open source platform OpenLabyrinth https://github.com/olab/Open-Labyrinth/wiki to build online virtual patients. The development methods employ visual thinking and concept mapping techniques that are accessible, yet flexible enough to simulate real clinical decisions through non-linear pathways.
Of Interest to: Online and distance education, Post-secondary education, K-12 educators, Instructional designers, Educational technologists
