Using Expert Decision Maps to Promote Reflection and Self-Assessment in Medical Case-Based Instruction

We describe a pilot study that explores whether or not medical students can understand visual representations of expert thinking. This research builds upon our previous work in developing a methodology to support knowledge elicitation and knowledge validation in the ill-defined domain of medical case-based instruction [1]. Second-year medical students were assigned to one of two feedback conditions. They solved patient cases in BioWorld, a computer-based learning environment. We examined their selfassessed performance and computer logs over three cases to determine whether the feedback condition has any effect on their ability to discern differences between their own diagnostic reasoning patterns and those of experts. The results from this study will be used to guide the development of cognitive tools to support the provision of dynamic formative feedback in BioWorld. By tapping into the students’ current understanding of expert thinking, we can design appropriate scaffolding and feedback mechanisms to support the students’ developing expertise.