The association between quality of connections and diagnostic accuracy in student-generated concept maps for clinical reasoning education with virtual patients.

Objectives: Concept maps are a learning tool that fosters clinical reasoning skills in healthcare education. They can be developed by students in combination with virtual patients to create a visual representation of the clinical reasoning process while solving a case. However, in order to optimize feedback, there is a need to better understand the role of connections between concepts in student-generated maps. Therefore, in this study we investigated whether the quality of these connections is indicative of diagnostic accuracy. Methods: We analyzed 40 concept maps created by fifth-year medical students in the context of four virtual patients with commonly encountered diagnoses. Half of the maps were created by students who made a correct diagnosis on the first attempt; the other half were created by students who made an error in their first diagnosis. The connections in the maps were rated by two reviewers using a relational scoring system. Analysis of covariance was employed to examine the difference in mean connection scores among groups while controlling for the number of connections. Results: There were no differences between the groups in the number of concepts or connections in the maps; however, maps made by students who made a correct first diagnosis had higher scores for the quality of connections than those created by students who made an incorrect first diagnosis (12.13 vs 9.09; p=0.03). We also observed students' general reluctance to use connections in their concept maps. Conclusion: Our results suggest that the quality, not the quantity, of connections in concept maps is indicative of their diagnostic accuracy.