Abstract
Medical students’ metacognitive and self-regulatory behaviors are examined as they diagnose patient cases using BioWorld, a technology rich learning environment. BioWorld offers an authentic problem-based environment where students solve clinical cases and receive expert feedback. We evaluate the effectiveness of key features in BioWorld (the evidence table and visualization maps) to see whether they promote metacognitive monitoring and evaluation. Learning outcomes were assessed through novice/expert comparisons in relation to diagnostic accuracy, confidence, and case summaries. More specifically we examined how diagnostic processes and learning outcomes were refined or improved through practice at solving a series of patient cases. The results suggest that, with practice, medical students became more expert-like in the processes involved in making crucial clinical decisions. The implications of these findings for the design of features embedded within BioWorld that foster key metacognitive and self-regulatory processes are discussed.
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Lajoie, S.P. et al. (2013). Technology-Rich Tools to Support Self-Regulated Learning and Performance in Medicine. In: Azevedo, R., Aleven, V. (eds) International Handbook of Metacognition and Learning Technologies. Springer International Handbooks of Education, vol 28. Springer, New York, NY. https://doi.org/10.1007/978-1-4419-5546-3_16
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