Abstract
Although cognitive errors (i.e., premature closure, faulty data gathering, and faulty knowledge) are the main reasons for making diagnostic mistakes, the mechanisms by which they occur are difficult to isolate in clinical settings. Computer-based learning environments (CBLE) offer the opportunity to train medical students to avoid cognitive errors by tracking the onset of these errors. The purpose of this study is to explore cognitive errors in a CBLE called BioWorld. A logistic regression was fitted to learner behaviors that characterize premature closure in order to predict diagnostic performance. An ANOVA was used to assess if participants who were highly confident in their wrong diagnosis engaged in more faulty data gathering via confirmation bias. Findings suggest that diagnostic mistakes can be predicted from faulty knowledge and faulty data gathering and indicate poor metacognitive awareness. This study supports the notion that to improve diagnostic performance medical education programs should promote metacognitive skills.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Elstein, A.S., Schwartz, A.: Clinical reasoning in medicine. In: Clinical Reasoning in the Health Professions, pp. 49–59. Butterworth-Heinemann, Woburn (1995)
Bartlett, E.E.: Physicians’ cognitive errors and their liability consequences. Journal of Healthcare Risk Management 18(4), 62–69 (1998)
Graber, M.L., Franklin, N., Gordon, R.: Diagnostic error in internal medicine. Archives of Internal Medicine 165(13), 1493–1499 (2005)
Norman, G.R., Eva, K.W.: Diagnostic error and clinical reasoning. Medical Education 44(1), 94–100 (2010)
Podbregar, M., Voga, G., Krivec, B., Skale, R., Parežnik, R., Gabršček, L.: Should we confirm our clinical diagnostic certainty by autopsies? Intensive Care Medicine 27(11), 1750–1755 (2001)
Lajoie, S.: Developing professional expertise with a cognitive apprenticeship mode. In: Development of professional expertise, Cambridge, UK, pp. 61–83 (2009)
Berner, E.S., Graber, M.L.: Overconfidence as a cause of diagnostic error inmedicine. The American Journal of Medicine 121(5), S2–S23 (2008)
Azevedo, R., Feyzi-Behnagh, R.: Dysregulated learning with advanced learning technologies. In: AAAI Fall Symposium: Cognitive and Metacognitive Educational Systems
Croskerry, P.: The importance of cognitive errors in diagnosis and strategies to minimize them. Academic Medicine 78(8), 775–780 (2003)
Lajoie, S.P., Poitras, E.G., Doleck, T., Jarrell, A.: Modeling metacognitive activities in medical problem-solving with BioWorld. In: Metacognition: Fundaments, Applications, and Trends, pp. 323–343. Springer International Publishing (2015)
Lajoie, S., Naismith, L., Poitras, E., Hong, Y., Panesso-Cruz, I., Ranelluci, J., Wiseman, J.: 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, Amsterdam (2013)
Naismith, L.: Examining motivational and emotional influences on medical students’ attention to feedback in a technology-rich environment for learning clinical reasoning (Unpublished doctoral dissertation). McGill University, Canada (2013)
Midgley, C., Maehr, M.L., Hruda, L.Z., Anderman, E., Anderman, L., Freeman, K.E. et al.: Manual for the Patterns of Adaptive Learning Scales. University of Michigan (2000)
Pekrun, R., Goetz, T., Frenzel, A.C., Barchfeld, P., Perry, R.P.: Measuring emotions in students’ learning and performance: The Achievement Emotions Questionnaire (AEQ). Contemporary Educational Psychology 36, 36–48 (2011)
Gauthier, G., Lajoie, P.S., Naismith, L., Wiseman, J.: Using expert decision maps to promote reflection and self-assessment in medical case-based instruction. In: Proceedings of Workshop on the Assessment and Feedback in Ill-Defined Domains at ITS, Montréal, Canada (2008)
Howell, D.: 8th Edition of statistical methods for psychology. Wadsworth, Belmont (2013)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2015 Springer International Publishing Switzerland
About this paper
Cite this paper
Jarrell, A., Doleck, T., Poitras, E., Lajoie, S., Tressel, T. (2015). Learning to Diagnose a Virtual Patient: an Investigation of Cognitive Errors in Medical Problem Solving. In: Conati, C., Heffernan, N., Mitrovic, A., Verdejo, M. (eds) Artificial Intelligence in Education. AIED 2015. Lecture Notes in Computer Science(), vol 9112. Springer, Cham. https://doi.org/10.1007/978-3-319-19773-9_18
Download citation
DOI: https://doi.org/10.1007/978-3-319-19773-9_18
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-19772-2
Online ISBN: 978-3-319-19773-9
eBook Packages: Computer ScienceComputer Science (R0)