Cognitive processing differences of experts and novices when correlating anatomy and cross-sectional imaging

Lonie R. Salkowski; Rosemary Russ

doi:10.1117/1.JMI.5.3.031411

18 May 2018 Cognitive processing differences of experts and novices when correlating anatomy and cross-sectional imaging

Lonie R. Salkowski, Rosemary Russ

Author Affiliations +

Journal of Medical Imaging, Vol. 5, Issue 3, 031411 (May 2018). https://doi.org/10.1117/1.JMI.5.3.031411

Abstract

The ability to correlate anatomical knowledge and medical imaging is crucial to radiology and as such, should be a critical component of medical education. However, we are hindered in our ability to teach this skill because we know very little about what expert practice looks like, and even less about novices’ understanding. Using a unique simulation tool, this research conducted cognitive clinical interviews with experts and novices to explore differences in how they engage in this correlation and the underlying cognitive processes involved in doing so. This research supported what has been known in the literature, that experts are significantly faster at making decisions on medical imaging than novices. It also offers insight into the spatial ability and reasoning that is involved in the correlation of anatomy to medical imaging. There are differences in the cognitive processing of experts and novices with respect to meaningful patterns, organized content knowledge, and the flexibility of retrieval. Presented are some novice–expert similarities and differences in image processing. This study investigated extremes, opening an opportunity to investigate the sequential knowledge acquisition from student to resident to expert, and where educators can help intervene in this learning process.

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Lonie R. Salkowski and Rosemary Russ "Cognitive processing differences of experts and novices when correlating anatomy and cross-sectional imaging," Journal of Medical Imaging 5(3), 031411 (18 May 2018). https://doi.org/10.1117/1.JMI.5.3.031411

Received: 13 December 2017; Accepted: 23 April 2018; Published: 18 May 2018

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