Novice and Expert Differences and Educational Interventions to Improve Veterinary Pathology Visual Diagnostic Reasoning Measured by Eye-tracking Technology

Date
2013-12-13
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Abstract
Purpose: There were two objectives, to 1) to use eye-tracking to establish baseline quantitative and qualitative differences between novice and expert veterinary pathologists and explore dual process theory of clinical reasoning, and 2) determine if the introduction of two educational interventions, the active use of key diagnostic features and image repetition, improved novice visual diagnostic reasoning skills. Method: A pre-experimental static group comparison between novice and expert veterinary pathologists was used. Participants were shown 10 veterinary cytology images and asked to formulate a diagnosis while wearing eye-tracking equipment (10 slides) and while concurrently thinking aloud (5 slides). A quasi-experimental, pre-test and post-test comparison group design was used to compare the two teaching interventions to a comparison group using eye-tracking as an assessment method. The time to diagnosis and percentage time spent viewing an area of diagnostic interest (AOI) were compared using independent t-tests (novice and expert) and paired t-tests (time) and analysis of covariance (ANCOVA) (between groups) was used for the educational interventions. Diagnostic accuracy as a dichotomous variable was compared using chi-square tables. Results: Compared to novice, experts demonstrated significantly higher diagnostic accuracy (p < 0.017), shorter time to diagnosis (p < 0.017) and a higher percentage of time spent viewing AOIs (p < 0.017). Experts elicited more key-diagnostic features in the think-aloud protocol and had more efficient patterns of eye-movement. Students in the extended visual reasoning teaching intervention: active learning, image repetition behaved most like experts with no significant difference to experts for diagnostic accuracy, percentage time spent in the AOIs and a significantly faster time to diagnosis than experts (p < 0.017). Discussion: I suggest that experts’ fast time to diagnosis, efficient eye-movement patterns, and preference for viewing AOIs supports system 1 (pattern-recognition) reasoning and script-inductive knowledge structures with system 2 (analytic) reasoning to verify their diagnosis. Our results from the educational interventions suggest a greater level of improvement in the eye-tracking of students that were taught key-diagnostic features in an active learning forum and were shown multiple case examples.
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Keywords
Education--Vocational
Citation
Warren, A. L. (2013). Novice and Expert Differences and Educational Interventions to Improve Veterinary Pathology Visual Diagnostic Reasoning Measured by Eye-tracking Technology (Doctoral thesis, University of Calgary, Calgary, Canada). Retrieved from https://prism.ucalgary.ca. doi:10.11575/PRISM/27137