Neurocognition of Teaching and Learning Clinical Reasoning in Veterinary Pathology Using Eye‐tracking and Electroencephalography

Examining clinical reasoning skill acquisition in health professions education is key to optimize the teaching of this skill. Insights from neural (electroencephalography) and biometric (eye‐tracking) data could provide novel proximal measures that generate quantitative empirical evidence representing a learner’s (and expert’s) cognitive processing. Visual diagnostic reasoning in particular relies on data acquired from visual images to recognize anatomic pathologies. Eye‐tracking research has shown distinct differences in expert versus novice eye tracking patterns in visual diagnostic reasoning, where novices are expected to have more disorganized eye‐movement patterns resulting in longer times to reach diagnosis and less time is spent focusing on important areas of interest. Employing eye‐tracking in conjunction with neural and behavioural measures could yield more complete evidence for analysis to understand nuances in progression of learning. Aim The aim of this work is to determine whether learners acquire the same neural signatures as expert pathologists and whether learners are attending to the clinically significant features of an image. Methods Novice learners (n = 27) were taught to accurately visually diagnose twelve distinct bovine liver pathologies through a trial and error process where feedback was provided using a computerized module. This learning module consisted of 288 fast paced (5 seconds each), self‐advancing, interactive questions. Expert veterinary anatomic pathologists (n = 8) also completed this module. Behavioural performance (accuracy, response time), EEG, and eye‐tracking data were collected for each participant as they progressed through the module. This study has been approved by the University of Calgary Conjoint Faculties Research Ethics Board (REB16‐0925). Results All data has been collected and is presently under analysis. Discussion and Conclusion Based on the results of this work we can determine whether training module is appropriately stimulating learner attention to clinically appropriate visual cues and whether similar neural signatures in competent learners (as defined by behavioural accuracy) compared to experts are observed. The findings of this work will also contribute to generating a neurobiometric profile of expertise and expertise development. By defining a profile, we can better assess how teaching strategies support or hinder the transition of learners along the novice to expert continuum. While advances in the development of tools to measure neurophysiological data continue to make neuroeducational research more accessible and practical in an educational setting, the challenge will be to meaningfully design and communicate research in a way that is applicable to educationalists. Support or Funding Information University of Calgary Veterinary Education Research Fund