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Shan Li; Xiaoshan Huang; Tingting Wang; Juan Zheng; Susanne P. Lajoie – Journal of Computing in Higher Education, 2025
Coding think-aloud transcripts is time-consuming and labor-intensive. In this study, we examined the feasibility of predicting students' reasoning activities based on their think-aloud transcripts by leveraging the affordances of text mining and machine learning techniques. We collected the think-aloud data of 34 medical students as they diagnosed…
Descriptors: Information Retrieval, Artificial Intelligence, Prediction, Abstract Reasoning
McBee, Elexis; Ratcliffe, Temple; Picho, Katherine; Artino, Anthony R., Jr.; Schuwirth, Lambert; Kelly, William; Masel, Jennifer; van der Vleuten, Cees; Durning, Steven J. – Advances in Health Sciences Education, 2015
Context specificity and the impact that contextual factors have on the complex process of clinical reasoning is poorly understood. Using situated cognition as the theoretical framework, our aim was to evaluate the verbalized clinical reasoning processes of resident physicians in order to describe what impact the presence of contextual factors have…
Descriptors: Context Effect, Clinical Diagnosis, Abstract Reasoning, Physicians

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