Effect of Generative Artificial Intelligence Use on Diagnostic Learning in Medical Students: A Quasi-Experimental Study

Abstract

Generative artificial intelligence (GenAI) has emerged as a transformative tool in medical education, particularly in the development of diagnostic learning and clinical reasoning skills. This study aimed to examine the effect of GenAI use on diagnostic learning among medical students through a quasi-experimental pretest–posttest design. A total of 62 students participated, assigned to an experimental group that used GenAI to solve clinical cases and a control group that relied on traditional study methods. Findings showed a markedly greater improvement in the experimental group, which achieved higher gains in diagnostic accuracy, quality of reasoning and reduced case-resolution time. Students' perceptions were highly positive, emphasising the usefulness, clarity and cognitive support offered by GenAI. Although moderate risks of error were identified, they did not significantly affect the overall evaluation of the tool. The study concludes that generative AI significantly enhances diagnostic learning and strengthens essential clinical competencies, provided its implementation occurs within an appropriate ethical and pedagogical framework. These results open new avenues for research regarding curriculum integration, impact on more complex clinical scenarios and its potential as an intelligent tutoring resource in contemporary medical education.

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