Effect of a flipped classroom course to foster medical students’ AI literacy with a focus on medical imaging: a single group pre-and post-test study

Abstract

BACKGROUND: The use of artificial intelligence applications in medicine is becoming increasingly common. At the same time, however, there are few initiatives to teach this important and timely topic to medical students. One reason for this is the predetermined medical curriculum, which leaves very little room for new topics that were not included before. We present a flipped classroom course designed to give undergraduate medical students an elaborated first impression of AI and to increase their "AI readiness". METHODS: The course was tested and evaluated at Bonn Medical School in Germany with medical students in semester three or higher and consisted of a mixture of online self-study units and online classroom lessons. While the online content provided the theoretical underpinnings and demonstrated different perspectives on AI in medical imaging, the classroom sessions offered deeper insight into how "human" diagnostic decision-making differs from AI diagnoses. This was achieved through interactive exercises in which students first diagnosed medical image data themselves and then compared their results with the AI diagnoses. We adapted the "Medical Artificial Intelligence Scale for Medical Students" to evaluate differences in "AI readiness" before and after taking part in the course. These differences were measured by calculating the so called "comparative self-assessment gain" (CSA gain) which enables a valid and reliable representation of changes in behaviour, attitudes, or knowledge. RESULTS: We found a statistically significant increase in perceived AI readiness. While values of CSA gain were different across items and factors, the overall CSA gain regarding AI readiness was satisfactory. CONCLUSION: Attending a course developed to increase knowledge about AI in medical imaging can increase self-perceived AI readiness in medical students.

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