ArticleCureus2026
Integration of Artificial Intelligence Into a Medical Curriculum: Evolving Student Perceptions and Faculty Development Challenges.
Article in Cureus, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Authors and funding
5 authors.
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Abstract
BACKGROUND AND
methodsThe rapid integration of generative artificial intelligence (AI) into medical education presents both opportunities and continuing challenges for faculty and learners alike. This study provides an update on ongoing efforts to integrate AI into the curriculum at Quillen College of Medicine, East Tennessee State University in the United States, focusing on evolving student perceptions and a structured faculty development initiative. Using our previously published satisfaction instrument, we tracked shifting attitudes toward AI among our pre-clerkship and clerkship students.
resultsIncoming students demonstrated increasing awareness of AI's impact on education and the profession, alongside a stronger commitment to developing core clinical competencies independent of technology. The response rate for AI use was higher in 2026 compared to 2025 (97%, n=68 vs. 89%, n=62) for rising third-year students (class sizes of 80). Those students showed a meaningful shift toward using AI for active learning, particularly practice question generation and self-testing (Mean 2.30, SD 1.10 for 2025; Mean 2.77, SD 1.14 for 2026), while upper-level clerkship students consistently prioritized the ability to function as competent clinicians without AI assistance. To address faculty readiness, we developed a multi-dimensional framework for responsible AI integration and implemented a series of faculty development workshops. The first workshop produced an increase in confidence (+0.75) and practical engagement (+0.43). A second workshop focused on ethical and policy considerations yielded greater critical awareness, though with a more cautious outlook. Feedback across both workshops consistently highlighted the need for hands-on training, prompt engineering instruction, and role-specific, tool-agnostic development pathways.
conclusionsOur findings underscore that integration of AI into medical education requires sustained, flexible, and mission-aligned faculty development. As AI becomes standard in clinical practice, equipping both educators and learners with the skills for responsible, thoughtful AI use is not optional; it is essential.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.