Surgical education reimagined: the convergence of learning theories and artificial intelligence

Abstract

PURPOSE: The integration of artificial intelligence (AI) into surgical education is transforming the way surgical skills and knowledge are developed. This article examines how AI aligns with key educational theories-behaviourism, cognitivism, constructivism, humanism, and connectivism-to enhance learning through personalised simulations, adaptive feedback, and networked platforms. MATERIALS AND METHODS: A review of literature and theoretical frameworks was conducted to analyse AI's applications in surgical training. Key features include AI-driven tools for structured feedback, cognitive optimisation, experiential learning, individual growth, and collaboration through interconnected networks. The article also identifies ethical challenges, including data privacy, algorithmic bias, and equitable access. RESULTS: AI has the potential to revolutionise surgical education by fostering critical thinking, improving training outcomes, and expanding access to learning resources. However, risks such as over-reliance on automation, loss of hands-on experience, and superficial AI use ("AI theatre") highlight the need for thoughtful and ethical implementation. CONCLUSION: With a balanced and collaborative approach among educators, technologists, and healthcare professionals, AI can create dynamic, learner-centred environments. By addressing challenges, AI can support the development of skilled, compassionate surgeons equipped to navigate the complexities of modern medical practice.

Ähnliche Arbeiten