The rapid advancement of information technology has accelerated the integration of Generative Artificial Intelligence (Generative AI) across various domains, particularly in smart healthcare and education. This study investigates the efficacy of Generative AI as a pedagogical tool in teaching the Internet of Things (IoT), a foundational technology within smart healthcare. Drawing upon Vygotsky’s Zone of Proximal Development (ZPD) theory, scaffolding learning theory, and relevant instructional strategies, this research aims to bridge students’ pre-existing knowledge gaps and evaluate the influence of AI-supported learning on their academic outcomes and perceptions. Employing an experimental research design, the study involved 60 medical university students who were randomly assigned to either an experimental group, utilizing “Generative AI,” or a control group, employing traditional “web browser” methods. Post-intervention analyses revealed significant improvements in academic performance for both groups. Notably, the experimental group exhibited significantly higher learning outcomes and more positive perceptions regarding AI-driven scaffolding than the control group. This study emphasizes the potential of integrating established learning theories with AI-based scaffolding to effectively address knowledge deficiencies, foster autonomous learning, and enhance educational outcomes. The findings suggest that Generative AI represents a powerful resource for developing healthcare information professionals equipped with essential AI competencies.