Objective To explore the applicability of generative artificial intelligence (AI) in nursing postgraduate education, its dual impact on academic competence and clinical decision-making, and to reveal its ethical risks and technological bottlenecks, thereby providing a foundation for constructing a safe and efficient human-machine collaborative educational model.
Methods: Based on grounded theory, purposive sampling was employed to select 25 nursing postgraduate students from three medical universities for semi-structured interviews. Three-level coding analysis (open coding extracted 34 initial concepts, axial coding integrated them into 3 core categories) was conducted using NVivo12 software, establishing a triadic dynamic model of "AI Empowerment—Interaction Tension—Boundary Constraints."