Artificial Intelligence Empowered Nursing Teaching: Application Design and Effect Evaluation

Abstract

Nursing education faces the dual challenges of rapidly increasing talent demand and uneven distribution of teaching resources. Traditional teaching models have obvious limitations in personalized training and practical skills development. Artificial intelligence technologies, including intelligent teaching systems, virtual simulation platforms, and natural language processing, provide innovative pathways for nursing education. Studies show that AI-assisted teaching can increase students’ average theoretical performance by 18%, shorten the time required to meet operational skill standards by 30%, and improve teaching efficiency by approximately 25%, thereby effectively supporting the construction of an integrated “theory–simulation–practice” teaching system. However, current technological applications still face problems such as insufficient accuracy in simulating complex clinical scenarios, incomplete data security mechanisms, and a decline in the quality of teacher–student interaction. In the future, efforts should focus on three major directions: constructing personalized learning pathways, integrating virtual simulation with augmented reality technologies, and developing data security mechanisms and explainable AI. These efforts will promote interdisciplinary collaboration and the establishment of full-chain intelligent support systems, ultimately achieving an organic integration of technology empowerment and the essence of education.