Utilizing GPT 4.0 with prompt learning in nursing education: a case study approach based on Benner's theory

Abstract

Background: Artificial intelligence (AI) and large language models, such as ChatGPT, have the potential to enhance nursing education by serving as a virtual mentor who can provide real-time guidance and resources. However, integrating AI chatbots into nursing necessitates a detailed understanding of how to align these technologies with established nursing theories. Aim: To develop guidelines on how to employ GPT 4.0 using the prompt learning method. Methods: In the method of prompt learning, users give specific prompts, and the AI model reacts according to its training, specifically aligned with the progression of knowledge and skills in nursing education as outlined by Benner's theory. This study used a case study methodology. Results: The customization of a conversational AI chatbot is shown to support the development of nursing knowledge and skills. This paper outlines how to integrate Benner's theory with ChatGPT's capabilities, addresses bias issues, and establishes best practices for the safe and effective use of AI in nursing. Conclusion: The findings have important implications for the advancement of nursing education and the safe and responsible use of AI tools in clinical environments.