Integration of Artificial Intelligence in Nursing Simulation Education: A Scoping Review

Area of Science:

• Nursing Education
• Artificial Intelligence
• Simulation Technology

Background:

• The integration of artificial intelligence (AI) in nursing simulation education is expanding.
• Understanding AI's role across different simulation phases is currently limited.

Purpose of the Study:

• To systematically map the applications of artificial intelligence (AI) within the prebriefing, simulation, and debriefing stages of nursing education.
• To provide a comprehensive overview of AI's current implementation in nursing simulation.

Main Methods:

• A scoping review was conducted following established guidelines (Arksey and O'Malley, PRISMA-ScR).
• Searches were performed in major databases (PubMed, CINAHL, EMBASE, Scopus, Web of Science) from 2015-2024.
• Included studies focused on prelicensure nursing students, AI in simulation, and were peer-reviewed English publications.

Main Results:

• Analysis of 14 studies identified AI applications in prebriefing (chatbots, n=2), simulation (virtual environments, n=11), and debriefing (feedback, n=1).
• Key benefits include standardized educational content and personalized learning experiences for nursing students.
• Identified challenges encompass technical limitations and the need for faculty preparedness in utilizing AI tools.

Conclusions:

• Artificial intelligence demonstrates significant potential to improve nursing simulation education.
• Standardized learning experiences can be achieved through AI integration.
• Structured faculty support and robust evaluation methodologies are crucial for effective AI implementation in nursing simulation.