TY - GEN
T1 - How does Artificial Intelligence (AI) change in Nursing Education?
AU - Hsu, Mei Hua Kerry
AU - Dai, Hong Xia
AU - Liu, Ming
N1 - Publisher Copyright:
© 2025 Copyright held by the owner/author(s).
PY - 2026/3/16
Y1 - 2026/3/16
N2 - The term "artificial intelligence (AI)"was first emerged in 1956 during a workshop defined as "science and engineering of making intelligent machines, especially intelligent computer programs". The use of artificial intelligence (AI) in health education has a significant impact on clinical practice, research, and policy. The integrations of artificial intelligence (AI) technology including the natural language processing (NLP), machine learning (ML) and generative pre-trained transformers (GPT), have the potential to advance nursing education contents and processes. The aim of this study is to study and discuss the integration of AI in nursing education as the framework for identifying the opportunities and challenges associated with high-quality nursing in teaching, clinical practice, and research. AI in nursing education framework involves curriculum design, teaching and learning analysis, content and clinical scenario recommendation, chatbots and simulation, automatic assessment and marking system. Intelligent nursing tutoring system. The future of nursing education will inherently embrace AI-driven applications and technologies. "AI nursing systems"hold significant importance in the future. Ultimately, equipping future nursing educators with proficiency in AI technologies and associated ethical implications are essential for promoting high-quality nursing practice and education.
AB - The term "artificial intelligence (AI)"was first emerged in 1956 during a workshop defined as "science and engineering of making intelligent machines, especially intelligent computer programs". The use of artificial intelligence (AI) in health education has a significant impact on clinical practice, research, and policy. The integrations of artificial intelligence (AI) technology including the natural language processing (NLP), machine learning (ML) and generative pre-trained transformers (GPT), have the potential to advance nursing education contents and processes. The aim of this study is to study and discuss the integration of AI in nursing education as the framework for identifying the opportunities and challenges associated with high-quality nursing in teaching, clinical practice, and research. AI in nursing education framework involves curriculum design, teaching and learning analysis, content and clinical scenario recommendation, chatbots and simulation, automatic assessment and marking system. Intelligent nursing tutoring system. The future of nursing education will inherently embrace AI-driven applications and technologies. "AI nursing systems"hold significant importance in the future. Ultimately, equipping future nursing educators with proficiency in AI technologies and associated ethical implications are essential for promoting high-quality nursing practice and education.
KW - Aged simulation
KW - Artificial Intelligence
KW - Gerontological Nursing (GN)
KW - Nursing Education
KW - Virtual reality (VR)
UR - https://www.scopus.com/pages/publications/105036688884
U2 - 10.1145/3761843.3761866
DO - 10.1145/3761843.3761866
M3 - Conference contribution
AN - SCOPUS:105036688884
T3 - ICEMT 2025 - 2025 9th International Conference on Education and Multimedia Technology
SP - 277
EP - 281
BT - ICEMT 2025 - 2025 9th International Conference on Education and Multimedia Technology
PB - Association for Computing Machinery, Inc
T2 - 9th International Conference on Education and Multimedia Technology, ICEMT 2025
Y2 - 29 July 2025 through 1 August 2025
ER -