Challenges for future directions for artificial intelligence integrated nursing simulation education
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Artificial intelligence (AI) has tremendous potential to change the way we train future health professionals. Although AI can provide improved realism, engagement, and personalization in nursing simulations, it is also important to address any issues associated with the technology, teaching methods, and ethical considerations of AI. In nursing simulation education, AI does not replace the valuable role of nurse educators but can enhance the educational effectiveness of simulation by promoting interdisciplinary collaboration, faculty development, and learner self-direction. We should continue to explore, innovate, and adapt our teaching methods to provide nursing students with the best possible education.
Abstract
Artificial intelligence (AI) has tremendous potential to change the way we train future health professionals. Although AI can provide improved realism, engagement, and personalization in nursing simulations, it is also important to address any issues associated with the technology, teaching methods, and ethical considerations of AI. In nursing simulation education, AI does not replace the valuable role of nurse educators but can enhance the educational effectiveness of simulation by promoting interdisciplinary collaboration, faculty development, and learner self-direction. We should continue to explore, innovate, and adapt our teaching methods to provide nursing students with the best possible education.
참고문헌 (16)
- Ouyang F, "Artificial intelligence in online higher education : A systematic review of empirical research from 2011 to 2020", Educ Inf Technol, 27(1), pp.7893~7925 (2022)[DOI]
- Bohr A, "Artificial intelligence in healthcare", pp.25~60 (2020), Academic Press
- Kardong-Edgren S, "Evaluating the usability of a second-generation virtual reality game for refreshing sterile urinary catheterization skills", Nurse Educ, 44(3), pp.137~141 (2019)[DOI]
- De Gagne JC, "The state of artificial intelligence in nursing education : past, present, and future directions", Int J Environ Res Public Health, 20(6), pp.4884~ (2023)[DOI]
- Foronda CL, "Virtual simulation in nursing education : a systematic review spanning 1996 to 2018", Simul Healthc, 15(1), pp.46~54 (2020)[DOI]
- Abuazizeh M, "Computational state space model for intelligent tutoring of students in nursing subjects", Conference paper of PETRA ’20: The 13th PErvasive Technologies Related to Assistive Environments Conference (2020), Association for Computing Machinery
- Andersen BL, "Blending adaptive learning technology into nursing education : a scoping review", Contemp Educ Technol, 14(1), pp.ep333~ (2021)[DOI]
- "AI in simulation-Clinical intelligence at NCLEX standards" (2023)[URL]
- Liaw SY, "Artificial intelligence in virtual reality simulation for interprofessional communication training : mixed method study", Nurse Educ Today, 122, pp.105718~ (2023)[DOI]
- Seibert K, "Application scenarios for artificial intelligence in nursing care : rapid review", J Med Internet Res, 23(11), pp.e26522~ (2021)[DOI]
- Watts PI, "Onward and upward : Introducing the Healthcare Simulation Standards of Best PracticeTM", Clin Simul Nurs, 58, pp.1~4 (2021)[DOI]
- Watts PI, "Healthcare Simulation Standards of Best PracticeTM simulation design", Clin Simul Nurs, 58, pp.14~21 (2021)[DOI]
- McMahon E, "Healthcare Simulation Standards of Best PracticeTM evaluation of learning and performance", Clin Simul Nurs, 58, pp.54~56 (2021)[DOI]
- Decker S, "Healthcare Simulation Standards of Best PracticeTM the debriefing process", Clin Simul Nurs, 58, pp.27~32 (2021)[DOI]
- Bowler F, "Healthcare Simulation Standards of Best PracticeTM professional integrity", Clin Simul Nurs, 58, pp.45~48 (2021)[DOI]
- Lee SH, "CHAT GPT generation", pp.276~321 (2023), Book Moment