Students' Perceptions of the Integration of Artificial Intelligence Nursing Education: A Study at a Private Chilean University
Palabras clave:
Artificial intelligence, Nursing education, Faculty training, Student perception, Higher educationResumen
The use of artificial intelligence (AI) in higher education has gained significant attention, particularly in health-related fields. This study explores the perceptions of AI use among nursing students at a private Chilean university. The research aimed to assess students' attitudes and experiences with AI in their learning process. A sample of 36 nursing students participated, and data were collected using a Likert-scale questionnaire measuring various dimensions of AI integration. Results indicated moderate perceptions of AI use, with an average score of M = 3.15. While students recognized the potential of AI to enhance learning efficiency and access to information, concerns were raised regarding the limited practical implementation and insufficient training opportunities. The findings suggest that to fully leverage AI in nursing education, improvements such as targeted training programs and expanded technological resources are essential. Future efforts should focus on fostering AI literacy to better prepare nursing students for technologically advanced healthcare environments.
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Alazzam, M. B., Tayyib, N., Alshawwa, S. Z. & Ahmed, M. K. (2022). Nursing care systematization with case‐based reasoning and artificial intelligence. Journal of Healthcare Engineering, 1–9. 10.1155/2022/1959371. https://doi.org/10.1155/2022/1959371
Alowais, S.A., Alghamdi, S.S., Alsuhebany, N. et al. Revolutionizing healthcare: the role of artificial intelligence in clinical practice. BMC Med Educ 23, 689 (2023). https://doi.org/10.1186/s12909-023-04698-z
Bahroun, Z., Anane, C., Ahmed, V. & Zacca, A. (2023). Transforming Education: A Comprehensive Review of Generative Artificial Intelligence in Educational Settings through Bibliometric and Content Analysis. Sustainability, 15, Article 12983. https://doi.org/10.3390/su151712983
Bajwa, J., Munir, U., Nori, A. & Williams, B. (2021). Artificial intelligence in healthcare: transforming the practice of medicine. Future Healthc J 8(2):e188-e194. doi: 10.7861/fhj.2021-0095. PMID: 34286183; PMCID: PMC8285156. https://pmc.ncbi.nlm.nih.gov/articles/PMC8285156/
Buchanan, C., Howitt, M. L., Wilson, R., Booth, R. G., Risling, T. & Bamford, M. (2020a). Nursing in the age of artificial intelligence: Protocol for a scoping review. JMIR Research Protocols, 9(4), e17490. 10.2196/17490. https://doi.org/10.2196/17490
Cheung, S. K. S., Kwok, L. F., Phusavat, K. & Yang, H. H. (2021). Shaping the Future Learning Environments with Smart Elements: Challenges and Opportunities. International Journal of Educational Technology in Higher Education, 18, 1-9. https://doi.org/10.1186/s41239-021-00254-1
Clancy, T. R. (2020). Artificial intelligence and nursing: The future is now. The Journal of Nursing Administration, 50(3), 125–127. 10.1097/NNA.0000000000000855. https://journals.lww.com/jonajournal/abstract/2020/03000/artificial_intelligence_and_nursing__the_future_is.4.aspx
Glauberman G, Ito-Fujita A, Katz S, Callahan J. Artificial Intelligence in Nursing Education: Opportunities and Challenges. Hawaii J Health Soc Welf. 2023 Dec;82(12):302-305. PMID: 38093763; PMCID: PMC10713739. https://pmc.ncbi.nlm.nih.gov/articles/PMC10713739/
Green, J., Camilli, G.& Elmore, P. (2006). Complementary methods in education research. New York: Routledge.
Kollerup, K., N., Johansen, S. S., Tolsgaard, M. G., Lønborg Friis, M., Skov, M. B., & van Berkel, N. (2024). Clinical needs and preferences for AI-based explanations in clinical simulation training. Behaviour & Information Technology, 1–21. https://doi.org/10.1080/0144929X.2024.2334852
Maleki Varnosfaderani, S., & Forouzanfar, M. (2024). The Role of AI in Hospitals and Clinics: Transforming Healthcare in the 21st Century. Bioengineering, 11(4), 337. https://doi.org/10.3390/bioengineering11040337
Mhlanga, D. (2021). Artificial Intelligence in the Industry 4.0, and Its Impact on Poverty, Innovation, Infrastructure Development, and the Sustainable Development Goals: Lessons from Emerging Economies? Sustainability, 13, Article 5788. https://doi.org/10.3390/su13115788
Rana, J., Gutierrez, P.L., Oldroyd, J.C. (2021). Quantitative Methods. In: Farazmand, A. (eds) Global Encyclopedia of Public Administration, Public Policy, and Governance. Springer, Cham. https://doi.org/10.1007/978-3-319-31816-5_460-1
Stokes, F., & Palmer, A. (2020). Artificial intelligence and robotics in nursing: Ethics of caring as a guide to dividing tasks between AI and humans. Nursing Philosophy, 21(4), e12306. 10.1111/nup.12306. https://www.mdpi.com/2076-3417/13/8/5212
Van Bulck, L., Couturier, R. & Moons, P. (2023). Applications of artificial intelligence for nursing: Has a new era arrived? European Journal of Cardiovascular Nursing, 22(3), e19–e20. 10.1093/eurjcn/zvac097. https://doi.org/10.1093/jamia/ocz130
Vera, F. (2023). Integration of Artificial Intelligence Technology in Higher Education: Exploring Faculty Members’ Experience. Transformar, 4(3), 17–22. https://revistatransformar.cl/index.php/transformar/article/view/99
Vera, F. (2024). Student Performance in Writing Prompts for Text-based GenAI tools in a Research Methodology Course. Transformar, 5(2), 71–90. https://revistatransformar.cl/index.php/transformar/article/view/129