Nursing Educators' Perspectives on the Integration of Artificial Intelligence Into Academic Settings

被引:2
作者
Rony, Moustaq Karim Khan [1 ]
Ahmad, Sumon [2 ]
Tanha, Sabren Mukta [2 ]
Das, Dipak Chandra [3 ]
Akter, Mosammat Ruma [4 ]
Khatun, Mst. Amena [5 ]
Begum, Most. Hasina [4 ]
Khalil, Md Ibrahim [6 ]
Peu, Umme Rabeya [7 ]
Parvin, Mst. Rina [8 ]
Alrazeeni, Daifallah M. [9 ]
Akter, Fazila [10 ]
机构
[1] Int Univ Business Agr & Technol, Miyan Res Inst, Dhaka, Bangladesh
[2] Leading Univ, Dept Publ Hlth, Sylhet, Bangladesh
[3] Shanto Mariam Univ Creat Technol, Dept Social Sci Sociol & Anthropol, Dhaka, Bangladesh
[4] Natl Inst Adv Nursing Educ & Res Mugda, Dept Sci Nursing, Dhaka, Bangladesh
[5] TMSS Nursing Coll, Coll Nursing, Bogura, Bangladesh
[6] Univ Dhaka, Inst Social Welf & Res, Dhaka, Bangladesh
[7] Chattogram Imperial Coll Nursing, Coll Nursing, Chattogram, Bangladesh
[8] Combined Mil Hosp, Armed Forces Nursing Serv, Dhaka, Bangladesh
[9] King Saud Univ, Dept Prince Sultan Bin Abdul Aziz Coll Emergency M, Riyadh, Saudi Arabia
[10] Western Norway Univ Appl Sci, Dept Hlth & Functioning, Bergen, Norway
关键词
artificial intelligence; nursing education; health educators; technology; ethics; PEDAGOGICAL CONTENT KNOWLEDGE; QUALITATIVE RESEARCH;
D O I
10.1177/23779608251342931
中图分类号
R47 [护理学];
学科分类号
1011 ;
摘要
Background The integration of artificial intelligence (AI) into education has the potential to revolutionize teaching and learning practices, especially in nursing education, which combines theoretical and practical knowledge. However, challenges such as infrastructural limitations, ethical considerations, and a lack of educator preparedness hinder its widespread adoption in settings with limited access to technology, insufficient funding, and inadequate training opportunities for educators. Aims This study explores nursing educators' perspectives on integrating AI into academic settings. Methods Using the Technological Pedagogical Content Knowledge framework, this qualitative study employed a phenomenological approach to understand nursing educators' lived experiences. Data were collected through 14 semistructured interviews and three focus group discussions with 16 participants from three nursing colleges in Bangladesh. Thematic analysis was conducted to identify key insights and trends. Results Nursing educators recognized the potential of AI tools, such as adaptive learning platforms, virtual simulations, and predictive analytics, to enhance teaching efficiency, personalize learning, and engage students. However, barriers such as insufficient training, infrastructural challenges, and ethical concerns related to data privacy, algorithmic bias, and AI-driven decision making were highlighted. Thematic analysis revealed five major themes: (1) perceived benefits of AI, (2) barriers to AI integration, (3) ethical considerations in AI use, (4) educator readiness and adaptation, and (5) AI as a tool for personalized learning. Many educators expressed a need for professional development and institutional support to effectively integrate AI technologies. Strategies for overcoming these challenges included targeted training programs, ethical guidelines, and addressing disparities in resource distribution. Conclusions AI holds transformative potential for nursing education, offering opportunities to enhance teaching and learning. However, its effective integration requires addressing educators' readiness, ethical challenges, and resource limitations. These findings underscore the importance of equipping nursing educators with the necessary competencies to prepare future nurses for AI-enhanced clinical environments, thereby bridging education with evolving healthcare practice.
引用
收藏
页数:17
相关论文
共 63 条
[1]   Perceptions and Attitudes of Registered Nurses and Nursing Students Toward Advanced Technology and Artificial Intelligence [J].
Abdelaziz, Omar ;
Lee, Sohye ;
Howard, Sheri ;
Lefler, Leanne .
CIN-COMPUTERS INFORMATICS NURSING, 2025, 43 (03)
[2]  
Abdelwahab SI, 2025, TEACH LEARN NURS, V20, pe356, DOI [10.1016/j.teln.2024.11.018, 10.1016/j.teln.2024.11.018]
[3]   A Strengths, Weaknesses, Opportunities, and Threats (SWOT) Analysis of ChatGPT Integration in Nursing Education: A Narrative Review [J].
Abujaber, Ahmad A. ;
Abd-alrazaq, Alaa ;
Al-Qudimat, Ahmad R. ;
Nashwan, Abdulqadir J. .
CUREUS JOURNAL OF MEDICAL SCIENCE, 2023, 15 (11)
[4]  
Ahmed FR, 2025, TEACH LEARN NURS, V20, pe408, DOI [10.1016/j.teln.2024.12.002, 10.1016/j.teln.2024.12.002]
[5]  
Ahmed SK, 2024, Journal of Medicine Surgery and Public Health, V2, P100051, DOI [10.1016/j.glmedi.2024.100051, 10.1016/j.glmedi.2024.100051, DOI 10.1016/J.GLMEDI.2024.100051, https://doi.org/10.1016/j.glmedi.2024.100051]
[6]   Empirical Research on Technological Pedagogical Content Knowledge (TPACK) Framework in Health Professions Education: A Literature Review [J].
Ait Ali, Driss ;
El Meniari, Abdelilah ;
El Filali, Saadia ;
Morabite, Oumaima ;
Senhaji, Fatima ;
Khabbache, Hicham .
MEDICAL SCIENCE EDUCATOR, 2023, 33 (03) :791-803
[7]   The effect of artificial intelligence supported case analysis on nursing students' case management performance and satisfaction: A randomized controlled trial [J].
Akutay, Seda ;
Kacmaz, Hatice Yuceler ;
Kahraman, Hilal .
NURSE EDUCATION IN PRACTICE, 2024, 80
[8]   ChatGPT in nursing education: opportunities and challenges [J].
Athilingam, Ponrathi ;
He, Hong-Gu .
TEACHING AND LEARNING IN NURSING, 2024, 19 (01) :97-101
[9]   Transforming Education: A Comprehensive Review of Generative Artificial Intelligence in Educational Settings through Bibliometric and Content Analysis [J].
Bahroun, Zied ;
Anane, Chiraz ;
Ahmed, Vian ;
Zacca, Andrew .
SUSTAINABILITY, 2023, 15 (17)
[10]   Artificial Intelligence in Nursing: Catalyzing Change Across Clinical, Educational, and Administrative Domains [J].
Barbosa, Sayonara de Fatima F. ;
Topaz, Maxim ;
Pruinelli, Lisiane .
JOURNAL OF NURSING SCHOLARSHIP, 2025, 57 (01) :3-4