Exploring Undergraduate Nursing Students’ Perception on AI Integration in the Classroom
A Descriptive Qualitative Study
DOI:
https://doi.org/10.48112/bms.v3i1.1211Abstract
Abstract Views: 149
The sudden emergence of Artificial Intelligence (AI) in the healthcare industry has brought into being a paradigm shift needed but restless in the field of nursing education. These two approaches to learning and knowledge transfer are the most important because the curricular gap between the old and the new digital reality of the modern clinical practice and the ways to negotiate these technologies in nursing students is growing wider with each passing day. This qualitative research is a descriptive study that will examine the perceptions, attitudes, and lived experiences of undergraduate nursing students in terms of the application of AI tools, namely Generative AI (GenAI) and Virtual Reality (VR), in the classroom and clinical learning settings. Data were gathered using semi-structured philosophy of focus groups with undergraduate nursing students (N=22) to reflect on the student experience in order to capture its essence in terms of the descriptive phenomenological approach. The interpretations of the qualitative data were done using thematic analysis. The results indicate the complex dichotomy of the student perceptions. Although the students do see the possibility of AI improving the efficiency of learning, tailoring study schedules and offering secure and simulated clinical settings, there are major challenges when it comes to professional identity. Overwhelming themes included: AI as an Efficiency Tool vs. Critical Thinking Barrier, The Safety Net of Virtual Reality, and Ethical Anxiety and The Hidden Curriculum. The participants were deeply worried about the fact that the overuse of AI could destroy the fundamental humanistic nursing competencies and compassion and create such a phenomenon as de-skilling. The research concludes that students are usually prepared to accept AI technically, but they do not have the required ethical frameworks and institutional guidance that they could be sure. Therefore, AI introduction into nursing education should not be technical but pedagogical by focusing on both AI literacy and human-centered care. These observations can guide educators to plan their curricula based on the idea that AI could be used as a guide, not to replace the critical thinking of nursing.
Keywords:
Artificial Intelligence, Nursing Education, Student Perception, Qualitative Study, Academic Integrity, Virtual Reality.References
Abou Hashish, E. A., Alsayed, S. A., & Abdel Razek, N. M. F. (2025). Embracing AI in academia: A mixed methods study of nursing students’ and educators’ perspectives on using ChatGPT. PLOS ONE, 20(7), e0327981. https://doi.org/10.1371/journal.pone.0327981
Ahmad, M. N., Abdallah, S. A., Abbasi, S. A., & Abdallah, A. M. (2023). Student perspectives on the integration of artificial intelligence into healthcare services. DIGITAL HEALTH. https://doi.org/10.1177/20552076231174095
Alenazi, L., & Al-Anazi, S. H. (2025). Understanding artificial intelligence through the eyes of future nurses: Insights from nursing students. Saudi Medical Journal, 46(3), 238–243. https://doi.org/10.15537/smj.2025.46.3.20241069
Almansour, M., & Almoayad, F. (2024). Exploring challenges and perceptions in the learning environment: An online qualitative study of medical students. BMC Medical Education, 24, 147. https://doi.org/10.1186/s12909-024-05116-8
Balay-odao, E. M., Omirzakova, D., Bolla, S. R., et al. (2025). Health professions students’ perceptions of artificial intelligence and its integration to health professions education and healthcare: A thematic analysis. AI & Society, 40, 1863–1873. https://doi.org/10.1007/s00146-024-01957-5
Bodur, G., Cakir, H., Turan, S., et al. (2025). Artificial intelligence in nursing practice: A qualitative study of nurses’ perspectives on opportunities, challenges, and ethical implications. BMC Nursing, 24, 1263. https://doi.org/10.1186/s12912-025-03775-6
Buchanan, C., Howitt, M., Wilson, R., Booth, R., Risling, T., & Bamford, M. (2021). Predicted influences of artificial intelligence on nursing education: A scoping review. JMIR Nursing, 4(1), e23933. https://doi.org/10.2196/23933
Braun, V., & Clarke, V. (2006). Using thematic analysis in psychology. Qualitative Research in Psychology, 3(2), 77–101. https://doi.org/10.1191/1478088706qp063oa
Cucci, F., Marasciulo, D., Romani, M., Soldano, G., Cascio, D., De Nunzio, G., Caldararo, C., Rubbi, I., Vitale, E., Lupo, R., & Conte, L. (2025). The contribution of artificial intelligence in nursing education: A scoping review of the literature. Nursing Reports, 15(8), 283. https://doi.org/10.3390/nursrep15080283
Emotional intelligence competencies in the undergraduate nursing curriculum: A descriptive qualitative study. https://doi.org/10.1016/j.nedt.2022.105594
Fontenot, J., Hebert, M., Lin, H. C., & Kulshreshth, A. K. (2024). Examining the perceptions among undergraduate nursing students using virtual reality in a community course: A mixed-methods explanatory study. Journal of Community Health Nursing, 41(3), 145–155. https://doi.org/10.1080/07370016.2023.2280617
Gonzalez-Garcia, A., Bermejo-Martinez, D., Lopez-Alonso, A. I., Trevisson-Redondo, B., Martín-Vázquez, C., & Perez-Gonzalez, S. (2025). Impact of ChatGPT usage on nursing students education: A cross-sectional study. Heliyon, 11(1). https://doi.org/10.1016/j.heliyon.2024.e41559
Irfan, M., Murray, L. I. A. M., & Ali, S. (2023). Insights into student perceptions: Investigating artificial intelligence (AI) tool usability in Irish higher education at the University of Limerick. http://dx.doi.org/10.31703/gdpmr.2023(VI-II).05
Kong, W., Ning, Y., Ma, T., Song, F., Mao, Y., Yang, C., et al. (2024). Experience of undergraduate nursing students participating in artificial intelligence+ project task driven learning at different stages: A qualitative study. BMC Nursing, 23(1), 314. https://doi.org/10.1186/s12912-024-01982-1
Kowitlawakul, Y., Tan, J. J. M., Suebnukarn, S., Nguyen, H. D., Poo, D. C. C., Chai, J., Kamala, D. M., Wang, W. (2024). Development of an artificial intelligence teaching assistant system for undergraduate nursing students: A field testing study. Computers, Informatics, Nursing, 42(5), 334-342. https://doi.org/10.1097/CIN.0000000000001103
Labrague, L. J., & Al Sabei, S. (2024). Integration of AI-powered chatbots in nursing education: A scoping review of their utilization, outcomes, and challenges. Teaching and Learning in Nursing. https://doi.org/10.1016/j.teln.2024.11.010
Labrague, L. J., Aguilar-Rosales, R., Yboa, B. C., Sabio, J. B., de los Santos, J. A. (2023). Student nurses' attitudes, perceived utilization, and intention to adopt artificial intelligence (AI) technology in nursing practice: A cross-sectional study. Nurse Education in Practice, 73, 103815. https://doi.org/10.1016/j.nepr.2023.103815
Alharbi, M., Kuhn, L., & Morphet, J. (2020). Undergraduate nursing students' adoption of the professional identity of nursing through social media use: A qualitative descriptive study. Nurse Education Today. https://doi.org/10.1016/j.nedt.2020.104488
Magalhães Araujo, S., & Cruz-Correia, R. (2024). Incorporating ChatGPT in medical informatics education: Mixed methods study on student perceptions and experiential integration proposals. JMIR Medical Education, 10, e51151. https://doi.org/10.2196/51151
Zgambo, M., Costello, M., Buhlmann, M., Maldon, J., Anyango, E., Adama, E. (2025). Artificial intelligence and academic integrity in nursing education: A mixed methods study on usage, perceptions, and institutional implications. Nurse Education Today, 153, 106796. https://doi.org/10.1016/j.nedt.2025.106796
Movahhedi, T., Hajiyavand, A. M., & Dearn, K. D. (2023). Exploring undergraduates’ perceptions of and engagement in an AI-enhanced online course. Frontiers in Education, 8, 1252543. https://doi.org/10.3389/feduc.2023.1252543
Nezhad, M. S., Abdi, A., & Ahmadi, M. (2025). Exploring the experiences and perceptions of nursing students in utilizing artificial intelligence: A descriptive phenomenological study. BMC Nursing, 24, 740. https://doi.org/10.1186/s12912-025-03392-3
Nursing students' perceptions on motivation strategies to enhance academic achievement through blended learning: A qualitative study. https://doi.org/10.1016/j.heliyon.2022.e09818
Perceptions and experiences of Generation Z nursing students during their practicum in an intensive care unit: A qualitative study. https://doi.org/10.1016/j.heliyon.2024.e26205
Ramadan, O. M. E., Alruwaili, M. M., Alruwaili, A. N., et al. (2024). Facilitators and barriers to AI adoption in nursing practice: A qualitative study of registered nurses' perspectives. BMC Nursing, 23, 891. https://doi.org/10.1186/s12912-024-02571-y
Rony, M. K. K., Ahmad, S., Das, D. C., Tanha, S. M., Deb, T. R., Akter, M. R., & Akter, F. (2025). Nursing students' perspectives on integrating artificial intelligence into clinical practice and training: A qualitative descriptive study. Health Science Reports, 8(4). https://doi.org/10.1002/hsr2.70728
Saab, M. M., Hegarty, J., Murphy, D., & Landers, M. (2021). Incorporating virtual reality in nurse education: A qualitative study of nursing students' perspectives. Nurse Education Today, 105, 105045. https://doi.org/10.1016/j.nedt.2021.105045
Saab, M. M., Hegarty, J., Murphy, D., & Landers, M. (2021). Incorporating virtual reality in nurse education: A qualitative study of nursing students' perspectives. Nurse Education Today, 105, 105045. https://doi.org/10.1016/j.nedt.2021.105045
Saab, M. M., Hegarty, J., Murphy, D., & Landers, M. (2021). Incorporating virtual reality in nurse education: A qualitative study of nursing students' perspectives. Nurse Education Today, 105, 105045. https://doi.org/10.1016/j.nedt.2021.105045
Saab, M. M., Landers, M., Murphy, D., O’Mahony, B., Cooke, E., O’Driscoll, M., & Hegarty, J. (2022). Nursing students’ views of using virtual reality in healthcare: A qualitative study. Journal of Clinical Nursing, 31(9-10), 1228-1242. https://doi.org/10.1111/jocn.15978
Undergraduate nursing students' perceptions of active learning strategies: A focus group study. https://doi.org/10.1016/j.nedt.2023.105986
Vera, F. (2024). Students' perceptions of the integration of artificial intelligence in nursing education: A study at a private Chilean university. Transform, 5(4), 58–73. https://www.revistatransformar.cl/index.php/transformar/article/view/148
Yalcinkaya, T., Ergin, E., & Yucel, S. C. (2024). Exploring nursing students' attitudes and readiness for artificial intelligence: A cross-sectional study. Teaching and Learning in Nursing, 19(4), e722-e728. https://doi.org/10.1016/j.teln.2024.07.008
Yuan, Y., Fu, J., Leng, L., Wen, Z., Wei, X., Han, D., Hu, X., Liang, Y., Luo, Q., Zhang, X., & Hu, R. (2025). The strengths, weaknesses, opportunities, and threats of generative artificial intelligence: A qualitative study of undergraduate nursing students. Frontiers in Public Health, 13, 1672140. https://doi.org/10.3389/fpubh.2025.1672140
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