Exploring the Experience and Perception of Artificial Intelligence Utilization Among Students of Department of Nursing, Bayero University Kano
Open accessAbstract
Artificial intelligence (AI) is rapidly transforming various sectors, including healthcare and education. In nursing, AI has the potential to enhance educational outcomes and improve clinical practices. The study aim to explore the nuanced experiences and perceptions of nursing students at Bayero University, Kano, in relation to the use of AI in their academic and clinical environments. A qualitative narrative inquiry was conducted among nursing students at Bayero University, Kano. Focus group discussion was used to collect data from the participants. Thematic analysis was employed to identify and interpret themes related to their experiences and perceptions of AI. The study identified that the majority of students have engaged with AI technologies primarily for academic purposes, such as researching assignments and accessing clinical information. However, they demonstrated limited awareness of nursing-specific AI tools. Participants also reported significant challenges related to network connectivity and data access, which hindered their use of AI. Despite these challenges, the overall perception of AI was positive, with students acknowledging its potential to improve nursing education and practice. Concerns about technical errors, over-reliance, and job displacement were also noted. Nursing students at Bayero University, Kano, recognize the potential benefits of AI in education and clinical practice but face significant challenges due to infrastructural limitations. Their p…
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The absence of standardized ethical and pedagogical frameworks means that students must navigate these technologies through their own interaction practices, often without guidance.
“However, the absence of standardized ethical and pedagogical frameworks means that students must navigate these technologies through their own interaction practices, often without guidance [29, 39, 42].”
From From adoption to interaction: examining human-GenAI engagement patterns, ethical tensions, and educational trade-offs in nursing education (2026) · cites this paper as [42]
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Yang, M., Long, J., He, Y., Meng, R., Ling, C., Long, Q., & Wen, J. (2026) · BMC Nursing · doi:10.1186/s12912-026-05132-7
- Authors
- Rajah, A. S., Sardauna, Z. M., & Ladan, M. A.
- Venue
- REAL in Nursing Journal
- Publisher
- Universitas Fort De Kock
- Published
- 2024-12-23
- Volume
- 7
- Issue
- 3
- Pages
- 220
- ISSN
- 2685-1997 (ISSN-L)
- 2685-9068
- OpenAlex
- W4406598873
- Cited by
- 1
- References
- 0
- Citations by year
- 2025: 1
- FWCI
- 0.09
- Type
- journal article
- Language
- en
- Open access
- diamond
- doi.org
- Licence
- cc-by-sa
- Locations
- REAL in Nursing Journal (publishedVersion, cc-by-sa)
- Topics
- Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
- Physical Sciences › Computer Science › Information Systems › Artificial Intelligence in Education
- Physical Sciences › Computer Science › Artificial Intelligence › Artificial Intelligence Applications
- Keywords
- artificial intelligence in nursing, nursing students, student perceptions of AI, technological infrastructure barriers, overreliance on AI, Bayero University Kano
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