ArticleThe Canadian journal of nursing research = Revue canadienne de recherche en sciences infirmieres2025
Undergraduate Nursing Students' Perspectives on Artificial Intelligence in Academia.
Article in The Canadian journal of nursing research = Revue canadienne de recherche en sciences infirmieres, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 2 of them syntheses that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
6 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Nurse educators' experiences and perceptions using generative artificial intelligence: a systematic review.BMC medical education · 2026Pooled it
- A Meta-synthesis of nursing students' experiences with generative artificial intelligence-assisted learning.Frontiers in medicine · 2026Pooled it
- Understanding undergraduate nursing students' learning journeys with artificial intelligence: a journey mapping study.BMC medical education · 2026Article
- The experience of nursing students using generative artificial intelligence: a qualitative meta-synthesis.BMC nursing · 2026Article
- Nursing Students' Experiences With Artificial Intelligence: A Qualitative Study on Education, Clinical Practice, and Future Expectations.Journal of evaluation in clinical practice · 2026Article
- The psychological mechanisms and behavioral determinants of academic integrity in the age of artificial intelligence.Frontiers in psychology · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
With Artificial Intelligence (AI) tools becoming increasingly commonplace, the usage of AI-enabled tools in education has also grown. AI-enabled tools refer to machines incorporated with human-like capabilities, such as reasoning, interpretation, and problem-solving, to perform tasks that require human intelligence. ChatGPT is one of these tools, which uses large language models (LLM), a type of AI that generates natural language, to give human-like answers to questions. This study investigated nursing students' perspectives on AI-enabled tools, such as ChatGPT, aiming to identify (1) perceived benefits and challenges and (2) implications for the ethical and responsible use of AI within undergraduate nursing programs. Using interpretive description, we conducted focus group interviews with undergraduate nursing students. Through convenience sampling, sixteen students were recruited. Our findings revealed four key themes - utilization as a support tool, utilization leading to a loss of competency in foundational skills, utilization risking credibility and academic integrity, and the need for further education and resources. Three key factors - evidence-based practice, ethical considerations, and the importance of critical thinking skills - influence nursing students' perspectives toward AI tools. To ensure the safe and ethical use of AI in academia, robust institutional policies and training are needed. Promoting open dialogues and education can help students understand AI's advantages, potential harms, and risk mitigation strategies. Future research should build a comprehensive understanding of the perspectives of undergraduate and graduate nursing students, and educators on AI usage in academia. Development of interventions that mitigate AI-usage risks is also necessary to improve integration into education.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.