Undergraduate Nursing Students' Perspectives on Artificial Intelligence in Academia.

Journal: The Canadian Journal Of Nursing Research = Revue Canadienne De Recherche En Sciences Infirmieres
Published:
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.

Authors
Michelle Lam, Nassim Adhami, Olivia Du, Riley Huntley, Abdul-fatawu Abdulai, Karen Yi Wong, Lillian Hung