Authenticity and academic integrity in Generative Artificial Intelligence (GenAI) use among undergraduate nursing students. - Siah, Chiew-Jiat Rosalind; Lim, Junwei Vincent; Lyu, Meng Meng; Levett-Jones, Tracy; Mattar, Ihsan (Journal of Professional Nursing, 2026)
The use of large Generative Artificial Intelligence (GenAI) in higher education is reshaping how students learn. While GenAI offers significant benefits and the potential to improve education, it also poses ethical challenges and may affect students' ability to identify learning gaps and engage with course content. This study aims to explore students' experiences with GenAI related to academic integrity and the authenticity of work, including their awareness and attitudes toward acceptable use. This study employed a qualitative descriptive approach. The participants were recruited from the Bachelor of Science (Nursing) program in an academic university during the period October 2024 to January 2025. Fourteen undergraduates in their second- and third-year of study participated in group interviews. The qualitative data analysis revealed five key themes: 1) integration with learning, 2) trust and credibility of GenAI information, 3) ethical considerations, 4) addressing academic integrity, and 5) guidance on using GenAI. These five key themes underscore the need to better understand the role of GenAI in higher education, particularly in self-directed learning and managing learning activities. With regards to academic integrity, clear guidelines must be put in place for educators to guide the use of GenAI, emphasizing its use as an instrument to augment, and not replace original work. • Participants emphasized personal accountability and expressed concerns on over-reliance on GenAI. • Authentic academic work is important for developing clinical reasoning and analytical skills. • There is a need for institutional guidelines that define plagiarism and ethical GenAI use.