"Is GenAI my supervisor?" Experiences of nursing undergraduates in using generative AI to assist in case study theses: A qualitative study.

OBJECTIVE: This qualitative study aimed to explore the experiences of nursing undergraduate students using Generative Artificial Intelligence (GenAI) for their case study theses. BACKGROUND: The growing use of GenAI in academic settings has facilitated its gradual integration into nursing education. Although the application of GenAI for educational purposes in nursing is gaining traction, in the integration of GenAI into thesis writing practices, especially the type of case study, remains limited. DESIGN: This study employed a qualitative descriptive design. PARTICIPANTS: Participants were selected using purposive sampling. A total of 19 graduates holding a Bachelor of Science in Nursing degree were included in the study. METHOD: Data were collected through semi-structured interviews to obtained perspectives from nursing graduates. The collected data were encoded and analyzed using thematic analysis method. RESULTS: We extracted 163 codes from the interview data and categorized them into three main categories with eight subcategories: a) AI-Driven Factors: insufficient academic writing skills, lack of supervisor's guidance and a climate of widespread recommendations; b) Dual-edged performance: boost writing efficiency and accuracy concerns; c) Hidden costs of AI: outsourcing of cognition, ethical compliance challenges and self-deception. CONCLUSION: This study revealed the diverse experiences among nursing undergraduates using GenAI in their case study work. It provides valuable insights for nursing institutions to establish GenAI usage guidelines and enhance support systems, offering insights to inform educational interventions.