The Effects of Metacognition, Digital Literacy, and Perceptions of Artificial Intelligence on Learning Ethics among Nursing Students
This descriptive survey study aimed to identify the factors influencing learning ethics among 134 nursing students in G city. Data were collected from May 25 to June 3, 2026, and analyzed using the SPSS 23.0 program. The results indicated relatively high levels of metacognition(4.34±0.43), digital literacy(4.38±0.51), artificial intelligence(AI) perception(3.79±0.87), and learning ethics(3.25±0.53). Significant positive correlations were observed among all research variables. Multiple regression analysis revealed that learning ethics was significantly predicted by AI perception(β=.423, p<.001), AI education experience(β=.422, p<.001), major satisfaction('satisfied': β=.257, 'very satisfied': β=.228, p<.001), being a 3rd-year student(β=.245, p<.001), metacognition(β=.207, p<.001), and gender(β=.135, p=.003). The model’s total explanatory power was 82.4%.These findings suggest that establishing learning ethics in an educational environment with expanding generative AI usage requires fostering correct AI perceptions, providing practical AI ethics education, and enhancing metacognition as a self-regulatory capacity. Consequently, systematic educational programs that integrate AI ethics and metacognition while considering learner characteristics and educational experiences should be developed and implemented.