Effects of nursing students’ attitudes toward artificial intelligence on self-directed learning: Analysis of the mediating effects of digital literacy sub-dimensions
TL;DR
Findings indicate that fostering a favorable attitude alone is insufficient to enhance self-directed learning and educational strategies are required to strengthen both practical skills, such as prompt construction competency, and ethical reflection in order to critically evaluate AI-generated outputs for effective nursing education.
Abstract
Purpose: This study aimed to identify the mediating effects of digital literacy sub-dimensions on the relationship between nursing students’ attitudes toward artificial intelligence (AI) and self-directed learning.Methods: Two hundred nursing students from three universities participated in the study. Data were collected through an online survey conducted from October to November 2025. Analyses were performed using IBM SPSS version 27.0 and PROCESS macro version 4.2.Results: Digital ethics competency mediated the relationship between AI attitudes and self-directed learning, showing a significant indirect effect (B=0.05, 95% confidence interval=0.001~0.117). The direct effect of attitudes toward AI on self-directed learning was not significant. Meanwhile, the mediating effects of digital tool proficiency, data utilization, and digital learning proficiency were not statistically significant.Conclusion: This study identified the mediating effect of digital ethics competency on the relationship between nursing students’ attitudes toward AI and self-directed learning. These findings indicate that fostering a favorable attitude alone is insufficient to enhance self-directed learning. Educational strategies are required to strengthen both practical skills, such as prompt construction competency, and ethical reflection in order to critically evaluate AI-generated outputs for effective nursing education.