The effect of artificial intelligence literacy on self-directed learning skills: the mediating role of attitude towards artificial intelligence: a study on nursing and midwifery students

Abstract

Aim: This study investigates the impact of generative artificial intelligence literacy (GAIL) on self-directed learning skills (SDL) among nursing and midwifery students. Additionally, it examines whether general attitudes toward artificial intelligence (GAAI) mediate this relationship. Background: Artificial intelligence (AI) has the potential to support the development of clinical decision-making and problem-solving skills in nursing and midwifery education, particularly by enhancing students' self-directed learning abilities. Methods: A cross-sectional, descriptive and correlational study design was used. The study was conducted in three universities in T & uuml;rkiye between January and February 2025. 656 nursing and midwifery students participated, selected through cluster sampling. Data were collected using the GAIL, GAAI and SDL scales. The survey form included descriptive questions regarding participants' socio-demographic characteristics and AI usage patterns. Structural equation modeling was conducted to analyze direct and indirect relationships among variables. Results: A significant positive effect of GAILS on GAAIS was found (beta = 0.75, p < .01). GAILS also had a direct and significant effect on SDLS (beta = 0.60, p < .01). However, GAAIS did not mediate the relationship between GAILS and SDLS (beta = 0.02, p > .05). Conclusions: AI literacy significantly enhances SDL in nursing and midwifery students. However, positive attitudes toward AI do not independently foster SDL, highlighting the need for structured AI education in healthcare curricula. Future studies should explore long-term AI literacy interventions to assess their impact on academic outcomes and their potential contributions to clinical reasoning and decision-making skills.