Association Between ChatGPT Reliance, Self‐Directed Learning, and Problem‐Solving Competencies Among Nursing Students: The Mediating Role of Academic Self‐Efficacy in an Analytical Cross‐Sectional Design. - Elzeky, Mohamed E. H.; Alanazi, Sulaiman; F. M. Shahine, Noha; Atashzadeh-Shoorideh, Foroozan (Nursing Forum, 2026)
Background: Although prior research has highlighted problematic patterns of artificial intelligence (AI) use in education, including overreliance on AI tools, the academic implications of such reliance among nursing students remain insufficiently explored. Aim: To examine the associations between reliance on ChatGPT (ROC) during nursing education and academic self‐efficacy (ASE), self‐directed learning (SDL), and problem‐solving ability (PSA) among nursing students. Methods: A cross‐sectional design was employed. Data were collected from undergraduate nursing students using validated self‐report measures assessing ROC, ASE, SDL, and PSA. Structural path analysis using maximum likelihood estimation was conducted to examine direct and indirect relationships among the study variables, with ASE specified as a mediator. Indirect effects were tested using bias‐corrected bootstrapping (5000 resamples). Multigroup analysis was performed to explore gender differences. Results: ROC was significantly and negatively associated with ASE (β = −0.248, p < 0.001). ASE was positively associated with SDL (β = 0.742, p < 0.001) and negatively associated with problem‐solving difficulties (PSA) (β = −0.569, p < 0.001). Indirect effects indicated that ROC was associated with lower SDL (B = −0.185, 95% CI [−0.200, −0.099]) and higher problem‐solving difficulties (B = 0.145, 95% CI [0.095, 0.191]) through reduced ASE. Gender differences were observed, with a stronger negative association between ChatGPT reliance and ASE among female students, and a stronger positive association between ASE and SDL among male students. Conclusions: ChatGPT reliance was associated with nursing students' academic competencies primarily through its relationship with ASE. These findings raise concerns about the potential erosion of critical thinking and learning autonomy associated with uncritical AI use. The results highlight the need for structured and ethically guided integration of AI in nursing education to support SDL and preserve core professional competencies.