Amel Dawod Kamel Gouda, Marwa Samir Sorour, Amany Salama Ayoub, Reda M. Nabil Aboushady, Mai Nour Eldien Mohamed Mohamed Awad, Fatma Mohamed El swerky, M Ayed, Basma W. Elrefay, Hend Abdelmonem Eid Elshnawie, Heba Elsayed
BACKGROUND: Artificial intelligence (AI) is rapidly permeating health systems, yet undergraduate nursing students often report limited AI literacy and uncertainty about safe, appropriate use. AIM: To evaluate the effect of a standardized 10-session blended curriculum on nursing students’ AI knowledge and acceptance and to examine theory-consistent associations between knowledge and acceptance. DESIGN: One-group pretest–posttest quasi-experimental study. METHODS: A stratified random sample of undergraduates (n=1,000) from the Faculty of Nursing, Sohag University (Egypt) completed a self-administered questionnaire at baseline and one month after the program. Outcomes were the AI Knowledge Scale (AIKS-16; 0–32) and the AI Acceptance Scale (AIA-34; 0–136) aligned with Technology Acceptance Model subdomains (Perceived Usefulness [PU], Perceived Ease of Use [PEOU], Attitude/Intention). Analyses used paired t-tests with 95% CIs and Cohen’s d; Pearson correlations; and exploratory ANCOVA adjusting for baseline to probe subgroup differences (sex, residence). Ethics approval: IRB 88-6-2023. RESULTS: Knowledge increased from 15.01±4.72 to 30.33±3.11 and acceptance from 67.02±13.47 to 122.33±9.21 (both p<0.001; large effects). Gains were observed across PU, PEOU, and Attitude/Intention. Post-test knowledge correlated strongly with acceptance (r=0.647, p<0.001). ANCOVA showed no educationally meaningful differences by sex or residence after adjustment (partial η2 ≤0.006). Knowledge-level transitions indicated marked movement from low/moderate to high categories. CONCLUSIONS: A standardized, fidelity-checked blended curriculum produced substantial and equitable improvements in AI knowledge and acceptance among undergraduate nursing students. Framed by the Technology Acceptance Model, results suggest that concept scaffolding, brief hands-on practice, and explicit disclosure/verification routines strengthen perceived usefulness and ease of use, supporting accountable AI adoption. Multi-site controlled studies with performance-based outcomes and longer follow-up are warranted. TRIAL REGISTRATION: Not applicable. This was an educational pretest–posttest study with no clinical trial component.