Artificial Intelligence Assisted Teaching of Structured Nursing Care According to ERAS Protocol

This study evaluates an AI-supported case-based educational approach for teaching nursing care of gynecologic oncology patients according to the Enhanced Recovery After Surgery (ERAS) protocol. This single-center, parallel-group randomized controlled trial was conducted during the second semester of the 2024-2025 academic year with third-year undergraduate nursing students who had successfully completed the Obstetrics and Gynecology Nursing course and its related clinical practice at a public university in western Türkiye. A total of 76 students were randomized in equal proportions to the AI-supported case-simulation group or the control group using block randomization. Six participants were lost to follow-up because of withdrawal or incomplete data collection forms, and the final analyses included 70 students (35 in each group). Data were collected before and after the intervention using the researcher-developed ERAS Protocol Nursing Care Knowledge Test and the Multidimensional 21st Century Skills Scale. Descriptive statistics, including frequencies, percentages, means, and standard deviations, were used to summarize participant characteristics and study variables. Baseline characteristics were examined using independent-samples t-tests for continuous variables and chi-square tests for categorical variables. Intervention effects were evaluated using 2 × 2 mixed-design analysis of variance (ANOVA), with time (pretest and posttest) as the within-subjects factor and group (AI-supported intervention and control) as the between-subjects factor. The principal effect of interest was the Time × Group interaction, indicating whether changes from pretest to posttest differed between groups. The same analytical approach was applied to ERAS knowledge, the total 21st-century skills score, and its subdimensions. Effect sizes were reported using partial eta squared (partial η²), and statistical significance was set at p \< .05.