The effect of artificial intelligence supported case analysis on nursing students' case management performance and satisfaction: A randomized controlled trial

Background: Rapid developments in artificial intelligence have begun to necessitate changes and transformations in nursing education. Objective: This study aimed to evaluate the impact of an artificial intelligence-supported case created in the inclass case analysis lecture for nursing students on students' case management performance and satisfaction. Design: This study was a randomized controlled trial. Method: The study involved 188 third-year nursing students randomly assigned to the AI group (n=94) or the control group (n=94). An information form, case evaluation form, knowledge test and Mentimeter application were used to assess the students' case management performance and nursing diagnoses. The level of satisfaction with the case analysis lecture was evaluated using the VAS scale. Results: The case management performance scores of the students in the artificial intelligence group were significantly higher than those of the control group (p<0.05). There was no statistically significant difference in satisfaction levels between the artificial intelligence (AI) group and the control group (p>0.05). Conclusions: The study's results indicated that AI-supported cases improved students' case management performance and were as effective as instructor-led cases regarding satisfaction with the case analysis lecture, focus and interest in the case. The integration of artificial intelligence into traditional nursing education curricula is recommended. Clinical trials registration number: https://register.clinicaltrials.gov; (NCT06443983).