Artificial Intelligence Supported Case Analysis on Nursing Education

The Effect of Artificial Intelligence Supported Case Analysis on Nursing Students' Case Management Performance and Satisfaction: A Randomized Controlled Trial

Background: Rapid developments in the field of 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 in-class 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 who were randomly assigned to either the AI group (n=94) and 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.

Inclusion Criteria:

• having taken nursing process lecture before
• having planned care for at least one surgical patient in clinical practice before
• having a mobile phone with internet connection

Exclusion Criteria:

• not attending the case analysis lecture
• not being an active student
• incomplete completion of the data collection forms
• not accepting to participate in the study