Impact of AI-Supported Teaching on Clinical Decision-Making in Nursing Students

In the intervention group (C-CASE), after informed consent and pretest completion (including a sociodemographic form and CDMNS), the case scenario was introduced by the course instructor. Students were divided into small groups, and each group selected a representative who accessed ChatGPT-4.0 Premium via credentials provided by the research team. Using a collaborative problem-solving format, each group worked through a structured case scenario involving pediatric surgical emergencies. Questions were distributed sequentially, with 5-minute intervals allocated per question. Students used ChatGPT to support reasoning and clinical decision-making within their group. After each interval, responses were submitted, and the next question was handed out. Sessions were proctored by research assistants, and the full implementation, including discussion, lasted approximately two hours. The intervention aimed to foster decision-making, teamwork, and AI literacy in a clinical nursing education.

In the control group (Standard Education), students followed the same structured case-based learning session as the intervention group, without access to AI tools. After providing informed consent and completing the pretest (sociodemographic form and CDMNS), the case scenario was introduced by the instructor. Students were divided into small groups and selected a representative to use a personal computer during the session. To ensure no access to AI-based tools, the Mobile Guardian app was installed to block websites such as ChatGPT. Students were allowed to use only academic databases and the university's online library. Each group answered a series of timed case questions (5 minutes per item), submitting responses before receiving the next question. Research assistants monitored the session in both classrooms to ensure standardization and prevent external support. The session concluded with a class-wide case discussion, led by the course instructor.