Breaking Barriers in Simulation Using Accessible Pedagogical Innovation: Enhancing Nursing Students’ Clinical Competence through Cost-Effective 360° VR with Structured Debriefing.

Abstract

<p><strong>Background</strong></p><p>Universities are crucial in helping nursing students transition to becoming registered nurses. Our previous study reported that Generative AI can enhance students' clinical competence, cultural awareness and AI readiness. We have developed real-case generative AI patients in a virtual simulation setting to train final-year nursing students and prepare them for a smooth transition into professional practice. </p><p><br></p><p><strong>Objective</strong></p><p>This study aims to assess the preliminary effectiveness of generative AI in enhancing final-year nursing students’ clinical competence and readiness for clinical practice.</p><p><br></p><p><strong>Methods</strong></p><p>This pilot study used a one-group, pre- and post-test experimental design. Final-year nursing students who enrolled in the course, which provides a virtual environment for students to practise various generative AI patients, were invited. Participants completed two online questionnaires, the Casey-Fink Readiness for Practice Survey (CF-RFPS) and Clinical Competence Questionnaire (CCQ), before and after participating in two generative AI workshops. In workshops, students interviewed AI patients, conducted health assessments, performed nursing interventions, and identified nursing diagnoses with prioritisation. They received generative AI feedback on their performance. </p><p><br></p><p><strong>Results</strong></p><p>Thirteen final-year nursing students (4 males and 9 females) participated in this pilot study. After the generative AI workshops, improvements were found in the overall scores and subscales of the CF-RFPS and the CCQ. These improvements in the CF-RFPS subscales included ‘clinical problem solving’, ‘learning techniques’, ‘professional identity’, and ‘trials & tribulations’. Similarly, the CCQ subscales—‘nursing professional behaviour’, ‘general performance’, ‘core nursing skills’, and ‘advanced nursing skills’—also showed increases. </p><p><br></p><p><strong>Conclusion</strong></p><p>The results support that the general AI can enhance final-year nursing students’ clinical competence and help them prepare to become registered nurses. More studies are needed to investigate further the effectiveness of generative AI in helping final year nursing students prepare themselves and enhance their clinical competency to become registered nurses.</p>