From Cases to Confidence: Developing Diagnostic Reasoning Skills Through Collaborative Learning in Graduate Nursing Education

Abstract Teaching diagnostic reasoning to graduate nursing students is both essential and challenging, particularly in asynchronous environments where absence of real-time interaction requires innovative strategies to engage students and support the development of clinical application skills. The innovation detailed in this article demonstrates a collaborative learning approach using artificial intelligence (AI)-generated cases to simulate clinical scenarios and cultivate diagnostic reasoning in first-year advanced practice provider students. Pre- and post-assessments showed increased confidence; qualitative reflections emphasized the value of peer collaboration. This innovative model demonstrates how collaborative learning, supported by AI, can transform clinical education in asynchronous nursing programs.