From Script to Simulation

<p>This study examines the use of generative artificial intelligence (GAI) to develop an interactive digital simulation aimed at reinforcing Universal Design for Learning (UDL) principles in a graduate-level nursing education course. Using Twine, an open-source platform for non-linear storytelling, the simulation presented a series of branching scenarios in which learners engaged with diverse student profiles and made instructional decisions grounded in accessibility and inclusivity. GAI tools—ChatGPT, Microsoft Copilot, and ElevenLabs—were used to generate narrative content, Twine code, visual assets, and audio narration, creating a multimodal learning experience aligned with UDL guidelines. Guided by the Artificial Intelligence Technological Pedagogical Content Knowledge (AI-TPACK) framework, this qualitative descriptive study employed reflexive thematic analysis (RTA) to examine students’ perceptions of the simulation’s cultural sensitivity, pedagogical value, and educational utility. Findings indicate that participants perceived the AI-generated content as generally inclusive and contextually appropriate, though some noted concerns about reductive diversity and stereotyping. Students appreciated the simulation’s interactivity, multimodal design, and relevance to their future roles as nurse educators. Quantitative data from Likert-scale responses corroborated these themes, with participants largely agreeing that the simulation promoted engagement and enhanced decision-making skills related to UDL. These findings suggest that GAI, when guided by pedagogical intent and supported by human oversight, can effectively and efficiently contribute to the creation of accessible, engaging, and contextually relevant learning assets in nursing education. The study contributes to the growing body of research on the educational applications of GAI and offers practical implications for the design of inclusive digital simulations in health professions education.</p>