Enhancing Nursing Simulation with AI-Generated Scenarios Using Retrieval-Augmented Generation (RAG)

Date: 05 Nov 2025, Wed | Time: 1535 - 1605 | Track Type: Workshops
Format: Face-to-face | Venue: Level 2, L2-T2
Speaker: Mr Mario Putong

Traditional nursing simulations often rely on static case scenarios, limiting adaptability and realism. This workshop introduces an innovative approach that integrates AI-driven avatars with Retrieval-Augmented Generation (RAG) to dynamically generate patient cases and dialogue based on real-world data and learning objectives.The session aims to demonstrate how educators and simulation designers can leverage AI to create contextually relevant, personalized, and evolving scenarios that enhance clinical reasoning and communication skills.

By the end of the workshop, participants will be able to:

1. Understand how RAG models retrieve and contextualize medical data to generate realistic simulation narratives.
2. Design dynamic nursing simulation cases using AI avatars that respond to learner inputs.
3. Evaluate and adapt AI-generated content for accuracy, ethical use, and educational alignment.

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