Scalable Antibiotic Stewardship Training via Adaptive Game Dynamics and Procedural Content Generation

**Abstract:** This research introduces a novel framework for personalized and scalable antibiotic stewardship (AS) education leveraging adaptive game dynamics and procedural content generation (PCG). Recognizing the limitations of traditional AS training methods, which often lack engagement and individualized feedback, we propose a system that dynamically adjusts gameplay and content based on player performance and learning needs. The framework utilizes a multi-layered evaluation pipeline, incorporating logical consistency verification, mechanistic simulation of bacterial resistance, and real-time assessment of decision-making processes. This enables personalized learning pathways and provides immediate, constructive feedback, enhancing knowledge retention and promoting behavioral change amongst healthcare professionals. The proposed system is readily commercializable within a 5-year timeframe and addresses a critical need to combat the global threat of antibiotic resistance.