Continuity in AI Imaging Pedagogy: Rethinking Teaching Frameworks in the Era of Multi-Modal Generative Systems

40,000

This project examines how visual storytelling education adapts to rapid advances in generative artificial intelligence. Recent multimodal systems can interpret natural language and produce coherent images, scenes, and motion, altering pedagogical conditions that previously relied on open source diffusion workflows. The project develops an updated teaching framework that integrates emerging AI imaging methods while maintaining critical visual practice and technical understanding. It combines open source production pipelines with selected commercial multimodal engines and embeds responsible AI use within the curriculum. Learning indicators including technical proficiency, workflow reasoning, narrative coherence, and visual consistency will guide evaluation across undergraduate and postgraduate teaching. The project will produce a renewed teaching framework, a practical workflow toolkit for AI assisted visual production, and a dissemination plan to support sustainable integration of AI imaging in creative media education.