The MTA-TPACK Dynamic Collaboration Spiral: Making Pedagogical Thinking Visible in Human–AI Scientific Visualization for Sustainable Teacher Innovation

Generative AI challenges traditional technology integration frameworks by introducing agentic systems that actively participate in meaning-making and representation. Existing TPACK-based extensions have identified new knowledge domains required for AI integration, yet they offer insufficient explanations of how such knowledge is dynamically activated during human–AI collaboration. This study proposes the MTA–TPACK Dynamic Collaboration Spiral, a theoretical framework that integrates Meta-Task Awareness (MTA) with TPACK to explain how static knowledge resources are transformed into visible pedagogical reasoning through iterative human–AI interaction. Within this framework, MTA functions as a dynamic navigation engine that guides experts along a Generate–Evaluate–Refine trajectory, enabling principled orchestration of AI participation while maintaining epistemic responsibility. The framework is illustrated through a two-phase scientific visualization task on typhoon–terrain interactions, using Midjourney and GPT-4o. The results show how disciplinary knowledge must be reformulated as AI-interpretable constraints and how evaluation practices evolve when AI systems participate in closed-loop feedback. The resulting visual artifacts embody what is termed Visible Pedagogical Thinking—externalized cognitive constructs that make expert reasoning inspectable. By foregrounding evaluation-centered task design, this study provides a transferable account of how human–AI collaboration can remain pedagogically meaningful by rendering expert reasoning observable and reusable across iterative generative workflows. In doing so, the model contributes to sustainable pedagogical innovation by strengthening teachers’ long-term epistemic agency in AI-mediated design environments.