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Demonstrates a framework for enhancing visible pedagogical thinking in human–AI collaborations, indicating potential for teacher innovation.
Generative AI (GenAI) challenges traditional technology integration frameworks by introducing agentic systems that actively participate in meaning-making, requiring educators to shift from tool operation to cognitive orchestration. This study introduces the MTA–TPACK Dynamic Collaboration Spiral, a theoretical framework that integrates Meta-Task Awareness (MTA) to explain how static knowledge resources are dynamically activated during human–AI collaboration. We empirically illustrate this framework through a two-phase scientific visualization task concerning typhoon–terrain interactions, utilizing Midjourney for human-led orchestration and GPT-4o for closed-loop refinement. The results demonstrate that successful integration requires translating abstract disciplinary knowledge into precise, AI-intelligible visual constraints rather than relying solely on technical prompting skills. Furthermore, we document how evaluation practices evolve from simple error correction to structured, AI-assisted diagnosis. The resulting visual artifacts embody Visible Pedagogical Thinking (VPT)—externalized cognitive constructs that make expert reasoning inspectable and reusable. By foregrounding evaluation-centered task design, this study provides a transferable, theoretically grounded account of how human–AI collaboration can remain pedagogically meaningful. The model contributes to sustainable pedagogical innovation by offering a roadmap for strengthening teachers’ long-term epistemic agency in AI-mediated design environments.
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Chen et al. (2026) studied this question.
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