2025 年 5 巻 1 号 p. Inv-p003
Generative AI (GenAI) is reshaping how learners and educators engage in content generation, task completion, and feedback. While prompting remains central today, this paper anticipates a shift toward a post-prompting era in which AI agents become more proactive, contextual, and multimodal. In this landscape, the challenge lies not in crafting prompts but in shaping learning trajectories with AI as a co-agent. We propose two key constructs: Meta-Task Awareness (MTA), the ability to discern deeper goals, structures, and strategies behind tasks; and the Chain of Learning (CoL), which reconceptualizes learning as an iterative, generative-reflective trajectory rather than a sequence of isolated tasks. For educators, we extend this to the Chain of Learning Design and Evaluation (CoLDE), which highlights how GenAI can support the design of interconnected learning tasks and the evaluation of student outputs to inform future design. CoL focuses on learner agency in navigating with AI support, whereas CoLDE focuses on teacher agency in orchestrating and improving learning through AI-assisted design and feedback loops. These constructs offer a foundation for human-AI co-agency in learning and teaching. Preparing for this shift demands technical fluency, conceptual clarity, pedagogical imagination, and systemic design foresight.
