Generative-AI–Driven Intelligent Socratic Dialogue: A Theoretical Analysis and Model Construction

Imagine a classroom where every student gets a personal tutor trained in the Socratic art—not to give answers, but to ask just the right questions. That vision, however, has long run into a practical wall: how do you scale a method built on live, adaptive dialogue to hundreds or thousands of learners? In this article, we explore a generative-AI model designed to do exactly that. Instead of reducing Socratic teaching to a scripted Q&A, we treat the AI as a “midwife” for thinking—one that operates from deliberate ignorance, provides cognitive scaffolding, and dynamically shifts initiative back to the learner. Technically, the system works through a three-layer “Goal–Agent–Conversation” architecture, turning broad instructional aims into living, personalized dialogues. Learners move through a kind of cognitive spiral: they externalize their assumptions, run into contradictions, reflect critically, and gradually rebuild understanding. What we’re really trying to address here is an old tension in education—the tug‑of‑war between standardization and genuine personalization. Could this approach ease that friction? Looking ahead, we see the beginnings of a data‑informed learning model that doesn’t just deliver knowledge but cultivates the skill of thinking itself. We also sketch where the work goes from here—from technical fine‑tuning and new use cases to the ethical questions that will inevitably follow.