Artificial intelligence in education is evolving from passive chatbots to proactive AI agents capable of initiation and goal-directed interactions. While offering opportunities for personalised learning, this shift risks undermining learner agency and cognitive effort. This paper reviews six pedagogical principles-prior knowledge activation, collaborative learning, problem-based learning, formative assessment, scaffolding, and metacognition-through the lens of agentic AI. We discuss the tension between automation and learning, proposing design recommendations that prioritise intentional friction, dynamic scaffolding, human-in-the-loop oversight, and considered AI utilisation to ensure AI supports rather than supplants human learning.

翻译：教育中的人工智能正从被动式聊天机器人演变为具备主动性和目标导向交互能力的智能体。尽管这种转变为实现个性化学习提供了机遇，但同时也可能削弱学习者的自主性和认知投入。本文通过智能体人工智能的视角，审视了六项教学原则——先前知识激活、协作学习、问题导向学习、形成性评估、支架式教学和元认知。我们探讨了自动化与学习之间的张力，并提出以有意摩擦、动态支架、人在回路监督和审慎AI应用为核心的设计建议，以确保人工智能促进而非取代人类学习。