摘要： 人类认知活动蕴含一种与人工智能“大模型”结构功能相似的内在机制——“认知活动大模型”。该机制以高度关联、动态演化的知识单元构成“内核”系统，通过知识调取、关联推理与持续训练驱动认知迭代，是决定人类思维效能与学习质量的关键隐性因素。而长期以来，教育实践中过度侧重标准化知识灌输，忽视了对支撑批判性思维与跨学科整合的“系统提示词”能力的培育。生成式人工智能的技术路径（知识增强、反馈微调等）不仅印证了CALM机制的可行性，更为其研究提供了新范式，揭示了人类智能的深层原理。自觉优化个体CALM的构建与运行，强化知识关联、深度思考与实践验证，是突破现有教育困境、提升思维水平及培养人工智能时代创新型人才的核心路径。

关键词: 认知活动, 大模型, 学习质量, 人类智能

Abstract: Human cognitive activities contain an inherent mechanism similar in structure and function to the “large model” of artificial intelligence, namely the “cognitive activity large model” (CALM). This mechanism consists of highly correlated and dynamically evolving knowledge units that form the core “kernel” system. Its long-term neglect has led to an excessive emphasis on standardized knowledge transmission in educational practice, neglecting the cultivation of the ability to support critical thinking and interdisciplinary integration through “systematic prompts”, resulting in cognitive and educational misconceptions. The technological path of generative artificial intelligence (knowledge augmentation, feedback fine-tuning, etc.) not only confirms the feasibility of the CALM mechanism, but also provides a new paradigm for research, revealing the deep principles of human intelligence. Consciously optimizing the construction and operation of individual CALM, strengthening knowledge connections, deep thinking, and practical verification, is the core path to break through existing educational difficulties, improve thinking levels, and cultivate innovative talents in the era of artificial intelligence.

Key words: cognitive activity, large model, learning quality, human intelligence