中国电化教育

大模型强大的语言生成能力,将对语文教育产生实质性的影响,并促使我们重新确立“以语言运用为中心”的教学理念。该文基于认知语言学、大语言模型的学习机制、神经元连接的可塑性等多学科理论视角,构建了AI辅助的语言运用教学模型。该模型以“语言输入-认知加工-语言输出-智能反馈”的动态闭环为核心,按照语言运用的规律,深度嵌入人工智能,赋能实现精准、高效、促进思维发展的语言实践:AI赋能精准输入,提供个性化与高度情境化的可理解语料; AI支持深度认知加工,促进语义整合与结构化建构; AI驱动的情境化输出,强化意义建构式表达与交际实践; AI协同的智能调节与反馈,实现语言表达与认知结构的持续优化;最终通过三重联动的螺旋式循环机制,推动语言能力内化、思维深度发展与综合素养的协同提升,为语文教育中合理使用AI提供了系统化的理论框架与可操作的实践路径。

The robust language generation capabilities of large language models(LLMs) will exert a substantial impact on Chinese language education and impel us to re-establish the teaching philosophy centered on language application. Drawing on a multidisciplinary theoretical framework encompassing cognitive linguistics, the learning mechanisms of LLMs, and the plasticity of neuronal connections, this paper constructs an AI-assisted language application teaching model. At its core lies a dynamic closed-loop process consisting of language input, cognitive processing, language output, and intelligent feedback. By deeply integrating artificial intelligence in accordance with the inherent laws of language application, this model empowers targeted, efficient language practice that fosters thinking development: AI-enabled precision input delivers personalized and highly contextualized comprehensible linguistic materials; AI-supported in-depth cognitive processing facilitates semantic integration and structured knowledge construction; AI-driven contextualized output reinforces meaning-making expression and communicative practice; AI-collaborated intelligent regulation and feedback enables continuous optimization of both language expression and cognitive structures. Ultimately, through a triple-interactive spiral cycle mechanism, the model promotes the internalization of language proficiency, the in-depth development of thinking, and the coordinated enhancement of comprehensive literacy. It thereby provides a systematic theoretical framework and actionable practical pathways for the rational integration of AI in Chinese language education.