摘要
针对生成式人工智能引发的信息碎片化对语文深度学习的挑战，提出以人文价值引领、技术工具协同的项目式学习框架。该框架融合建构主义与认知负荷理论，设计“情境锚定—探究整合—批判创造—社会性反思”四阶段螺旋式学习流程，人工智能的角色从情境模拟器、信息组织者向思辨碰撞伙伴动态演进。以福建某中学《虎门销烟》教学实践为例开展的准实验研究显示，参与项目式学习的学生在历史理解深度与批判性思维等维度上的表现显著优于对照组，学生对人工智能工具的接受度和认可度维持在78%至95%的较高区间。此框架的核心创新点在于建立人机协同机制，将碎片化信息有效转化为结构化认知资源，为人工智能时代在语文教育中兼顾技术效率与人文深度探索可行的实践路径。
关键词： 信息碎片化；项目式学习；人机协同；语文深度学习
Abstract
In view of the challenges of information fragmentation caused by generative artificial intelligence to Chinese deep learning, a project-based learning framework guided by humanistic values and coordinated by technical tools is proposed. This framework integrates constructivism and cognitive load theory, and designs a four-stage spiral learning process of "situational anchoring-exploration integration-critical creation-social reflection". The role of artificial intelligence dynamically evolves from situation simulator and information organizer to a speculative collision partner. A quasi-experimental study based on the teaching practice of "Humen Suppression of Opium" in a middle school in Fujian showed that students participating in project-based learning performed significantly better than the control group in dimensions such as depth of historical understanding and critical thinking. Students' acceptance and recognition of artificial intelligence tools remained in the high range of 78% to 95%. The core innovation of this framework is to establish a human-computer collaboration mechanism to effectively transform fragmented information into structured cognitive resources, and explore feasible practical paths for taking into account both technical efficiency and humanistic depth in Chinese education in the era of artificial intelligence.
Key words： Information fragmentation; Project-based learning; Human-computer collaboration; Chinese deep learning
参考文献 References
[1] 中华人民共和国教育部. 中国智慧教育白皮书发布[N/OL]. 人民网, 2025-05-16 [2025-12-04].
http://www.moe.gov.cn/jyb_xwfb/xw_zt/moe_357/2025/2025_zt06/mtbd/202505/t20250516_1190804.html.
[2] 温儒敏. 温儒敏谈人文学科与语文教育如何面对AI:跟进,但不盲目追赶[N/OL]. 腾讯新闻, 2025-09-06 [2025-12-04]. https://news.qq.com/rain/a/20250906A06JXR00.
[3] Vygotsky L S. Mind in society: The development of higher psychological processes[M]. Cambridge: Harvard University Press, 1978:34-54.
[4] Sweller J. Cognitive load during problem solving: Effects on learning[J]. Cognitive Science, 1988, 12(2):257-285.
[5] Stiegler B. For a new critique of political economy[M]. Cambridge: Polity Press, 2010:22-28.
[6] Nussbaum M C. Cultivating humanity: A classical defense of reform in liberal education[M]. Cambridge: Harvard University Press, 1997:8-16.
[7] Kohnke L, Moorhouse B L, Zou D. ChatGPT for language teaching and learning[J]. RELC Journal, 2023, 54(2):537-550.
[8] Liu T, Mantuhac P B. Teacher support and student engagement in the conduct of blended learning instruction for english as a foreign language[J]. Journal of Education and Educational Research, 2024, 11(2):22-31.
[9] Mangold A, Gawer L, Weinhold S, 等. From fragmentation to focus: How AI can assist researchers in academic writing[C]//International Conference on Human-Computer Interaction. Cham: Springer Nature Switzerland, 2025:55-71.
[10] Zhang W, Zou L. Generative artificial intelligence enabling fragmented learning: Status, challenges and optimization strategies[C]//Proceedings of the 2nd Guangdong-Hong Kong-Macao Greater Bay Area Education Digitalization and Computer Science International Conference. 2025:94-99.
[11] 王品芝, 邵钰倩. AI时代,六成受访者认为"走心表达"有助对抗信息碎片化的空虚感[N]. 中国青年报, 2025-08-21(004).
[12] Hongbing Z. The development trends, practical dilemmas and promotion strategies of adults' fragmented learning in the context of big data[J]. Adult Education, 2023, 43(7):6-12.
[13] Xiaowei T, Rui N. On the integration path of teachers' fragmented learning in the digital age: From the perspective of cognitive surplus[J]. China Educational Technology, 2022(2):69-74,97.