Yunling Experimental Middle School, Yuncheng, Shanxi, China

Abstract: In recent years, digital teaching of Chinese language in junior high schools has tended to slide towards two extremes. The first is the "technology-showcase" type — VR Peach Blossom Land, animated Red Cliff, AI one-click reading reflections — classes are lively but language practice is hollow at its core. The second is the "question-bank" type — brushing reading comprehension on platforms, generating essay templates, test-data that looks good, yet students cannot revise their own sentences. Writing as a frontline junior high school Chinese teacher in mainland China, this paper proposes the "Slow-motion Annotation + AI Counter-questioning" model: technology does not speak for the student first; rather, it first preserves the "hesitation, misreading, revision, and pause" in reading and writing. AI does not act as a model-essay printer, but only as an "argumentative reader," pressing precisely: "On what grounds do you say this?" "Would someone else think differently?" "Which line of paragraph three is your evidence in?" Using three types of lesson cases — seventh-grade prose, eighth-grade news, and ninth-grade argumentative writing — the paper demonstrates that the digitization of Chinese teaching is not about moving textbooks onto a screen, but about making visible "the process of students wrestling with their own language." The model aligns with the task groups in the Chinese Language Curriculum Standards for Compulsory Education (2022 Edition) — "Literary Reading and Creative Expression," "Practical Reading and Communication," and "Critical Reading and Expression." An ordinary public junior high school in mainland China can implement it with classroom tablets, WeChat voice messages, free large models, and a school-based annotation bank.

Keywords: educational digitalization; junior high school Chinese; slow-motion annotation; AI counter-questioning; process corpus; learning task groups