Innovation in Chinese Writing Teaching Empowered by Digital Intelligence Operational Path, Classroom Practice, and Effectiveness Testing of Human Computer Co Writing Mode
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Abstract
To address major problems in Chinese writing instruction, including insufficient teacher guidance throughout the writing process, delayed personalized feedback, and weak externalization of students’ writing thinking, this study constructs a human-computer collaborative writing teaching model empowered by digital intelligence. A three-level operational path is developed, consisting of collaborative brainstorming, segmented interactive writing, and multidimensional integrated evaluation and revision. Based on an intelligent writing platform, a 16-week classroom practice is conducted, and teaching effectiveness is examined through a quasi-experimental design from three dimensions: writing performance, thinking development, and learning engagement. The experimental results show that the post-test score of the experimental class is significantly higher than that of the control class, reaching 85.45 ± 5.15 compared with 78.18 ± 6.49 (p < 0.001). The adoption rate of AI suggestions reaches 53.12%, and the task completion rate reaches 92.96%. The findings confirm that the model can externalize the writing process, make writing thinking visible and iterative, and provide an operable solution for personalized guidance in large-scale writing teaching.
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