Author(s)

Zhou Zhou

Affiliation(s)

School of Foreign Studies, Xi’an University, Xi’an 710065, Shaanxi, China.

Corresponding Author

Zhou Zhou

ABSTRACT

Addressing the core challenges of "homogenized teaching models" and "delayed feedback" inherent in traditional K-12 Chinese writing instruction, this study aims to construct a new data-driven paradigm for personalized writing instruction. Employing a mixed-methods research design, the study utilizes quasi-experimental methods and triangulation strategies to verify the effectiveness of digital tools throughout the entire writing process.First, the study constructs a student-centered, four-dimensional personalized learning strategy model comprising "diagnosis, intervention, feedback, and assessment," alongside a functional mapping system for digital tools. Second, empirical analysis based on pre-test, post-test, and delayed-test data reveals that this strategy significantly enhances students' writing performance, language construction capabilities, and metacognitive levels, while demonstrating differential gains among students with varying proficiency levels. Finally, the study explores the synergistic mechanism between AI-based intelligent correction and peer review.This study not only confirms the efficacy of digital tools in resolving the conflict between individual student needs and large-scale instruction but also provides a theoretical basis and practical pathways for resource allocation, teacher professional development, and the establishment of ethical norms within the context of the digital transformation of education.

KEYWORDS

Digital writing instruction; Personalized learning strategies; Data-driven; Core literacy; Education; K-12 Chinese language

CITE THIS PAPER

Zhou Zhou. Digital empowerment in k-12 Chinese writing instruction: research on personalized learning strategies and practice models. World Journal of Educational Studies. 2025, 3(8): 37-52. DOI: https://doi.org/10.61784/wjes3108.

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