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ZENODO
Article . 2025
License: CC BY
Data sources: ZENODO
ZENODO
Article . 2025
License: CC BY
Data sources: Datacite
ZENODO
Article . 2025
License: CC BY
Data sources: Datacite
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Constructing and Practicing a Precision Teaching Model for Business English Writing Course Empowered by AIGC

Authors: Wang Pei1, Gao Yanhua2;

Constructing and Practicing a Precision Teaching Model for Business English Writing Course Empowered by AIGC

Abstract

The advent of Artificial Intelligence Generated Content (AIGC), particularly large language models (LLMs), presents a transformative opportunity for addressing long-standing challenges in Business English Writing instruction. Traditional teaching models often struggle with providing timely, personalized feedback and creating authentic, scalable practice scenarios due to high teacher workload and heterogeneous student proficiency levels. This paper proposes a novel Precision Teaching model empowered by AIGC, designed to overcome these limitations. The model conceptualizes a dynamic teaching process comprising three core stages: AIGC-powered precise diagnostic analysis, AIGC-facilitated personalized learning cycles, and AIGC-assisted multidimensional holistic evaluation. It fundamentally redefines the roles of teachers and students, advocating for a "human-AI synergy" where AIGC handles repetitive tasks like initial drafting, grammar checking, and scenario generation, freeing teachers to focus on higher-order instruction such as critical thinking, strategic communication, and ethical application. A preliminary practice study conducted within an undergraduate Business English program demonstrated the model's efficacy in enhancing students' writing accuracy, genre awareness, and learning motivation. The study also revealed challenges, including prompt engineering proficiency and the need for AI literacy training. The paper concludes that the AIGC-empowered Precision Teaching model offers a viable and innovative pathway for achieving student-centered, data-informed, and practically oriented reform in Business English Writing education, while also highlighting imperative considerations for academic integrity and pedagogical adaptation.

Keywords

AIGC; Business English Writing; Precision Teaching; Teaching Reform; Large Language Models (LLMs); Personalized Learning

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
Green