A Study on the Intervention and Optimization of Generative AI in Mitigating Negative Semantic Transfer in English Writing

Rui-Chen Feng （ Shaanxi University of International Trade & Commerce, Xianyang City, Shaanxi Province, 712046, China ）

Abstract

This study focuses on the intervention and optimization of generative AI in addressing semantic negative transfer in English writing. It first elaborates on the theoretical foundations and research progress of AI-assisted second language writing, followed by an analysis of the types, characteristics, and native language roots of semantic negative transfer in English writing. Subsequently, the intervention effects of generative AI are examined in terms of its identification capabilities, the quality of revision suggestions, its impact on students' revision behaviors and writing skill development, as well as student attitudes. Finally, strategies and recommendations are proposed from three perspectives: optimizing the use of AI tools, refining teaching processes, and cultivating students' AI literacy, aiming to promote the intelligent development of second language writing instruction.

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