逻辑语义功能视域下Kimi ai写作优化效果研究

A Study on the Writing Optimization Effect of Kimi ai from the Perspective of Logical Semantic Function

摘要: 本研究基于系统功能语言学的逻辑语义功能理论，采用语篇对比分析与参与式跟踪调查相结合的方法，对陕西省某高校英语专业大二学生的写作样本进行研究，旨在评估Kimi ai在不同水平写作样本优化中的实际效能。结果显示，Kimi ai在低至中等水平文本优化方面表现显著，通过扩展意义和句式变换提升了文本质量；然而，在高水平写作样本优化中，尽管能够通过复合连词植入和句式重组实现表层句法改良，但在扩展关系句式比例和整体文本评分上未达到显著差异。此外，其显性连接策略与写作者的隐性连贯机制存在冲突，且受限于命题框架的突破能力，未能有效提升深层逻辑连贯性和概念层级重组，从而揭示了当前AI工具在语篇认知增强方面的功能性局限。这一研究为二语写作教学及GenAI写作优化功能的开发提供了实证支持。

Abstract: This study, grounded in the logical semantic function theory of systemic functional linguistics, employs a combined approach of discourse contrastive analysis and participatory tracking surveys to investigate the writing samples of second-year English majors at a university in Shaanxi Province. The aim is to evaluate the practical effectiveness of Kimi AI in optimizing writing samples across different proficiency levels. The results show that Kimi AI significantly enhances the quality of low- to mid-level texts through meaning expansion and syntactic transformation. However, in high-level writing optimization, while Kimi AI can improve surface syntax through the insertion of complex conjunctions and sentence restructuring, it fails to achieve significant differences in the proportion of extended relational sentences and overall text scores. Furthermore, its explicit connection strategies conflict with the implicit coherence mechanisms of writers, and its limited ability to break through propositional frameworks prevents effective enhancement of deep logical coherence and conceptual reorganization. These findings reveal the functional limitations of current AI tools in enhancing discourse cognition and provide empirical support for second language writing instruction and the development of GenAI writing optimization functions.