GenAI让二语写作更流畅，却抹去了作者的文化表达特色。
The Cost of Perfect English: Pragmatic Flattening and the Erasure of Authorial Voice in L2 Writing Supported by GenAI
- 用大模型优化中文学生作文，发现语法改对了但语气变单一
- 模型删掉协商性表达，把讨论变成单向陈述；对观点谨慎度处理不一
- 适合关注AI写作工具如何影响语言多样性的教育研究者
将生成式AI（GenAI）融入语言学习为第二语言（L2）写作者提供了文本优化的强大工具。然而，追求母语级流利度往往牺牲了社会语用多样性。本研究探讨‘语用同质化’现象——即文化偏好礼貌和作者立场的系统性消失，对来自ICNALE语料库的中国B2水平大学生议论文进行对比分析。原始文本通过四个主流大模型的API在零温度设置下进行润色以保证可复现性。结果揭示了‘语义保留悖论’中的‘维度分歧’：虽然模型纠正了词汇语法错误并保留了命题意义，但在社会语用层面干预出现分化。在互动维度上，所有模型均大幅削弱对话参与标记，使协商性论述转变为单向断言；而在认识论立场维度上，模型表现出架构差异：部分模型激进地清除认识论标记，另一些则强化试探性措辞作为脱离语境的算法谨慎。这证实，尽管GenAI提升了准确性，却系统性地将二语作者独特的修辞身份替换为同质化的盎格鲁-美国范式。我们主张未来教学应超越纠错，倡导批判性人工智能素养，帮助多语写作者在利用GenAI提升语言的同时，保护社会语用多样性和修辞自主权。
原文摘要 · Abstract (English)
The integration of Generative AI (GenAI) into language learning offers second language (L2) writers powerful tools for text optimization. However, pursuing native-like fluency often sacrifices sociopragmatic diversity. Investigating "pragmatic flattening" - the systematic erasure of culturally preferred politeness and authorial stance - this study conducts a comparative analysis of argumentative essays by Chinese B2-level university students from the ICNALE corpus. The original texts were polished via the APIs of four leading Large Language Models at a zero-temperature setting for reproducibility. Findings reveal a nuanced "dimensional divergence" within the Semantic Preservation Paradox. While models corrected lexicogrammatical errors and retained propositional meaning, sociopragmatic interventions were bifurcated. In the interactive dimension, all models showed a drastic collapse of dialogic engagement markers, turning negotiated discourse into monologic assertions. Conversely, in the epistemic stance dimension, models showed architecture-based variability: some aggressively scrubbed epistemic markers, while others reinforced tentative hedging as decontextualized algorithmic caution. This confirms that while GenAI enhances accuracy, it systematically overwrites L2 writers' unique rhetorical identities into a homogenized Anglo-American paradigm. We argue that future instruction must move beyond error correction, advocating for Critical AI Literacy to empower multilingual writers to use GenAI for linguistic enhancement while safeguarding sociopragmatic diversity and rhetorical agency.
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