Keywords
politeness strategies
AI-generated writing
human writing
Uzbek EFL learners
pragmatics
second-language writing
discourse
How to Cite
Abstract
Generative AI has quietly become one more source of English- language text in the world, and that raises a question worth asking: how does what a machine writes actually compare with what a language learner writes? Most of the attention so far has gone to grammar, vocabulary, and overall writing quality. Much less has gone to pragmatics - the layer of writing where a text manages relationships, signals stance, and organizes an argument for a reader. This gap is especially noticeable for Uzbek EFL learners, whose writing has rarely been examined from this angle. The present study compares pragmatic markers and politeness strategies in human- and AI- generated English argumentative writing, using a corpus-based design that sets learner- written texts against AI-generated responses to the same prompts. The analysis looks at discourse-organizing markers, stance and interpersonal markers, and politeness strategies, drawing mainly on Brown and Levinson's framework for the latter. The proposed dataset includes 60 comparable texts - 30 written by learners and 30 generated by AI. Markers are located through frequency searches and then checked by hand in context, since frequency alone cannot settle what a form is doing in a sentence; politeness strategies are classified by their interpersonal function rather than by surface wording. The illustrative analysis points to a pattern: AI-generated texts tend to carry more explicit discourse-organizing devices and lean more on negative-politeness resources, while learner texts show more individual variation and a more context- sensitive use of solidarity language. The broader argument is that pragmatic appropriateness is not the same thing as grammatical correctness, and it is not guaranteed just because a text contains recognizable discourse markers. For Uzbek EFL learners, knowing why and when to use a given marker or politeness strategy matters as much as knowing the form itself. The study sits at the intersection of second- language writing, pragmatics, politeness research, and the newer question of how humans and AI systems produce text differently.References
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