COMPARING DISCOURSE PATTERNS IN AI-ASSISTED AND L2 LEARNER TEXTS
DOI:
https://doi.org/10.55640/Keywords:
AI-assisted writing; discourse patterns; L2 academic writing; cohesion; discourse markers; syntactic complexityAbstract
This study investigates differences in discourse patterns between AI-assisted texts and texts produced independently by second language (L2) learners. As artificial intelligence tools increasingly influence academic writing practices, concerns have emerged regarding how AI assistance reshapes discourse organization, cohesion, and rhetorical structure. This research adopts a quasi-experimental mixed-methods design to compare discourse-level features in AI-assisted and non-AI-assisted L2 academic texts.The dataset consists of 120 academic essays written by undergraduate L2 English learners over an eight-week academic writing course. Sixty essays were revised with AI assistance, while sixty were revised using traditional self-editing without AI support. Quantitative discourse measures—including mean length of T-unit, clausal density, discourse marker frequency, and cohesion index—were analyzed using independent-samples t-tests. Qualitative discourse analysis was conducted to examine rhetorical organization and coherence patterns.
The results demonstrate statistically significant differences between the two groups. AI-assisted texts exhibited higher structural complexity, increased use of discourse markers, and greater surface-level cohesion. However, L2 learner texts showed stronger rhetorical consistency and contextual appropriateness. These findings suggest that while AI assistance enhances formal discourse features, it may also introduce formulaic patterns. The study concludes that AI tools can support discourse development when integrated with pedagogical guidance, rather than used as autonomous writing agents.
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