A Corpus-Linguistics-Based Comparison of AI-Aided Writing and Students' Writing

This study investigates the linguistic and stylistic differences between AI-aided writing and students' writing through a corpus-linguistics-based analysis. Two corpora were constructed, each consisting of 20 essays. The corpora were analyzed using AntConc 4.2.0 and compared against the Brown and Frown reference corpora to provide a benchmark for modern American English. Quantitative indicators such as type-token ratio (TTR), word length, sentence length, high-frequency words, and entropy were calculated to uncover distinctive linguistic features and patterns. The results reveal notable differences between the two corpora. AI-aided writing employs longer words compared to students’ writing, indicating a more sophisticated vocabulary in AI-generated texts. In contrast, students’ writing exhibits greater lexical variety and more syntactically flexible sentences. These findings suggest that AI-aided writing aligns more closely with the lexical sophistication of standard American English, as represented by the Brown and Frown corpora, while students’ writing reflects a simpler and more conversational style. This study provides insights into the linguistic characteristics of AI-aided writing and its implications for education, language learning, and the evolving role of AI in writing practices.