ChatGPT‐Generated and Human‐Simplified Texts for L2 English Readers: A Lexical and Syntactic Comparison Across Prompting Strategies

ABSTRACT

This study compared human‐adapted and ChatGPT‐simplified texts across three prompting strategies (general, example‐based, and instructive) using 51 authentic English‐language newspaper articles. Lexical complexity (density, diversity, and sophistication) and syntactic complexity (five length‐ and subordination‐based indices) were analyzed using established computational tools and linear mixed‐effects models. Although all simplified versions reduced syntactic complexity relative to the source texts, ChatGPT‐simplified texts exhibited significantly higher lexical density and more aggressive syntactic reduction than human‐adapted texts across all measures. Differences among the three prompting strategies were modest, though the instructive prompt consistently produced the syntactically simplest outputs. These findings suggest that ChatGPT and human simplification follow distinct linguistic profiles and that human oversight remains important when using AI‐generated texts for instruction.