A Comparative Study on the Enhancement of Lexical Richness in Students’ English Argumentative Writing by Different Large Language Models

This study investigates the impact of different large language models (LLMs) on lexical richness in student argumentative writing. By comparing the outputs of LLMs like GPT-3 and LaMDA, the research aims to identify specific linguistic features and stylistic variations introduced by each model. The study analyzes the extent to which LLMs enhance lexical density, lexical diversity and lexical sophistication in student writing, considering factors like authenticity, originality, and student learning. Quantitative and qualitative analyses are employed to assess lexical richness scores and identify stylistic patterns. The findings provide insights into the potential benefits and drawbacks of using LLMs for enhancing lexical richness in student writing, offering practical recommendations for educators on their appropriate integration into writing instruction.