Exploring the Impact of Linguistic Complexity on Writing Quality in High School Students’ English Letter Writing: A Quantitative Linguistic Approach

This study employs a quantitative linguistic approach to investigate the relationship between linguistic complexity and English letter writing quality by Chinese high school students. Analyzing 170 valid letter-writing samples, we extracted 18 linguistic features through computational tools and manual annotation, then examined their associations with human ratings using Pearson correlation analysis and stepwise multiple regression modeling. Results indicate that (1) lexical features (lexical density, low-frequency word usage, verb sophistication, and noun variation) significantly predict writing quality; (2) syntactic features (sentence length, coordinate phrases, complex nominal phrases, and non-restrictive attributive clauses) correlate positively with writing quality, with non-restrictive clauses showing the strongest correlation ( r = 0.776); and (3) a regression model combining lexical sophistication, coordinate structures, nominalization, and noun variation explains 63.4% of writing quality variance ( R ² = 0.634), with lexical variation as the strongest predictor ( β = 0.521). The findings suggest that effective English writing instruction should systematically integrate lexical complexity and syntactic complexity training, emphasizing advanced structures like complex nominal phrases and non-restrictive clauses for higher proficiency levels. This study provides empirical support for differentiated writing pedagogy and automated assessment systems.