Modeling relationships among large-grained, fine-grained absolute syntactic complexity and assessed L2 writing quality: An SEM approach

The current study investigated the relationships among large-grained and fine-grained aspects of absolute syntactic complexity (SC) and expert-assessed writing quality of 446 argumentative writing samples of college-level Chinese EFL learners. Computational indices tapping into large-grained and fine-grained aspects of absolute SC were computed by TAASSC and L2SCA. Drawing upon rigorous SEM analyses, this paper demonstrated the utility of computational indices that tap into absolute SC. Overall, the measurements of absolute SC accounted for 42 % of the variance in human-judged overall writing scores. The results revealed that (1) noun phrase (NP) complexity was the underlying cause that determined trained raters’ judgement on argumentative writing quality; (2) among traditional large-grained indices, MLC, CN/C, and CN/T, were dependable metrics in representing SC and predicting writing quality; (3) among fine-grained indices, prepositional phrases and relative clauses as noun modifiers were prominent in representing NP complexity; (4) relative clause and adjectival modifiers had unique and complementary effects to large-grained NP complexity in affording explanations for human judgement; (5) the use of prepositions in NP was the most prominent contributor to the increase of large-grained NP complexity among the noun phrase modifiers in this specific corpus. Situated in previous research, the results provide an opportunity to evaluate L2 writing within the theoretical framework of absolute syntactic complexity.