Supplementary file 1_The cumulative effects of AI-generated feedback on syntactic development in high school EFL writers: a longitudinal quasi-experimental study.docx

Introduction<p>While AI-generated writing feedback research has flourished, most studies prioritizeholistic quality over syntactic competence and rely on static pre-post comparisons, neglecting dynamic multi-round evolution.</p>Methods<p>This 35-week quasi-experiment examined cumulative associations between exposure to supplementary AI-generated feedback components and syntactic development among 69 Chinese high school EFL learners (Group A: n = 33 receiving automated AI scoring, official model compositions, and supplementary AI-generated feedback components; Group B: n = 36 receiving automated AI scoring and official model compositions).

Piecewise regression, cognitive load scales, and qualitative triangulation were used across 10 timed continuation tasks.</p>Results<p>The study described non-linear trajectories: an initial adaptation decline followed by faster gains. Among the 10 target error types, only Part-of-Speech errors showed a statistically significant reduction after FDR correction; other error categories exhibited only suggestive trends that did not remain robust after multiple comparison adjustment.