开源工具自动分析英文写作中语法结构使用，助力二语能力评估
ASC analyzer: A Python package for measuring argument structure construction usage in English texts
- 基于规则与统计结合的方法自动标注语法结构
- 提取50个指标反映结构多样性与使用频率
- 适合语言学研究者和二语写作评估场景
语法结构构造（ASCs）为第二语言（L2）能力分析提供了理论基础，但缺乏可扩展、系统化的测量工具。本文提出 ASC analyzer，一个公开可用的 Python 工具包，可自动标注 ASC 并计算 50 个指标，涵盖多样性、比例、频率及与动词词元的关联强度。通过双变量和多变量分析，验证了基于 ASC 的指标与 L2 写作得分之间的关联性，展示了其在语言能力评估中的实用性。
原文摘要 · Abstract (English)
Argument structure constructions (ASCs) offer a theoretically grounded lens for analyzing second language (L2) proficiency, yet scalable and systematic tools for measuring their usage remain limited. This paper introduces the ASC analyzer, a publicly available Python package designed to address this gap. The analyzer automatically tags ASCs and computes 50 indices that capture diversity, proportion, frequency, and ASC-verb lemma association strength. To demonstrate its utility, we conduct both bivariate and multivariate analyses that examine the relationship between ASC-based indices and L2 writing scores.
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