Given the lack of computational tools available for assessing second language (L2) production in Korean, this study introduces a novel automated tool called the Korean Syntactic Complexity Analyzer (KOSCA) for measuring syntactic complexity in L2 Korean production. As an open-source graphic user interface (GUI) developed in Python, KOSCA provides seven indices of syntactic complexity, including traditional and Korean-specific ones. Its validity was tested by investigating whether the syntactic complexity indices measured by it in L2 written and spoken production could explain the variability of L2 Korean learners’ proficiency. The results of mixed-effects regression analyses showed that all seven indices significantly accounted for learner proficiency in Korean. Subsequent stepwise multiple regression analyses revealed that the syntactic complexity indices explained 56.0% of the total variance in proficiency for the written data and 54.4% for the spoken data. These findings underscore the validity of the syntactic complexity indices measured by KOSCA as reliable indicators of L2 Korean proficiency, which can serve as a valuable resource for researchers and educators in the field of L2 Korean learning and assessment.

中文翻译：

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韩语句法复杂性分析器 (KOSCA)：用于分析第二语言生成中句法复杂性的 NLP 应用程序

鉴于缺乏可用于评估韩语第二语言 (L2) 生成的计算工具，本研究引入了一种称为韩语句法复杂性分析器 (KOSCA) 的新型自动化工具，用于测量 L2 韩语生成中的句法复杂性。作为用 Python 开发的开源图形用户界面 (GUI)，KOSCA 提供了七个句法复杂性指数，包括传统的和韩语特有的指数。通过调查其在二语书面和口语输出中测量的句法复杂性指数是否可以解释二语韩语学习者熟练程度的变异性来测试其有效性。混合效应回归分析的结果表明，所有七个指数都显着影响了学习者的韩语熟练程度。随后的逐步多元回归分析显示，句法复杂性指数解释了书面数据熟练程度总方差的 56.0% 和口语数据熟练程度总方差的 54.4%。这些发现强调了 KOSCA 测量的句法复杂性指数作为第二韩语熟练程度的可靠指标的有效性，可以作为第二韩语学习和评估领域的研究人员和教育工作者的宝贵资源。