L2 English speaking syntactic complexity: Data preprocessing issues, reliability of automated analysis, and the effects of proficiency, L1 background, and topic,The Modern Language Journal

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L2 English speaking syntactic complexity: Data preprocessing issues, reliability of automated analysis, and the effects of proficiency, L1 background, and topic
The Modern Language Journal ( IF 4.7 ) Pub Date : 2024-02-07 , DOI: 10.1111/modl.12907
Minjin Kim ₁ , Xiaofei Lu ₁

Affiliation

The effects of learner- and task-related variables on second language (L2) writing syntactic complexity (SC) have been extensively investigated. However, previous research has rarely assessed the reliability of computational tools for analyzing the SC of L2 spoken production, and we know less about the effects of such variables on L2 speaking SC. Using data from the International Corpus Network of Asian Learners of English, this study explores data preprocessing issues for preparing L2 English speech samples for automated SC analysis, evaluates the reliability of L2 Syntactic Complexity Analyzer on preprocessed L2 English speech samples, and examines the effects of proficiency, first language (L1) background, and topic on L2 speaking SC. Our manual analysis of 30 random speech samples identified several issues that can be addressed through preprocessing to improve the accuracy of automated SC analysis. Results from multiple linear mixed-effects models revealed significant effects of proficiency, L1 background, and topic on the mean length of clause, the number of complex AS-units per AS-unit, and the number of dependent clauses and complex nominals per clause in L2 learners’ spoken production. Our findings have useful implications for L2 speaking pedagogy and assessment as well as future L2 speaking SC research.

中文翻译：

L2 英语语法复杂性：数据预处理问题、自动分析的可靠性以及熟练程度、L1 背景和主题的影响

学习者和任务相关变量对第二语言（L2）写作句法复杂性（SC）的影响已被广泛研究。然而，以往的研究很少评估用于分析二语口语生产的 SC 的计算工具的可靠性，并且我们对这些变量对二语口语 SC 的影响知之甚少。本研究利用亚洲英语学习者国际语料库网络的数据，探讨了准备用于自动 SC 分析的 L2 英语语音样本的数据预处理问题，评估了 L2 句法复杂性分析器对预处理的 L2 英语语音样本的可靠性，并检验了熟练程度、第一语言 (L1) 背景以及 L2 口语 SC 的主题。我们对 30 个随机语音样本进行手动分析，发现了几个可以通过预处理解决的问题，以提高自动 SC 分析的准确性。多个线性混合效应模型的结果揭示了熟练程度、L1背景和主题对子句的平均长度、每个AS单元的复杂AS单元的数量以及每个子句的从属子句和复杂名词的数量的显着影响。 L2 学习者的口语表达。我们的研究结果对第二语言口语教学和评估以及未来第二语言口语 SC 研究具有有益的意义。

更新日期：2024-02-07

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