构造(python库)
语言序列复杂性
计算机科学
从属关系(语言学)
论证(复杂分析)
语言学
探索性因素分析
学术写作
代表(政治)
自然语言处理
人工智能
心理学
数学教育
程序设计语言
哲学
化学
机器学习
法学
政治
结构方程建模
生物化学
政治学
出处
期刊:Cambridge University Press eBooks
[Cambridge University Press]
日期:2024-12-05
卷期号:: 92-106
标识
DOI:10.1017/9781009425407.011
摘要
Grammatical complexity has been considered as an important research construct closely related to second language (L2) writing development. Although theoretical models were developed to demonstrate what grammatical complexity is, few studies have been conducted to analyze how this construct is represented from an empirical perspective. This chapter presents a data-driven investigation on the representation of grammatical complexity with an exploratory factor analysis (EFA). The investigation is based on (1) a corpus of scientific research reports written by Hong Kong students in an English Medium Instruction (EMI) scientific English course, and (2) an EFA, which is a statistical approach to uncover an underlying structure of a phenomenon, which fits this research purpose well. A corpus has been built with the science writing from EMI undergraduate students in Hong Kong. After corpus cleaning, Second Language Syntactic Complexity Analyzer – a software – was applied to output the values of fourteen effective measures of grammatical complexity for running the EFA in SPSS, and a step-by-step instruction was described in the chapter. The final model includes three latent factors: clausal (subordination) complexity, nominal phrasal complexity, and coordinate phrasal complexity. This EFA model is generally consistent with the argument of investigating grammatical complexity as a multidimensional construct (Biber et al., 2011; Norris & Ortega, 2009). In the end, we highlighted the research and pedagogical implications that readers should pay attention to when the EFA is applied in other EMI contexts in the future.
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