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6 - Factor Analysis in Writing Research

Investigating Grammatical Complexity in Science Writing from EMI Students in a Hong Kong University

from Part II - Empirical Chapters (Case Studies)

Published online by Cambridge University Press:  14 December 2024

Samantha M. Curle
Affiliation:
University of Bath
Jack Pun
Affiliation:
City University of Hong Kong
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Summary

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.

Type
Chapter
Information
Researching English Medium Instruction
Quantitative Methods for Students and Researchers
, pp. 92 - 106
Publisher: Cambridge University Press
Print publication year: 2024

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