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Article published In:
Revista Española de Lingüística Aplicada/Spanish Journal of Applied Linguistics
Vol. 36:2 (2023) ► pp.436–466

Constructional complexity as a predictor of Korean EFL learners’ writing proficiency

ORCID logo | Yonsei University
ORCID logo | Palacký University Olomouc
ORCID logo | Gyeongin National University of Education
Based on usage-based constructionist approaches to language development, this study investigates the validity of constructional complexity as a predictor of writing proficiency of Korean EFL learners. We analyzed argumentative essays produced by Korean EFL learners and compared a prediction model that uses English argument structure constructions with a conventional T-unit-based model. We first tested the predictive power of a discriminant function model with argument structure constructions as predictors for assessing writing proficiency of lower- and higher-level learners. We then compared the construction-based model to another model that included T-unit measures as predictors. The results validated the contribution of argument structure constructions for predicting L2 writing proficiency: The construction-based model yielded higher prediction accuracy than the T-unit-based model did, confirming that constructional complexity is closely aligned with writing proficiency. These findings demonstrate the significance of a construction-based model as a reliable tool for diagnosing EFL learners’ writing proficiency.
Keywords: second language writing, discriminant function analysis, constructionist approach, T-unit, Korean EFL students
Article outline
  • 1.Introduction
  • 2.Syntactic complexity measures in L2 writing
  • 3.Constructional approaches to language development
  • 4.L2 acquisition of English ASCs
  • 5.Present study
    • 5.1Research question 1: Constructional model
      • 5.1.1Method
        • 5.1.1.1Data collection
        • 5.1.1.2Variable selection and coding
      • 5.1.2Results and discussion
        • 5.1.2.1Multivariate analysis of variance
        • 5.1.2.2Discriminant function analysis
    • 5.2Research question 2: Testing model validity
      • 5.2.1Method
      • 5.2.2Results and discussion
        • 5.2.2.1Multivariate analysis of variance
        • 5.2.2.2Discriminant function analysis
        • 5.2.2.3Comparison of the models
  • 6.General discussion and conclusion
  • References
Published online: 10 May 2023
DOI logo
https://doi.org/10.1075/resla.20066.kim
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