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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 result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F25%3ASSVHECP7" target="_blank" >RIV/00216208:11320/25:SSVHECP7 - isvavai.cz</a>

  • Result on the web

    <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85184461744&doi=10.1111%2fmodl.12907&partnerID=40&md5=e642c0c90c12c9d00fe0b80028405a25" target="_blank" >https://www.scopus.com/inward/record.uri?eid=2-s2.0-85184461744&doi=10.1111%2fmodl.12907&partnerID=40&md5=e642c0c90c12c9d00fe0b80028405a25</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1111/modl.12907" target="_blank" >10.1111/modl.12907</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

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

  • Original language description

    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. © 2024 The Authors. The Modern Language Journal published by Wiley Periodicals LLC on behalf of National Federation of Modern Language Teachers Associations, Inc.

  • Czech name

  • Czech description

Classification

  • Type

    J<sub>SC</sub> - Article in a specialist periodical, which is included in the SCOPUS database

  • CEP classification

  • OECD FORD branch

    10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Result continuities

  • Project

  • Continuities

Others

  • Publication year

    2024

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Name of the periodical

    Modern Language Journal

  • ISSN

    0026-7902

  • e-ISSN

  • Volume of the periodical

    108

  • Issue of the periodical within the volume

    1

  • Country of publishing house

    US - UNITED STATES

  • Number of pages

    27

  • Pages from-to

    270-296

  • UT code for WoS article

  • EID of the result in the Scopus database

    2-s2.0-85184461744