Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/117876
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dc.contributorDepartment of English and Communication-
dc.creatorLi, C-
dc.creatorWang, X-
dc.creatorQian, L-
dc.date.accessioned2026-03-05T07:57:13Z-
dc.date.available2026-03-05T07:57:13Z-
dc.identifier.urihttp://hdl.handle.net/10397/117876-
dc.language.isoenen_US
dc.publisherSage Publications, Inc.en_US
dc.rights© The Author(s) 2025en_US
dc.rightsThis article is distributed under the terms of the Creative Commons Attribution 4.0 License (https://creativecommons.org/licenses/by/4.0/) which permits any use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access pages (https://us.sagepub.com/en-us/nam/open-access-at-sage).en_US
dc.rightsThe following publication Li, C., Wang, X., & Qian, L. (2025). Exploring Syntactic Complexity and Text Readability in an ELT Textbook Series for Chinese English Majors. Sage Open, 15(1) is available at https://doi.org/10.1177/21582440251323619.en_US
dc.subjectData miningen_US
dc.subjectELT textbooksen_US
dc.subjectSyntactic complexityen_US
dc.subjectText readabilityen_US
dc.titleExploring syntactic complexity and text readability in an ELT textbook series for Chinese English majorsen_US
dc.typeJournal/Magazine Articleen_US
dc.identifier.volume15-
dc.identifier.issue1-
dc.identifier.doi10.1177/21582440251323619-
dcterms.abstractThe effectiveness of English Language Teaching (ELT) materials significantly influences the learning outcomes of English as a Foreign Language (EFL) learners, positioning these resources as cardinal in the acquisition process. Despite this widely acknowledged significance, there remains a notable gap in research concerning the evaluation of key factors, such as syntactic complexity and text readability, which determine text difficulty. To address this gap, the present study evaluated the syntactic complexity and readability of a series of Intensive Reading textbooks widely used by English majors in China by adopting data mining technologies, including the L2 syntactic complexity analyzer (L2SCA) and six readability indicators. It also aimed to explore the impact of syntactic complexity as a predictor variable on text readability using multiple regression analysis. The results revealed that the selected series of textbooks demonstrated an increasing pattern of syntactic complexity and a decreasing pattern of text readability, indicating the appropriateness of the text difficulty level for this series. It was also found that clause per T-unit (C/T), clause per sentence (C/S), and dependent clauses per clause (DC/C) were the most significant predictors of readability among the 14 indicators of syntactic complexity. The analytical approach, which leverages data-mining technologies for ELT material evaluation, sets a precedent for future research. The insights gained from this study offer valuable implications for the development of ELT materials in China and other similar EFL contexts, helping to optimize learning by providing appropriately challenging content.-
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitationSAGE open, Jan.-Mar. 2025, v. 15, no. 1, https://doi.org/10.1177/21582440251323619-
dcterms.isPartOfSAGE open-
dcterms.issued2025-01-
dc.identifier.scopus2-s2.0-105000784352-
dc.identifier.eissn2158-2440-
dc.description.validate202603 bcch-
dc.description.oaVersion of Recorden_US
dc.identifier.FolderNumberOA_Scopus/WOSen_US
dc.description.fundingSourceOthersen_US
dc.description.fundingTextThe author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: The Humanities and Social Sciences Foundation, Ministry of Education of China (grant number: 22YJA740016), the Key Project of Hubei Provincial Department of Education Philosophy and Social Science Research Fund (No. 21ZD051), and the Teaching and Research Fund of Hubei University of Technology (No. Xiao2022018).en_US
dc.description.pubStatusPublisheden_US
dc.description.oaCategoryCCen_US
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