@inproceedings{stiborska-etal-2025-syntactic,
    title = "Syntactic Complexity in {L}2 Reading: A Comparison of Adapted and Original {C}zech Texts",
    author = "Stiborsk{\'a}, {\v{Z}}aneta  and
      Nogolov{\'a}, Michaela  and
      Chen, Xinying  and
      Kub{\'a}t, Miroslav",
    editor = "Chen, Xinying  and
      Wang, Yaqin",
    booktitle = "Proceedings of the Third Workshop on Quantitative Syntax (QUASY, SyntaxFest 2025)",
    month = aug,
    year = "2025",
    address = "Ljubljana, Slovenia",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/mtsummit-25-ingestion/2025.quasy-1.7/",
    pages = "47--55",
    ISBN = "979-8-89176-293-0",
    abstract = "This corpus-based study explores the syntactic complexity of adapted Czech texts designed for learners of Czech as a second language (L2). It investigates how syntactic complexity varies according to learner proficiency levels (A2, B1, B2) as defined by the Common European Framework of Reference for Languages (CEFR) and how these adapted texts differ from their original versions. Quantitative analyses using metrics such as average sentence length (ASL), average clause length (ACL), mean dependency distance (MDD), and mean hierarchical distance (MHD) demonstrate clear systematic simplifications in adapted texts at lower proficiency levels. At A2 and B1 levels, adapted texts were found to be significantly less syntactically complex compared to their original counterparts. However, these differences diminished notably at the B2 proficiency level, indicating a gradual alignment of adapted texts with native-level syntactic complexity as learner proficiency increased. These results underscore the importance of careful syntactic calibration in creating educational materials for language learners, highlighting implications for curriculum design, instructional methodologies, and materials development. The findings offer valuable insights for language educators and textbook authors aiming to optimize reading materials to support language acquisition effectively"
}