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Noun‐Phrase Complexity Measures in Chinese and Their Relationship to L2 Chinese Writing Quality

A Comparison with Topic–Comment‐Unit‐Based Measures

Dados Bibliográficos

ID21360167
AutoresXiaofei Lu (0000-0003-2365-2581, The Pennsylvania State University Department of Applied Linguistics 234 Sparks Building University Park PA 16802, autor correspondente), Jifeng Wu (0000-0003-3592-1427, Capital Normal University College of International Education 83 West 3rd Ring Road North Beijing 100089 China, autor correspondente)
Ano2022
Volume106
Fascículo1
Páginas267-283
Data de publicação2022-03-01
Peer ReviewedSim
Open AccessSim
TipoARTICLE
PeriódicoModern Language Journal (JOURNAL)
Identificadores do periódicoISSN: 0026-7902 • E-ISSN: 1540-4781
EditoraWiley (PUBLISHER • GB)
DOI10.1111/modl.12766
OpenAlexW4220722971
IdiomaEN
Citações recebidas15
Referências citadas24

This study proposed a set of measures for assessing noun phrase (NP) complexity in second language (L2) Chinese writing and compared the predictive power of these measures for L2 Chinese writing quality to that of a set of syntactic complexity measures based on the topic–comment unit (TC‐unit). Our data consisted of 101 narratives written by beginning–intermediate, intermediate–advanced, and advanced Korean Chinese‐as‐a‐second‐language (CSL) learners and rated by 2 trained CSL teachers. Results showed that the NP complexity measures explained a substantially larger proportion of variance in holistic writing scores than the TC‐unit‐based measures. Our findings confirmed the validity of the NP complexity measures we proposed and the need to attend to phrasal complexity in assessing L2 Chinese writing quality

Data mining · Linguistics · Mathematics education · Measure (data warehouse) · Natural language processing · Noun · Noun phrase · Phrase · Quality (philosophy) · Set (abstract data type) · Unit (ring theory) · Variance (accounting) · Artificial Intelligence · Computer Science · Psychology · Reading and Literacy Development · Second Language Acquisition and Learning · Text Readability and Simplification

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Obras citantes distintas15
Citações por ano7,5
Intervalo de citações2024 - 2026 (3)
Velocidade de citaçãocurrent
Altamente citadoNão
Tipos de citaçãoNeutras: 14
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