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Using automated indices of cohesion to explore the growth of cohesive features in L2 writing

Bibliographic Data

ID7802048
AuthorsMahmoud Abdi Tabari (0000-0002-8022-5415, Department of English , 6851 University of Nevada, Reno , Reno , NV , USA, corresponding author), Mark D Johnson (0000-0003-0015-1514, Department of English , 3627 East Carolina University , Greenville , NC , USA), Jianwu Gao (0000-0001-8322-4808, English Language and Literature , 12379 Capital Normal University , Beijing , China)
Year2025
Volume63
Issue3
Pages2169-2200
Publication date2025-09-25
Peer ReviewedYes
Open AccessNo
TypeARTICLE
VenueIRAL - International Review of Applied Linguistics in Language Teaching (JOURNAL)
Journal identifiersISSN: 0019-042X • E-ISSN: 1613-4141
PublisherWalter de Gruyter GmbH (PUBLISHER • DE)
DOI10.1515/iral-2023-0185
OpenAlexW4392235406
LanguageEN
Citations received3
References cited47

While the use of cohesive devices has received considerable attention in L2 writing research, scant attention has been devoted to exploring local, global, and textual cohesive features across two genres at different time points using indices generated by the computational tool for automatic analysis of cohesion (TAACO). Inspired by this gap, this study attempted to: (a) identify TAACO indices that are predictive of human ratings of essay organization, (b) investigate which of the identified TAACO indices differ between narrative and argumentative genres, and (c) explore which of the identified TAACO indices might change over time. To achieve these purposes, 270 narrative and argumentative essays were collected from 45 L2 writers in counterbalanced order at six different time points. The results of mixed-effects modeling revealed textual cohesive devices to be significant predictors of human ratings of essay organization regardless of genre and indicated sustained development in the use of textual cohesive devices over time. This study has important implications for L2 writing assessment including the potential to enhance assessment practices by incorporating computational tools like TAACO. The findings emphasize the importance of considering textual cohesive devices as significant predictors of essay organization, regardless of genre

Argumentative · Cohesion (chemistry) · Linguistics · Narrative · Computer Science · Discourse Analysis in Language Studies · Psychology · Second Language Acquisition and Learning · Writing and Handwriting Education

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Unique citing works3
Citations per year3
Citation span2025 - 2026 (2)
Citation velocitycurrent
Highly citedNo
Citation typesNeutral: 3

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