Sketching out Lexico‑Grammatical Patterns in Promotional Discourse Moves with Data Driven Learning
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F23%3AX8JXYLKF" target="_blank" >RIV/00216208:11320/23:X8JXYLKF - isvavai.cz</a>
Result on the web
<a href="https://journals.openedition.org/apliut/10904" target="_blank" >https://journals.openedition.org/apliut/10904</a>
DOI - Digital Object Identifier
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Alternative languages
Result language
angličtina
Original language name
Sketching out Lexico‑Grammatical Patterns in Promotional Discourse Moves with Data Driven Learning
Original language description
"This paper contributes to data-driven learning (DDL) literature about English for specific purposes. We examine the potential of DDL, via Sketch Engine, for learning and using persuasive language in a task-based approach to promotional discourse. This study took place in the applied foreign languages department of a French university (Langues étrangères appliquées - LEA). The LEA students’ written productions demonstrate mastery of lexico‑grammatical patterns for persuasive language encountered through Sketch Engine DDL activities. Students were generally favourable to the approach and considered it useful for developing their professional language skills."
Czech name
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Czech description
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Classification
Type
J<sub>ost</sub> - Miscellaneous article in a specialist periodical
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
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Continuities
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Others
Publication year
2023
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
"Recherche et pratiques pédagogiques en langues. Cahiers de l'Apliut"
ISSN
2257-5405
e-ISSN
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Volume of the periodical
42
Issue of the periodical within the volume
2
Country of publishing house
US - UNITED STATES
Number of pages
20
Pages from-to
1-20
UT code for WoS article
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EID of the result in the Scopus database
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