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Corpus Analysis on Students' Counter and Support Arguments in Argumentative Writing

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Title: Corpus Analysis on Students' Counter and Support Arguments in Argumentative Writing
Language: English
Authors: McCarthy, Philip M. (ORCID 0000-0001-5869-3709), Kaddoura, Noor W., Al-Harthy, Ayah, Thomas, Anuja M., Duran, Nicholas D., Ahmed, Khawlah
Source: Pegem Journal of Education and Instruction. 2022 12(1):256-271.
Availability: Pegem Academy Publishing and Educational Guidance Services TLC. Mesrutiyet Caddesi, No: 45, Ankara, Kizilay 06420, Turkey. e-mail: editor@pegegog.net; Web site: http://www.pegegog.net/
Peer Reviewed: Y
Page Count: 16
Publication Date: 2022
Document Type: Journal Articles
Reports - Research
Education Level: Higher Education
Postsecondary Education
Descriptors: Computational Linguistics, Connected Discourse, Discourse Analysis, Readability, Classification, Language Usage, Language Processing, Cognitive Ability, Persuasive Discourse, College Students, Essays, Writing Evaluation, Computer Software, Advanced Students, Writing Instruction, Grades (Scholastic), Structural Analysis (Linguistics)
ISSN: 2146-0655
Abstract: This study analyzes the linguistic features of counter-arguments and support arguments using two computational linguistic tools: Coh-Metrix and Gramulator. The research question investigates whether counter-argument paragraphs and support paragraphs are different in terms of their linguistic features. To conduct this study, a corpus of 78 argumentative papers was collected. The paragraphs in the papers were categorized in terms of their function. The categories included functions of Support, Counter-argument, Expostulation, Counter-argument and Expostulation, Background, and Other. The paragraphs were analyzed for their readability and writing quality through Coh-Metrix. With the exception of the measure of Deep Cohesion, the Coh-Metrix results suggest minimal differences in terms of readability and writing quality between counter-argument and support paragraphs. Following the Coh-Metrix analysis, both counter-argument and support corpora were analyzed through Gramulator for their lexical features. The Gramulator results suggest the presence of causal language and fixed expressions in counterarguments, as well as some tagged language in support arguments.
Abstractor: As Provided
Entry Date: 2022
Accession Number: EJ1329805
Database: ERIC
FullText Text:
  Availability: 0
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  Data: Corpus Analysis on Students' Counter and Support Arguments in Argumentative Writing
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  Data: <searchLink fieldCode="SO" term="%22Pegem+Journal+of+Education+and+Instruction%22"><i>Pegem Journal of Education and Instruction</i></searchLink>. 2022 12(1):256-271.
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  Data: Pegem Academy Publishing and Educational Guidance Services TLC. Mesrutiyet Caddesi, No: 45, Ankara, Kizilay 06420, Turkey. e-mail: editor@pegegog.net; Web site: http://www.pegegog.net/
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  Data: This study analyzes the linguistic features of counter-arguments and support arguments using two computational linguistic tools: Coh-Metrix and Gramulator. The research question investigates whether counter-argument paragraphs and support paragraphs are different in terms of their linguistic features. To conduct this study, a corpus of 78 argumentative papers was collected. The paragraphs in the papers were categorized in terms of their function. The categories included functions of Support, Counter-argument, Expostulation, Counter-argument and Expostulation, Background, and Other. The paragraphs were analyzed for their readability and writing quality through Coh-Metrix. With the exception of the measure of Deep Cohesion, the Coh-Metrix results suggest minimal differences in terms of readability and writing quality between counter-argument and support paragraphs. Following the Coh-Metrix analysis, both counter-argument and support corpora were analyzed through Gramulator for their lexical features. The Gramulator results suggest the presence of causal language and fixed expressions in counterarguments, as well as some tagged language in support arguments.
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      – Text: English
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        PageCount: 16
        StartPage: 256
    Subjects:
      – SubjectFull: Computational Linguistics
        Type: general
      – SubjectFull: Connected Discourse
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      – SubjectFull: Discourse Analysis
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      – SubjectFull: Readability
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      – SubjectFull: Language Usage
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      – SubjectFull: Language Processing
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      – SubjectFull: Persuasive Discourse
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      – SubjectFull: College Students
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      – SubjectFull: Essays
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      – SubjectFull: Writing Evaluation
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      – SubjectFull: Structural Analysis (Linguistics)
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      – TitleFull: Corpus Analysis on Students' Counter and Support Arguments in Argumentative Writing
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