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Evaluation of the Feedback Impact Generated by Generative Artificial Intelligence on Writing Ability in Descriptive Texts

Language Circle: Journal of Language and Literature · Vol. 20 No. 1 (2025) · pp. 428–439

DOI
10.15294/lc.v19i2.21540
ISSN
2460-853X, 1858-0157
Published
2025-05-01
Publisher
Universitas Negeri Semarang
Language
eng

Abstract

The ability to write clear and descriptive texts is an essential skill in a variety of academic and professional contexts. From designing compelling narrative essays in literature class to crafting clear and concise reports in the workplace, effective descriptive writing allows individuals to communicate their ideas and engage audiences with vivid imagination and sensory detail. However, the development of these skills often requires intensive practice and constructive feedback. Traditional writing instruction often relies on human feedback from teachers and lecturers. Therefore, this study aims to compare the feedback ability generated by generative artificial intelligence on the ability to write in descriptive texts. This study uses a quantitative research approach with quasi-experimental design. This study involved 58 students of Civil Engineering Vocational Education Program. The non-equivalent control group design was used to compare the results of the experimental class and the control class. Based on the results of data analysis using the Wilcoxon test, there were 29 positive ranks, this means that there were 29 students who experienced an increase in scores at the time of the posttest with an increase of 18.38% from the pre-test score. The average Gain Score = 0.4933 with a maximum value of 0.7272 and a minimum score = 0.28. It can be concluded that the use of generative artificial intelligence in providing feedback on students' descriptive texts is a medium or quite effective.

Keywords

Collaboration network of the authors

40 authors · 114 co-authorship links · showing the 40 most connected

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  • University of Brawijaya
  • Affiliation unknown
  • Different organisations
  • Same organisation
  • Affiliation unknown
  • Thicker line = more joint articles · bigger circle = more articles
Show as table
Co-authorOrganisationJoint articles
Bambang SugiyartoAffiliation unknown5
Nurul YuhanafiaAffiliation unknown5
Nur QudusAffiliation unknown3
TuginoAffiliation unknown3
Sri HandayaniUniversity of Brawijaya3
Tite JuliantineAffiliation unknown2
Aris WidodoAffiliation unknown2
Muhammad MahfudAffiliation unknown1
Nurisul UbbatAffiliation unknown1
MuhajirAffiliation unknown1
Ahmad HatipAffiliation unknown1
Harianingsih HarianingsihAffiliation unknown1
Savira Rinda ErlianaAffiliation unknown1
Isnina Noor UbayAffiliation unknown1
Indra Sakti PangestuAffiliation unknown1
Mohammad Pujo SiswoyoAffiliation unknown1
Yudhidwi NusantaraAffiliation unknown1
Kurnia Eka WijayantiAffiliation unknown1
CarsiwanAffiliation unknown1
Rizky SoemantriAffiliation unknown1
Aditia Putra MunggaranAffiliation unknown1
Alya DaviyatiAffiliation unknown1
Jajat Darajat Kusumah NegaraAffiliation unknown1
Yudy HendrayanaAffiliation unknown1
SyahviraAffiliation unknown1
Amung Ma’munAffiliation unknown1
Shofie VegaAffiliation unknown1
ArdianikAffiliation unknown1
Nailul IzzahAffiliation unknown1
Sunyoto Hadi PrajitnoAffiliation unknown1
agus gumilarAffiliation unknown1
Adang SuhermanAffiliation unknown1
NuryadiAffiliation unknown1
Nunni NoerginaAffiliation unknown1
Bagus HendriyantoAffiliation unknown1
Dito Rizky Nur SaputraAffiliation unknown1

Affiliations come from OpenAlex; journal OAI-PMH metadata carries none. Authors without an OpenAlex ID are matched by name, which can merge or split people.

Metadata source: OAI-PMH (metadata jurnal) https://journal.unnes.ac.id/journals/LC/oai, first harvested 5 Nov 2026, last seen 8 Nov 2026.
Original metadata (oai_dc) 
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	<dc:title xml:lang="en">Evaluation of the Feedback Impact Generated by Generative Artificial Intelligence on Writing Ability in Descriptive Texts</dc:title>
	<dc:creator xml:lang="en">Virgiawan Adi Kristianto</dc:creator>
	<dc:creator xml:lang="en">Sucipto</dc:creator>
	<dc:creator xml:lang="en">Sri, Handayani</dc:creator>
	<dc:creator xml:lang="en">Nurul, Yuhanafia</dc:creator>
	<dc:subject xml:lang="en">writing</dc:subject>
	<dc:subject xml:lang="en">artificial intelligence</dc:subject>
	<dc:subject xml:lang="en">English for specific purposes</dc:subject>
	<dc:subject xml:lang="en">feedback</dc:subject>
	<dc:subject xml:lang="en">evaluation</dc:subject>
	<dc:description xml:lang="en">The ability to write clear and descriptive texts is an essential skill in a variety of academic and professional contexts. From designing compelling narrative essays in literature class to crafting clear and concise reports in the workplace, effective descriptive writing allows individuals to communicate their ideas and engage audiences with vivid imagination and sensory detail. However, the development of these skills often requires intensive practice and constructive feedback. Traditional writing instruction often relies on human feedback from teachers and lecturers. Therefore, this study aims to compare the feedback ability generated by generative artificial intelligence on the ability to write in descriptive texts. This study uses a quantitative research approach with quasi-experimental design. This study involved 58 students of Civil Engineering Vocational Education Program. The non-equivalent control group design was used to compare the results of the experimental class and the control class. Based on the results of data analysis using the Wilcoxon test, there were 29 positive ranks, this means that there were 29 students who experienced an increase in scores at the time of the posttest with an increase of 18.38% from the pre-test score. The average Gain Score = 0.4933 with a maximum value of 0.7272 and a minimum score = 0.28. It can be concluded that the use of generative artificial intelligence in providing feedback on students' descriptive texts is a medium or quite effective.</dc:description>
	<dc:publisher xml:lang="en">Universitas Negeri Semarang</dc:publisher>
	<dc:date>2025-05-01</dc:date>
	<dc:type>info:eu-repo/semantics/article</dc:type>
	<dc:type>info:eu-repo/semantics/publishedVersion</dc:type>
	<dc:type xml:lang="en">Peer-reviewed Article</dc:type>
	<dc:format>application/pdf</dc:format>
	<dc:identifier>https://journal.unnes.ac.id/journals/LC/article/view/21540</dc:identifier>
	<dc:identifier>10.15294/lc.v19i2.21540</dc:identifier>
	<dc:source xml:lang="en">Language Circle: Journal of Language and Literature; Vol. 20 No. 1 (2025): April 2025 Regular Issue; 428 - 439</dc:source>
	<dc:source>2460-853X</dc:source>
	<dc:source>1858-0157</dc:source>
	<dc:language>eng</dc:language>
	<dc:relation>https://journal.unnes.ac.id/journals/LC/article/view/21540/3847</dc:relation>
	<dc:rights xml:lang="en">Copyright (c) 2025 Language Circle: Journal of Language and Literature</dc:rights>
</oai_dc:dc>