Grammarly as AI-powered English Writing Assistant: Students' Alternative for Writing English
Open accessAbstract
The presence of ‘Grammarly’ as one of the online grammar checkers as the impact of technology development. This paper aims to reveal an overview of ‘Grammarly’ as an AI-powered English Writing Assistant for EFL students in Writing English. This research applies descriptive qualitative research. Based on the analysis, using Grammarly software shows the performance increased. Before using Grammarly, the performance of the test score is 34 out of 100. After using Grammarly, the performance text score is 77 out of 100. This score shows the quality of writing in this text increased. The performance can be increased based on Grammarly's suggestions in a Premium account. The researcher recommends the students to use Grammarly. Grammarly is a web tool to perform grammar checks well, starting from the spelling of words, sentence structure to standard grammar. Grammarly is free, so it is recommended for students who want to check various documents or articles in English. Grammarly helps check the grammatical rule, the spelling rule in English structure, also correct errors in writing such as punctuation and capitalization. Grammarly runs on an Artificial Intelligence (AI) system, which is built to analyze English sentences relying on a set of rules. Grammarly takes context when showing corrections or suggestions, and inform the students quickly but still precisely. For accuracy, two service options available both free and paid features. Of course, the Grammarly free version still has limitations and in-service features, unlike the paid version (premium) which has full advantages and benefits, many features, and complete.
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Digital Writing Assistants (DWAs) such as Grammarly, WordTune and Perusall use Artificial Intelligence (AI) to improve student writing.
“Digital Writing Assistants (DWAs) such as Grammarly, WordTune and Perusall, use Artificial Intelligence (AI) to improve student writing (Fitria, 2021)”
From Academic Integrity considerations of AI Large Language Models in the post-pandemic era: ChatGPT and beyond (2023) · cites this paper as Fitria, 2021
The Abstract (page not specified) describes Grammarly as an AI-powered writing assistant and reports improved writing performance after its use. The paper supports that part of the claim, but the passages found for WordTune and Perusall do not address either tool, so it does not substantiate the claim about all three. (LLM, conf=0.88)
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Wiboolyasarin, W., Wiboolyasarin, K., Kamonsawad, R., & Jinowat, N. (2024) · English Teaching & Learning · doi:10.1007/s42321-024-00186-9 · Cited by 7 · see citing works
Emails by LLMs: A Comparison of Language in AI-Generated and Human-Written Emails
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Wang, G., Shakibaei, G., & Çakmak, F. (2025) · British Educational Research Journal · doi:10.1002/berj.4190 · Cited by 7 · see citing works
RetractedA mesterséges intelligencia alkalmazása a nyelvtanulásban
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- Authors
- Fitria, T. N.
- Affiliations
- Institut Teknologi Bisnis AAS Indonesia (ID)
- Corresponding author
- Fitria, Tira Nur
- ORCID
- Fitria, Tira Nur
- Venue
- Metathesis: Journal of English Language, Literature, and Teaching
- Publisher
- Universitas Tidar
- Published
- 2021-05-18
- Volume
- 5
- Issue
- 1
- Pages
- 65
- ISSN
- 2580-2712 (ISSN-L)
- 2580-2720
- OpenAlex
- W3163701888
- Cited by
- 221
- References
- 23
- Citations by year
- 2026: 19 · 2025: 73 · 2024: 59 · 2023: 58 · 2022: 9 · 2021: 3
- FWCI
- 29.16
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- Metathesis Journal of English Language Literature and Teaching (publishedVersion, cc-by-sa)
- Topics
- Physical Sciences › Computer Science › Information Systems › English Language Learning and Teaching
- Social Sciences › Arts and Humanities › Language and Linguistics › EFL/ESL Teaching and Learning
- Physical Sciences › Computer Science › Artificial Intelligence › Natural Language Processing Techniques
- Keywords
- Grammarly, EFL writing, English as a foreign language, grammar checking, spelling correction, punctuation correction, writing performance
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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