AI Chatbot as a Revision Aid in Second Language Writing: From Error Correction to Lexical Sophistication
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| Title: | AI Chatbot as a Revision Aid in Second Language Writing: From Error Correction to Lexical Sophistication |
|---|---|
| Language: | English |
| Authors: | Yuah V. Chon (ORCID |
| Source: | Journal of Computer Assisted Learning. 2026 42(3). |
| Availability: | Wiley. Available from: John Wiley & Sons, Inc. 111 River Street, Hoboken, NJ 07030. Tel: 800-835-6770; e-mail: cs-journals@wiley.com; Web site: https://www.wiley.com/en-us |
| Peer Reviewed: | Y |
| Page Count: | 20 |
| Publication Date: | 2026 |
| Document Type: | Journal Articles Reports - Research |
| Education Level: | Higher Education Postsecondary Education |
| Descriptors: | Artificial Intelligence, Technology Uses in Education, Computer Mediated Communication, Second Language Learning, Writing (Composition), Revision (Written Composition), Error Correction, Lexicology, Editing, Feedback (Response), College Students, English (Second Language), Foreign Countries, Preservice Teachers, Writing Evaluation, Language Usage, Text Structure, Writing Improvement |
| Geographic Terms: | South Korea (Seoul) |
| DOI: | 10.1002/jcal.70259 |
| ISSN: | 0266-4909 1365-2729 |
| Abstract: | Background: The use of recent artificial intelligence (AI) chatbots, such as chat generative pretrained transformer (ChatGPT), in second language (L2) writing may face criticism for potentially promoting plagiarism and raising ethical concerns. However, such tools can effectively provide guided suggestions for improving outlines, content, and organisation. Additionally, EditGPT, an extension that tracks changes made by ChatGPT, provides immediate, direct corrective feedback, thereby enhancing L2 learners' control over their writing process. Objectives: The aim of this study was to compare the quality of L2 learners' writing (LW), ChatGPT-proofread writing (PW), and learners' ChatGPT-supported revisions (RW) by analysing human raters' evaluations, assessing linguistic complexity, and identifying error types. Methods: A total of 40 university students majoring in English education, all of whom were English as a foreign language (EFL) learners and pre-service teachers, participated in this study. Based on significant differences in their TOEIC scores, they were divided into two groups. The secondary-school pre-service teachers were classified as skilled learners, while the elementary-school pre-service teachers were identified as less skilled learners. Participants completed a guided writing task supported by ChatGPT for idea generation and essay revision. They interacted directly with ChatGPT using standard prompts for brainstorming and outlining and received automated feedback on editing and proofreading through the EditGPT extension. Results: When LW and RW were compared, human raters found significant improvements in language use but not in content and organisation. The revisions demonstrated greater linguistic complexity, including increased use of academic words, improved lexical sophistication, and more varied sentence structures. Regarding language errors, 86.17% of the errors in LW were successfully rectified. However, a closer breakdown revealed that certain error types--particularly word choice (38.9% remaining) and sentence structure (35.4% remaining)--remained relatively unresolved. Addressing these lingering errors in both PW and RW often required judgements of contextual appropriateness, especially when attempting to preserve the learners' intended meanings and nuanced expressions. As a result, the overall error resolution rate dropped to 77.02% in RW. Conclusions: The structured AI-mediated revision environment was associated with short-term improvements in the linguistic quality of L2 writing within a controlled session. These effects reflect product-level changes and cannot be attributed to individual writing process components. While AI-supported revision reduced many surface-level errors, limitations remained for context-sensitive language use. Further longitudinal research is needed to determine whether these changes support sustained writing development. |
| Abstractor: | As Provided |
| Entry Date: | 2026 |
| Accession Number: | EJ1506909 |
| Database: | ERIC |
| FullText | Text: Availability: 0 |
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| Header | DbId: eric DbLabel: ERIC An: EJ1506909 AccessLevel: 3 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: AI Chatbot as a Revision Aid in Second Language Writing: From Error Correction to Lexical Sophistication – Name: Language Label: Language Group: Lang Data: English – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Yuah+V%2E+Chon%22">Yuah V. Chon</searchLink> (ORCID <externalLink term="https://orcid.org/0000-0002-4155-5892">0000-0002-4155-5892</externalLink>)<br /><searchLink fieldCode="AR" term="%22Dongkwang+Shin%22">Dongkwang Shin</searchLink> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="SO" term="%22Journal+of+Computer+Assisted+Learning%22"><i>Journal of Computer Assisted Learning</i></searchLink>. 2026 42(3). – Name: Avail Label: Availability Group: Avail Data: Wiley. Available from: John Wiley & Sons, Inc. 111 River Street, Hoboken, NJ 07030. Tel: 800-835-6770; e-mail: cs-journals@wiley.com; Web site: https://www.wiley.com/en-us – Name: PeerReviewed Label: Peer Reviewed Group: SrcInfo Data: Y – Name: Pages Label: Page Count Group: Src Data: 20 – Name: DatePubCY Label: Publication Date Group: Date Data: 2026 – Name: TypeDocument Label: Document Type Group: TypDoc Data: Journal Articles<br />Reports - Research – Name: Audience Label: Education Level Group: Audnce Data: <searchLink fieldCode="EL" term="%22Higher+Education%22">Higher Education</searchLink><br /><searchLink fieldCode="EL" term="%22Postsecondary+Education%22">Postsecondary Education</searchLink> – Name: Subject Label: Descriptors Group: Su Data: <searchLink fieldCode="DE" term="%22Artificial+Intelligence%22">Artificial Intelligence</searchLink><br /><searchLink fieldCode="DE" term="%22Technology+Uses+in+Education%22">Technology Uses in Education</searchLink><br /><searchLink fieldCode="DE" term="%22Computer+Mediated+Communication%22">Computer Mediated Communication</searchLink><br /><searchLink fieldCode="DE" term="%22Second+Language+Learning%22">Second Language Learning</searchLink><br /><searchLink fieldCode="DE" term="%22Writing+%28Composition%29%22">Writing (Composition)</searchLink><br /><searchLink fieldCode="DE" term="%22Revision+%28Written+Composition%29%22">Revision (Written Composition)</searchLink><br /><searchLink fieldCode="DE" term="%22Error+Correction%22">Error Correction</searchLink><br /><searchLink fieldCode="DE" term="%22Lexicology%22">Lexicology</searchLink><br /><searchLink fieldCode="DE" term="%22Editing%22">Editing</searchLink><br /><searchLink fieldCode="DE" term="%22Feedback+%28Response%29%22">Feedback (Response)</searchLink><br /><searchLink fieldCode="DE" term="%22College+Students%22">College Students</searchLink><br /><searchLink fieldCode="DE" term="%22English+%28Second+Language%29%22">English (Second Language)</searchLink><br /><searchLink fieldCode="DE" term="%22Foreign+Countries%22">Foreign Countries</searchLink><br /><searchLink fieldCode="DE" term="%22Preservice+Teachers%22">Preservice Teachers</searchLink><br /><searchLink fieldCode="DE" term="%22Writing+Evaluation%22">Writing Evaluation</searchLink><br /><searchLink fieldCode="DE" term="%22Language+Usage%22">Language Usage</searchLink><br /><searchLink fieldCode="DE" term="%22Text+Structure%22">Text Structure</searchLink><br /><searchLink fieldCode="DE" term="%22Writing+Improvement%22">Writing Improvement</searchLink> – Name: Subject Label: Geographic Terms Group: Su Data: <searchLink fieldCode="DE" term="%22South+Korea+%28Seoul%29%22">South Korea (Seoul)</searchLink> – Name: DOI Label: DOI Group: ID Data: 10.1002/jcal.70259 – Name: ISSN Label: ISSN Group: ISSN Data: 0266-4909<br />1365-2729 – Name: Abstract Label: Abstract Group: Ab Data: Background: The use of recent artificial intelligence (AI) chatbots, such as chat generative pretrained transformer (ChatGPT), in second language (L2) writing may face criticism for potentially promoting plagiarism and raising ethical concerns. However, such tools can effectively provide guided suggestions for improving outlines, content, and organisation. Additionally, EditGPT, an extension that tracks changes made by ChatGPT, provides immediate, direct corrective feedback, thereby enhancing L2 learners' control over their writing process. Objectives: The aim of this study was to compare the quality of L2 learners' writing (LW), ChatGPT-proofread writing (PW), and learners' ChatGPT-supported revisions (RW) by analysing human raters' evaluations, assessing linguistic complexity, and identifying error types. Methods: A total of 40 university students majoring in English education, all of whom were English as a foreign language (EFL) learners and pre-service teachers, participated in this study. Based on significant differences in their TOEIC scores, they were divided into two groups. The secondary-school pre-service teachers were classified as skilled learners, while the elementary-school pre-service teachers were identified as less skilled learners. Participants completed a guided writing task supported by ChatGPT for idea generation and essay revision. They interacted directly with ChatGPT using standard prompts for brainstorming and outlining and received automated feedback on editing and proofreading through the EditGPT extension. Results: When LW and RW were compared, human raters found significant improvements in language use but not in content and organisation. The revisions demonstrated greater linguistic complexity, including increased use of academic words, improved lexical sophistication, and more varied sentence structures. Regarding language errors, 86.17% of the errors in LW were successfully rectified. However, a closer breakdown revealed that certain error types--particularly word choice (38.9% remaining) and sentence structure (35.4% remaining)--remained relatively unresolved. Addressing these lingering errors in both PW and RW often required judgements of contextual appropriateness, especially when attempting to preserve the learners' intended meanings and nuanced expressions. As a result, the overall error resolution rate dropped to 77.02% in RW. Conclusions: The structured AI-mediated revision environment was associated with short-term improvements in the linguistic quality of L2 writing within a controlled session. These effects reflect product-level changes and cannot be attributed to individual writing process components. While AI-supported revision reduced many surface-level errors, limitations remained for context-sensitive language use. Further longitudinal research is needed to determine whether these changes support sustained writing development. – Name: AbstractInfo Label: Abstractor Group: Ab Data: As Provided – Name: DateEntry Label: Entry Date Group: Date Data: 2026 – Name: AN Label: Accession Number Group: ID Data: EJ1506909 |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1002/jcal.70259 Languages: – Text: English PhysicalDescription: Pagination: PageCount: 20 Subjects: – SubjectFull: Artificial Intelligence Type: general – SubjectFull: Technology Uses in Education Type: general – SubjectFull: Computer Mediated Communication Type: general – SubjectFull: Second Language Learning Type: general – SubjectFull: Writing (Composition) Type: general – SubjectFull: Revision (Written Composition) Type: general – SubjectFull: Error Correction Type: general – SubjectFull: Lexicology Type: general – SubjectFull: Editing Type: general – SubjectFull: Feedback (Response) Type: general – SubjectFull: College Students Type: general – SubjectFull: English (Second Language) Type: general – SubjectFull: Foreign Countries Type: general – SubjectFull: Preservice Teachers Type: general – SubjectFull: Writing Evaluation Type: general – SubjectFull: Language Usage Type: general – SubjectFull: Text Structure Type: general – SubjectFull: Writing Improvement Type: general – SubjectFull: South Korea (Seoul) Type: general Titles: – TitleFull: AI Chatbot as a Revision Aid in Second Language Writing: From Error Correction to Lexical Sophistication Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Yuah V. Chon – PersonEntity: Name: NameFull: Dongkwang Shin IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 06 Type: published Y: 2026 Identifiers: – Type: issn-print Value: 0266-4909 – Type: issn-electronic Value: 1365-2729 Numbering: – Type: volume Value: 42 – Type: issue Value: 3 Titles: – TitleFull: Journal of Computer Assisted Learning Type: main |
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