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This systematic review evaluates research on the quality of WCF generated by ChatGPT and by humans, and examines how ChatGPT-based WCF can support higher-education writing instruction. The analysis covers 23 studies from 18 peer-reviewed journals (2023–2024), identifying strengths and weaknesses, including extensive descriptive feedback as well as risks of system fatigue, inaccuracies, limited human nuance, and prompt dependence.",{"@graph":69,"@context":122},[70,84,105],{"@type":71,"itemListElement":72},"BreadcrumbList",[73,77,79,82],{"item":74,"name":75,"@type":76,"position":8},"https://docshare.wps.com","Home","ListItem",{"item":78,"name":9,"@type":76,"position":14},"https://docshare.wps.com/document/",{"item":80,"name":40,"@type":76,"position":81},"https://docshare.wps.com/document/research-report/",3,{"item":83,"name":65,"@type":76,"position":19},"https://docshare.wps.com/document/chatgpts-and-humans-written-corrective-feedback-in-eflesl-writing-a-systematic-review/582257/",{"url":83,"name":65,"@type":85,"image":86,"author":91,"headline":65,"publisher":94,"fileFormat":97,"inLanguage":63,"description":67,"dateModified":98,"datePublished":99,"encodingFormat":97,"isAccessibleForFree":100,"interactionStatistic":101},"DigitalDocument",{"url":87,"@type":88,"width":89,"height":90},"https://docshare.wps.com/thumbnails/chatgpts-and-humans-written-corrective-feedback-in-eflesl-writing-a-systematic-review/582257.png","ImageObject",300,407,{"name":92,"@type":93},"Ophelia","Person",{"url":74,"name":95,"@type":96},"DocShare","Organization","application/pdf","2026-11-15","2026-10-15",true,{"@type":102,"interactionType":103,"userInteractionCount":34},"InteractionCounter",{"@type":104},"ViewAction",{"@type":106,"mainEntity":107},"FAQPage",[108,114,118],{"name":109,"@type":110,"acceptedAnswer":111},"What is the goal of this systematic review?","Question",{"text":112,"@type":113},"The review examines existing studies on the quality of written corrective feedback (WCF) produced by ChatGPT and by humans, and explores how ChatGPT-generated WCF can support human feedback in higher-education EFL/ESL writing contexts.","Answer",{"name":115,"@type":110,"acceptedAnswer":116},"How was the evidence gathered for the review?",{"text":117,"@type":113},"The researcher analyzed 23 studies published in 18 peer-reviewed journals from 2023–2024, then compared the results regarding ChatGPT-generated and human-generated WCF.",{"name":119,"@type":110,"acceptedAnswer":120},"What strengths and limitations are reported for ChatGPT and for human feedback?",{"text":121,"@type":113},"ChatGPT can review multiple aspects of writing and provide extensive descriptive feedback, but it may suffer system fatigue affecting quality and can generate inaccurate feedback lacking human nuances. Humans may address aspects ChatGPT misses, but feedback can involve subjective judgment and may be unclear.","https://schema.org",{"og:url":83,"og:type":124,"og:title":65,"og:site_name":95,"og:description":67},"article",{"robots":126,"canonical":83},"index,follow",{"doc_id":128,"site_id":62},582257,1792161867,{"code":4,"msg":5,"data":131},{"doc_id":128,"user_id":132,"nickname":92,"user_avatar":133,"doc_module":4,"category_id":39,"category_name":40,"doc_title":65,"doc_description":67,"doc_content":134,"file_id":135,"file_url":136,"file_type":137,"file_size":138,"view_count":34,"is_deleted":4,"is_public":8,"is_downloadable":8,"audit_status":8,"page_count":139,"language":140,"language_code":63,"site_id":62,"html_lang":63,"table_of_contents":141,"faqs":142,"seo_title":143,"seo_description":67,"update_tm":144,"read_time":145,"preview_page_count":4},7971461741311,"https://ap-avatar.wpscdn.com/avatar/74000253aff267980c6?x-image-process=image/resize,m_fixed,w_180,h_180&k=1779345379180704826","Turkish Online Journal of Distance Education-TOJDE January 2026 ISSN 1302-6488 Volume: 27 Number: 1 Article: 3  \nCHATGPT’S AND HUMANS’WRITTEN CORRECTIVE FEEDBACK INEFL/ESL WRITING: A SYSTEMATIC REVIEW  \nDr. Yustinus Calvin Gai MALI  \nORCID: 0000-0001-9075-783X  \nMaster’s Program in English Language Education Universitas Kristen Satya Wacana  \nSalatiga, INDONESIA  \nReceived: 09/12/2024 Accepted: 21/04/2025  \nABSTRACT  \nWritten corrective feedback (WCF) is critical in EFL/ESL writing classrooms. This study aims to review existing research studies on the quality ofWCF generated by ChatGPT and humans and to examine how WCF generated by ChatGPT can support WCF that humans give to students’ written work in higher education EFL/ESL writing contexts. To meet these goals, the researcher examined 23 studies published in 18 peer-reviewed journals from 2023-2024. The analysis results highlighted potential strengths and weaknesses ofWCF generated by ChatGPT and humans. WCF generated by ChatGPT could review various aspects of writing and provide extensive descriptive feedback, yet it sometimes might experience system fatigue that affects the WCF quality. ChatGPT could also provide inaccurate WCF, give WCF that lacked human nuances, and were greatly influenced by how prompts were presented to it. Meanwhile, humans could provide aspects ofWCF not accounted for ChatGPT, but their WCF might involve subjective judgment and be unclear. With these findings in mind, the researcher identified three phases of how ChatGPT can work harmoniously with humans to provide quality WCF for students in writing classrooms. Those phases were making various efforts to enhance WCF generated by ChatGPT in students’ writing in support of the feedback provided by lecturers, enhancing students’ in-depth understanding that not all ChatGPT feedback is accurate, and combining ChatGPT-based WCF, specifically on earlier drafts of students’ writing. Pedagogical implications, which highlighted the essence of working synergistically with ChatGPT and mastering prompts to generate the most helpful WCF, for EFL/ESL lecturers in writing classrooms who wish to support their feedback with ChatGPT to provide quality WCF to their students’ written work werepresented. The researcher then proposed recommendations for future systematic review studies, expanding the research contexts, the scope of reviewed materials, and the research method of the reviewed articles, to address gaps and expand on the insights presented in this study.  \nKeywords: ChatGPT, EFL, ESL, written corrective feedback, writing classrooms.  \nINTRODUCTION  \nIn higher education contexts, particularly in English language education programs, writing skills are crucial in students’ language development and achievement across professional domains (Abas & Abd Aziz, 2018; Hang, 2023; Mali, 2022; Song & Song, 2023) . Proficiency in writing can also ensure the success of their studies, as many programs require the students to pass some writing courses, write a research proposal, complete a thesis, and eventually publish the thesis in an academic journal (Harmawan et al., 2023; Mali, 2023; Purwanti & Kastuhandani, 2023; Ramadhanti et al., 2023) . Yet, at the same time, writing might be one of the most challenging skills to master when learning English as a Second Language (ESL) or English asa Foreign Language (EFL) given the long, non-linear, and recursive writing processes of planning, drafting, revising, and editing (see Laksmi, 2006; Mali & Salsbury, 2021), and a range of linguistics abilities of grammatical rules, syntactic expressions, and lexical knowledge as well as a range of planning strategies for ideas organization, rhetoric, and styles that students have to master (Aydin & Yildiz, 2014; Chandra & Yuyun, 2018) .  \nTo address the challenges of mastering writing skills, regular, constructive, and timely written corrective feedback (WCF) from lecturers to their students’ work in EFL/ESL writing classes is critical (Ban","cbCail3ijIBB7DaW","https://ap.wps.com/l/cbCail3ijIBB7DaW","pdf",421938,18,"English","# Abstract\n# Introduction\n## Challenges in EFL/ESL Writing and the Role of WCF\n## AI as an Alternative: ChatGPT\n# Method (Systematic Review Scope)\n# Findings (Strengths and Weaknesses of ChatGPT vs. Humans)\n## Three Phases for Synergistic Use\n# Pedagogical Implications\n# Recommendations for Future Research","[{\"question\":\"What is the goal of this systematic review?\",\"answer\":\"The review examines existing studies on the quality of written corrective feedback (WCF) produced by ChatGPT and by humans, and explores how ChatGPT-generated WCF can support human feedback in higher-education EFL/ESL writing contexts.\"},{\"question\":\"How was the evidence gathered for the review?\",\"answer\":\"The researcher analyzed 23 studies published in 18 peer-reviewed journals from 2023–2024, then compared the results regarding ChatGPT-generated and human-generated WCF.\"},{\"question\":\"What strengths and limitations are reported for ChatGPT and for human feedback?\",\"answer\":\"ChatGPT can review multiple aspects of writing and provide extensive descriptive feedback, but it may suffer system fatigue affecting quality and can generate inaccurate feedback lacking human nuances. Humans may address aspects ChatGPT misses, but feedback can involve subjective judgment and may be unclear.\"}]","CHATGPT’S AND HUMANS’ WRITTEN CORRECTIVE FEEDBACK IN EFL/ESL WRITING: A SYSTEMATIC REVIEW | PDF",1792042905,45]