The DOI matches its Crossref record; 41 of the 41 references it cites were found in a registry or an index.
Cultivating writing skills: the role of ChatGPT as a learning assistant—a case study
Open accessAbstract
Abstract Artificial intelligence (AI) has garnered considerable interest in the field of language education in recent times; however, limited research has focused on the role of AI in the specific context of register knowledge learning during English language writing. This study aims to address this research gap by examining the impact of ChatGPT, an AI-powered chatbot, on the acquisition of register knowledge across various writing tasks. The research design employed a one-case shot pre-experimental design, with 11 voluntary participants selected through convenience sampling. Preliminary results indicate that students found ChatGPT beneficial for acquiring formal register knowledge but perceived it as unnecessary for informal writing. Additionally, the effectiveness of ChatGPT in teaching neutral register was questioned by the participants. This research contributes to the existing literature by shedding new light on the effects of AI-generated chatbots in register learning during the writing process, offering insights into their potential as learning assistants. Further investigation is warranted to explore the broader implications and applications of AI in language learning contexts.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
The cited source doesn’t support the claim as written.
In the citing paper
“Research on writing and language learning constitutes one of the most active areas of inquiry into ChatGPT's classroom use [10].”
From Fluency Illusion: A Review on Influence of ChatGPT in Classroom Settings (2026) · cites this paper as [10]
Checked by a reasoning model — may be wrong.
Experimental — accuracy not yet measuredThe source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“For example, studies examining AI-assisted writing tasks report that students often produce more fluent and well-structured text, while improvements in argument quality or conceptual reasoning remain limited [10][11][12].”
From Fluency Illusion: A Review on Influence of ChatGPT in Classroom Settings (2026) · cites this paper as [10]
Experimental — accuracy not yet measuredThe source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“Surface-level improvement may be mistaken for stronger writing competence [10,39]”
From Fluency Illusion: A Review on Influence of ChatGPT in Classroom Settings (2026) · cites this paper as [10]
Experimental — accuracy not yet measured
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Research Design: Qualitative, Quantitative, and Mixed Methods Approaches
Sloane-Seale, A. (2009) · Canadian Journal of University Continuing Education · doi:10.21225/d54s3d · Cited by 14,328
Bruner, J. (1996) · doi:10.4159/9780674251083 · Cited by 6,231
The Psychology of Learning and Motivation
(2021) · The Psychology of learning and motivation/The psychology of learning and motivation · doi:10.1016/s0079-7421(21)x0002-3 · Cited by 5,082
BAİDOO-ANU, D., & OWUSU ANSAH, L. (2023) · Journal of AI · doi:10.61969/jai.1337500 · Cited by 3,939
Mind in Society: Development of Higher Psychological Processes
VYGOTSKY, L. S. (1980) · doi:10.2307/j.ctvjf9vz4 · Cited by 3,123
Baidoo-Anu, D., & Owusu Ansah, L. (2023) · doi:10.2139/ssrn.4337484 · Cited by 3,004
Research Methods in Applied Linguistics
(2021) · Research methods in applied linguistics · doi:10.1075/rmal · Cited by 2,782
Biber, D., & Conrad, S. (2009) · Cambridge University Press eBooks · doi:10.1017/cbo9780511814358 · Cited by 2,126
Artificial intelligence in higher education: the state of the field
Crompton, H., & Burke, D. (2023) · International Journal of Educational Technology in Higher Education · doi:10.1186/s41239-023-00392-8 · Cited by 2,010
ChatGPT: five priorities for research
van Dis, E. A. M., Bollen, J., Zuidema, W., van Rooij, R., & Bockting, C. L. (2023) · Nature · doi:10.1038/d41586-023-00288-7 · Cited by 1,842 · cited 1×
“ChatGPT is a “large language model (LLM), a type of machine learning system that learns on its own from data and is trained on a vast corpus of text to produce sophisticated and presumably intelligent writing” (van Dis et al., 2023).”
Background
Research works printed but not linked: 7
- Andre, T. (1998). The impact of digital and electronic technology in education: A Glacier with multiple causes? Journal of Computing in Teacher Education, 14(3), 17–20.
- Fryer, L., Coniam, D., Carpenter, R., & Lăpușneanu, D. (2020). Bots for language learning now: Current and future directions. http://hdl.handle.net/10125/44719
- Kohnke, L. (2022). A pedagogical chatbot: A supplemental language learning tool. RELC Journal, 54, 828–838. https://doi.org/10.1177/0033688221106705 · DOI
- Malinowski, B. (1923). The problem of meaning in primitive languages. In C. K. Ogden & I. A. Richards (Eds.), The meaning of meaning (pp. 296–336). K. Paul, Trend, Trubner.
- Raja, R., & Nagasubramani, P. C. (2018). Impact of modern technology in education. Journal of Applied and Advanced Research, 3(1), 33–35. https://doi.org/10.21839/jaar.2018.v3S1.165 · DOI
- Ratheeswari, K. (2018). Information communication technology in education. Journal of Applied and Advanced Research, 3(1), 45–47. https://doi.org/10.21839/jaar.2018.v3S1.169 · DOI
- Reid, T. B. W. (1956). Linguistics, structuralism and philology. Archivum Linguisticum, 8(1), 28–37.
Cited by
Sorted by citations
Li, B., Tan, Y. L., Wang, C., & Lowell, V. L. (2025) · Computers and Education Artificial Intelligence · doi:10.1016/j.caeai.2025.100445 · Cited by 217
Teng, M. F. (2024) · International Journal of TESOL Studies · doi:10.58304/ijts.20240304 · Cited by 191
Mohebbi, A. (2025) · Cogent Education · doi:10.1080/2331186x.2024.2433814 · Cited by 161
Generative AI (GenAI) in the language classroom: A systematic review
Lee, S., Choe, H., Zou, D., & Jeon, J. (2026) · Interactive Learning Environments · doi:10.1080/10494820.2025.2498537 · Cited by 158
Meniado, J. C., Huyen, D. T. T., Panyadilokpong, N., & Lertkomolwit, P. (2024) · Computers and Education Artificial Intelligence · doi:10.1016/j.caeai.2024.100313 · Cited by 119
Metadata
- Authors
- Punar Özçelik, N., & Yangın Ekşi, G.
- Venue
- Smart Learning Environments
- Published
- 2024-03-18
- Volume
- 11
- Issue
- 1
- ISSN
- 2196-7091 (ISSN-L)
- OpenAlex
- W4392917047
- Cited by
- 115
- References
- 41
- Citations by year
- 2026: 40 · 2025: 47 · 2024: 28
- FWCI
- 43.13
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- Smart Learning Environments (publishedVersion, cc-by)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Topics
- Social Sciences › Education › Artificial Intelligence in Education
- Social Sciences › Arts and Humanities › Language and Linguistics › EFL/ESL Teaching and Learning
- Social Sciences › Education › English Language Learning and Teaching
- Keywords
- ChatGPT, AI chatbots, English writing, formal register, informal register, writing skills, learning assistants, artificial intelligence in language teaching
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 ›
Are you an author, or do you see a problem with this page? Request a review