Exploring students’ acceptance of ChatGPT in assisting EFL writing tasks: A technology acceptance model perspective

Research on the integration of ChatGPT revolutionizing English language learning in EFL contexts has been documented. Yet, research on the acceptance of ChatGPT from the perspective of a technology acceptance model (TAM) in the EFL writing context remains underexplored. This descriptive qualitative study aims to explore the students' acceptance of ChatGPT in assisting writing tasks using the TAM framework. The study involved six eleventh-grade students enrolled in the language program of a senior high school in Lamongan, Indonesia. Data were gathered through semi-structured interviews and classroom observation and then analyzed using a thematic pattern. The findings reveal a nuanced dynamic. EFL students view ChatGPT not merely as a correction tool in writing but as a cognitive scaffold that offers psychological safety through non-judgmental feedback, fostering self-regulated learning. Conversely, while the technical interface is intuitive, the students face significant semantic barriers when writing, requiring iterative "prompt engineering" to mitigate AI hallucinations. These results indicate that successful integration relies less on the tool's mechanics and more on the user's digital capabilities. The study implies a pedagogical shift towards critical AI literacy, encouraging educators to guide students in treating AI as a collaborative partner in hybrid intelligence rather than a replacement for critical thinking.

Authors

Publication Details

Journal
Journal on English as a Foreign Language
Published
2026-03-31
DOI
https://doi.org/10.23971/jefl.v16i1.10378
Primary Topic
Artificial Intelligence in Healthcare and Education
Type
article
Field-Weighted Citation Impact
0.00
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article

Exploring students’ acceptance of ChatGPT in assisting EFL writing tasks: A technology acceptance model perspective

Riryn Fatmawaty, Fita Faridah, Dian Luthfiyati
Journal on English as a Foreign Language
Artificial Intelligence in Healthcare and Education
article

Exploring students’ acceptance of ChatGPT in assisting EFL writing tasks: A technology acceptance model perspective

Riryn Fatmawaty, Fita Faridah, Dian Luthfiyati
article en

Abstract

Research on the integration of ChatGPT revolutionizing English language learning in EFL contexts has been documented. Yet, research on the acceptance of ChatGPT from the perspective of a technology acceptance model (TAM) in the EFL writing context remains underexplored. This descriptive qualitative study aims to explore the students' acceptance of ChatGPT in assisting writing tasks using the TAM framework. The study involved six eleventh-grade students enrolled in the language program of a senior high school in Lamongan, Indonesia. Data were gathered through semi-structured interviews and classroom observation and then analyzed using a thematic pattern. The findings reveal a nuanced dynamic. EFL students view ChatGPT not merely as a correction tool in writing but as a cognitive scaffold that offers psychological safety through non-judgmental feedback, fostering self-regulated learning. Conversely, while the technical interface is intuitive, the students face significant semantic barriers when writing, requiring iterative "prompt engineering" to mitigate AI hallucinations. These results indicate that successful integration relies less on the tool's mechanics and more on the user's digital capabilities. The study implies a pedagogical shift towards critical AI literacy, encouraging educators to guide students in treating AI as a collaborative partner in hybrid intelligence rather than a replacement for critical thinking.

Journal on English as a Foreign LanguageVol. 16(1)
Quality Education
Openalex Percentile: Top 9%
Artificial Intelligence in Healthcare and Education
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Exploring students’ acceptance of ChatGPT in assisting EFL writing tasks: A technology acceptance model perspective — Riryn Fatmawaty, Fita Faridah, et al. · Journal on English as a Foreign Language (2026) | TGRS Research Map | TGRS