AI-Assisted Feedback in EFL Writing: Implications for Writing Accuracy and Learner Autonomy

This structured thematic literature review synthesizes peer-reviewed empirical research published between 2020 and 2026 on AI-assisted feedback in English as a Foreign Language (EFL) writing, examining its dual implications for writing accuracy and learner autonomy. Drawing on foundational theories of written corrective feedback, self-regulated learning, and learner autonomy, the review analyzes studies comparing AI-generated, teacher-provided, and hybrid feedback models. Findings indicate that AI feedback appears to improve surface-level accuracy in the reviewed studies, although its effectiveness remains inconsistent regarding higher-order concerns, including coherence, argumentation, and organization. Furthermore, its influence on learner autonomy depends largely on pedagogical design, learners’ critical engagement, and teachers’ guidance. The review argues that accuracy and autonomy are interdependent outcomes shaped by instructional integration rather than technological tools alone. It identifies critical research gaps, particularly the lack of longitudinal evidence and limited research involving lower-proficiency learners, and proposes pedagogical recommendations for human-centered AI implementation in EFL writing classrooms.

Authors

Institutions

Publication Details

Journal
Лингвоспектр
Published
2026-11-01
DOI
https://doi.org/10.5281/zenodo.23864054
Primary Topic
EFL/ESL Teaching and Learning
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

AI-Assisted Feedback in EFL Writing: Implications for Writing Accuracy and Learner Autonomy

Madina Amrullo kizi Sulaymonova
1 links
Лингвоспектр
EFL/ESL Teaching and Learning
article

AI-Assisted Feedback in EFL Writing: Implications for Writing Accuracy and Learner Autonomy

Madina Amrullo kizi Sulaymonova
article en

Abstract

This structured thematic literature review synthesizes peer-reviewed empirical research published between 2020 and 2026 on AI-assisted feedback in English as a Foreign Language (EFL) writing, examining its dual implications for writing accuracy and learner autonomy. Drawing on foundational theories of written corrective feedback, self-regulated learning, and learner autonomy, the review analyzes studies comparing AI-generated, teacher-provided, and hybrid feedback models. Findings indicate that AI feedback appears to improve surface-level accuracy in the reviewed studies, although its effectiveness remains inconsistent regarding higher-order concerns, including coherence, argumentation, and organization. Furthermore, its influence on learner autonomy depends largely on pedagogical design, learners’ critical engagement, and teachers’ guidance. The review argues that accuracy and autonomy are interdependent outcomes shaped by instructional integration rather than technological tools alone. It identifies critical research gaps, particularly the lack of longitudinal evidence and limited research involving lower-proficiency learners, and proposes pedagogical recommendations for human-centered AI implementation in EFL writing classrooms.

Лингвоспектр
Uzbek State University of World Languages (UZ)
Quality education
Openalex Percentile: Top 3%
EFL/ESL Teaching and Learning
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Laika access coming soon
AI-Assisted Feedback in EFL Writing: Implications for Writing Accuracy and Learner Autonomy — Madina Amrullo kizi Sulaymonova · Лингвоспектр (2026) | TGRS Research Map | TGRS