Evidence map›Paper›PMID 42824047›Full record

ArticleFrontiers in psychology2026

The cumulative effects of AI-generated feedback on syntactic development in high school EFL writers: a longitudinal quasi-experimental study.

Qiong Xiao, Yunhe Sun

Abstract read
In one paragraph

Article in Frontiers in psychology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Qiong XiaoSchool of Educational Science, Hunan Normal University, Changsha, Hunan, China.
Yunhe SunSchool of Literature and Digital Communication, Hunan University of Technology and Business, Changsha, Hunan, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: While AI-generated writing feedback research has flourished, most studies prioritizeholistic quality over syntactic competence and rely on static pre-post comparisons, neglecting dynamic multi-round evolution. Methods: This 35-week quasi-experiment examined cumulative associations between exposure to supplementary AI-generated feedback components and syntactic development among 69 Chinese high school EFL learners (Group A: Results: The study described non-linear trajectories: an initial adaptation decline followed by faster gains. Among the 10 target error types, only Part-of-Speech errors showed a statistically significant reduction after FDR correction; other error categories exhibited only suggestive trends that did not remain robust after multiple comparison adjustment. Mixed-methods analysis described a hypothesized cognitive load pattern in which extraneous load diminished yet germane processing diverged contingent on learner strategy, with passive offloading coinciding with an illusion of competence. Four revision strategies emerged. Discussion: The findings are consistent with a conditional pathway within the CLT-SAT framework as an interpretive lens and suggest the potential of a phased Human-in-the-Loop model for contexts where supplementary AI-generated feedback is provided, one that scaffolds autonomy while guarding against passive offloading.

Indexed as

AI-generated feedbackcognitive load theoryEFL writinglongitudinal quasi-experimental studyskill acquisition theorysyntactic development

Identifiers

PMID42824047
PMCPMC13627100

What OpenQuestion holds

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.