Evidence map›Paper›PMID 41993815›Full record

ArticleFrontiers in psychology2026

How generative AI enhances self-regulated learning in EFL learners: a chain mediation model of "intention to use" and "learning engagement".

Jin Xu

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. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Article
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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

1 author.

Jin XuGeneral Education College, Jinhua University of Vocational Technology, Jinhua, Zhejiang, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Generative Artificial Intelligence is transforming English as a Foreign Language writing instruction. While much research has focused on technology acceptance, limited attention has been paid to how AI influences learners' psychological and behavioral processes, thereby affecting self-regulated learning. This study constructs and tests a theoretical model that examines the chain mediation of "intention to use → learning engagement" to explore how generative AI impacts self-regulated learning in EFL learners. Involving 386 Chinese EFL learners from universities, the study uses a questionnaire survey and structural equation modeling for data analysis. The findings show that the perceived ease of use, usefulness, and interactivity of generative AI significantly predict both intention to use and self-regulated learning. Intention to use is related to learning engagement, which in turn fosters self-regulated learning. Moreover, generative AI enhances self-regulated learning through intention to use and learning engagement, with these factors serving as key mediators. This study illuminates the pathway from "technology perception" to "behavioral intention," "immersive engagement," and "regulatory process," providing novel insights into AI-assisted second language writing learning and offering empirical evidence for designing effective human-computer collaborative EFL writing practices.

Indexed as

EFL (English as a Foreign Language)generative AIlearning engagementself-regulated learningtechnology acceptance model

Identifiers

PMID41993815
PMCPMC13079642

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.