Evidence map›Paper›PMID 39286160›Full record

ArticleHeliyon2024

From literacy to learning: The sequential mediation of attitudes and enjoyment in AI-assisted EFL education.

Jiqun Fan, Qinqing Zhang

Abstract read
In one paragraph

Article in Heliyon, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed, 2 pooled it
–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

10 citing papers in PubMed, 2 syntheses or guidelines pooled it.

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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

2 authors.

Jiqun FanSchool of Foreign Languages, Huainan Normal University, Huainan, Anhui Province, 232001, China.
Qinqing ZhangSchool of Foreign Languages, Huainan Normal University, Huainan, Anhui Province, 232001, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Artificial intelligence (AI) has become increasingly prominent in English as a Foreign Language (EFL) education. However, research on the factors influencing learners' sustained engagement with AI-assisted learning is scarce. This study bridges this gap by investigating the impact of AI literacy, learner attitudes toward AI-assisted learning, and foreign language enjoyment (FLE) on Chinese EFL learners' continuance intention (CI) for AI-assisted EFL learning. A survey of 417 EFL learners was conducted, and structural equation modeling was utilized to elucidate the relationships between these variables. The findings reveal that AI literacy, learner attitudes, and FLE significantly predict the CI. Moreover, AI literacy indirectly influences CI by mediating learner attitudes and FLE. Finally, FLE mediates the relationship between learner attitudes and CI. The study verifies a sequential mediation model, providing new insights into EFL learners' cognitive and affective traits and extending current models on the continuance intention in AI-assisted EFL learning. The research underscores the necessity for educators and technology developers to consider learners' interests and feedback, which are crucial for the sustainable progress of AI-assisted EFL learning.

Indexed as

AI-Assisted EFL learningAI literacyContinuance intentionForeign language enjoymentLearner attitudes

Identifiers

PMID39286160
PMCPMC11402731

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.