Evidence map›Paper›PMID 41572352›Full record

SynthesisBMC psychology2026

Factors influencing the intention to use generative artificial intelligence in educational systems: a meta-analysis.

Chang Yan Yan, Nuraini Binti Jafri

Abstract readMeta-AnalysisSystematic Review
In one paragraph

Synthesis in BMC 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.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

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.

Chang Yan YanFaculty of Educational Studies, Universiti Putra Malaysia, 43400, Serdang City, Selangor Darul Ehsan, Malaysia. gs71692@student.upm.edu.my.
Nuraini Binti JafriFaculty of Educational Studies, Universiti Putra Malaysia, 43400, Serdang City, Selangor Darul Ehsan, Malaysia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe rapid development of Generative Artificial Intelligence (Gen AI) has significantly impacted education. However, empirical findings on the intention to use Gen AI vary due to differing theoretical approaches. This study aims to clarify key influencing variables through a comprehensive meta-analysis.

methodsA total of 53 empirical studies were analyzed, including 17 influencing factors and 4 types of moderating variables. We extracted correlation coefficients from the included studies to assess their association with Gen AI use intention.

resultsStrong correlations were observed between use intention and perceived usefulness (r = 0.566) as well as attitude (r = 0.564). Moderate correlations are observed for performance expectancy (r = 0.499), perceived ease of use (r = 0.471), hedonic motivation (r = 0.456), personal innovation (r = 0.373), trust (r = 0.368), effort expectancy (r = 0.352), social influence (r = 0.329), and perceived intelligence (r = 0.326). Weak correlations are found for emotion (r = 0.255) and technology anxiety (r = − 0.239). Moderating effects were found: gender ratio influenced nine variables, country category affected effort expectancy and innovation, age moderated several cognitive and emotional variables, and measurement tools impacted multiple constructs including social influence and perceived ease of use.

conclusionThis study identifies core psychological and contextual factors influencing Gen AI use intention in educational settings. It offers theoretical clarity and practical guidance for optimizing Gen AI integration in education, supporting more effective adoption across diverse learner groups.

trial registrationThis study has been registered with PROSPERO, number: 639170.

Indexed as

Artificial IntelligenceGenerative Artificial IntelligenceIntentionHumansEducational technologyGenerative artificial intelligenceMeta-analysisModerating variablesTechnology acceptanceUser intention

Identifiers

PMID41572352
PMCPMC12964861

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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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.