Evidence map›Paper›PMID 41417785›Full record

ArticlePloS one2025

Ethical compliance and institutional policy support for artificial intelligence integration in African TVET Education: A structural equation modeling approach.

Musa Adekunle Ayanwale, Christian Basil Omeh, Folasade Mardiyya Oyeniran, Catherine Chiugo Kanu

Abstract read
In one paragraph

Article in PloS one, 2025. 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

4 authors.

Musa Adekunle AyanwaleDepartment of Mathematics, Science and Technology Education, Faculty of Education, University of Johannesburg, Auckland Park, South Africa.ORCID https://orcid.org/0000-0001-7640-9898
Christian Basil OmehDepartment of Science and Technology Education, University of South Africa, Pretoria, South Africa.ORCID https://orcid.org/0000-0002-1673-2578
Folasade Mardiyya OyeniranDepartment of Educational Technology and Library Studies, Obafemi Awolowo University, Nigeria.
Catherine Chiugo KanuDepartment of Business Education, University of Nigeria, Nigeria.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

As artificial intelligence (AI) reshapes educational landscapes, ensuring ethical alignment and institutional responsiveness is essential particularly in skill-intensive sectors such as Technical and Vocational Education and Training (TVET). In this study, we examined the predictive roles of Ethical Principles Guiding AI adoption (EPG), Compliance with AI Ethical Guidelines (CAEG), and Perceived AI Adoption Outcomes (PAAT), while testing the moderating effect of Institutional Policy Support (IPS). Grounded in Rest's Four Component Model of ethical behavior, we adopted a cross-sectional, quantitative design and surveyed 400 TVET educators across Nigeria using a rigorously validated instrument. Our analysis through Partial Least Squares Structural Equation Modeling (PLS-SEM) revealed that Ethical Principles Guiding AI adoption significantly influenced both Compliance with AI Ethical Guidelines and Perceived AI Adoption Outcomes. Moreover, CAEG partially mediated the relationship between EPG and PAAT, highlighting compliance as a vital conduit for ethical adoption. However, IPS did not significantly moderate the EPG-CAEG relationship, indicating that personal ethical orientation may remain influential even in the absence of institutional frameworks. Our model demonstrated strong explanatory and predictive validity, particularly in institutions without formal AI policies underscoring the compensatory role of ethical leadership. We contribute novel empirical insights to the emerging scholarship on AI ethics in education by integrating ethical compliance and policy dynamics into a unified framework contextualized within African TVET systems. Our findings emphasize the importance of empowering educators with ethical competencies and call for urgent institutional action in policy formulation, infrastructure investment, and professional development to support responsible AI integration in education.

Indexed as

Artificial IntelligenceAdultCross-Sectional StudiesFemaleHumansLatent Class AnalysisMaleMiddle AgedNigeria

Identifiers

PMID41417785
PMCPMC12716723

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.