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

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.

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Publication Details

Journal
PLoS ONE
Published
2025-12-19
DOI
https://doi.org/10.1371/journal.pone.0335747
Citations
1
Primary Topic
Ethics and Social Impacts of AI
Type
article
Field-Weighted Citation Impact
2.37
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article

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

1 citations
PLoS ONE
Ethics and Social Impacts of AI
2.37
article

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

article en
1 citations

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.

PLoS ONEVol. 20(12)
University of Nigeria (NG), University of South Africa (ZA), University of Johannesburg (ZA), Obafemi Awolowo University (NG)
Openalex Percentile: Top 8%
Ethics and Social Impacts of AI
2.37
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