INTEGRATING ARTIFICIAL INTELLIGENCE IN TECHNICAL AND VOCATIONAL EDUCATION AND TRAINING IN PUBLIC INSTITUTIONS IN NIGERIA: BRIDGING SKILLS GAPS FOR FUTURE WORKFORCE READINESS

Authors

  • AIRERUOR, N.E. Department of Vocational and Technical Education, Ambrose Alli University, Ekpoma
  • PROF. ADAVBIELE, J.A. Department of Vocational and Technical Education, Ambrose Alli University, Ekpoma
  • ABHULIMEN, J.I. Ph.D Department of Vocational and Technical Education, Ambrose Alli University, Ekpoma

Keywords:

Artificial Intelligence, TVET, Skills Gap, Workforce Readiness, Technology Education.

Abstract

The study examined the integration of Artificial Intelligence (AI) in public Technical and Vocational Education and Training (TVET) institutions in Edo State, Nigeria, for bridging skills gaps and enhancing future workforce readiness using descriptive survey research design. The study was guided by five research questions and three hypotheses. The population comprised 2,183 respondents consisting of 203 instructors and 1,980 students in seven public TVET institutions in Edo State. A sample of 372 respondents (150 instructors and 222 students) was selected using multi-stage sampling technique. Data were collected using a structured questionnaire titled Artificial Intelligence Integration in TVET Questionnaire (AIITVETQ) with an overall reliability coefficient of .87 established through Cronbach Alpha. Data were analyzed using mean, standard deviation, independent t-test, Pearson Product Moment Correlation and linear regression at .05 level of significance. Findings revealed moderate awareness but low functional knowledge and adoption of AI (cluster mean = 3.32), low extent of AI integration into curricula (2.35), high infrastructural and human capacity challenges (4.25), high perceived relevance of AI for workforce readiness (4.30), and strong agreement on strategies for integration (4.56). Hypotheses testing showed no significant difference between instructors and students on AI awareness (t = 1.82, p = .069), a strong positive relationship between AI integration and workforce readiness (r = .72, p = .000), and that institutional challenges significantly predicted AI integration (R² = .46, p = .000). The study concluded that public TVET institutions in Edo State operate largely on analog models with low AI integration despite high stakeholder interest. Recommendations include urgent curriculum review to embed AI, establishment of AI labs with reliable power and internet via PPP, continuous professional development for instructors, formulation of an AI policy framework for TVET, and strengthened industry partnerships.

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Published

2026-09-24 — Updated on 2026-09-30