AI-DRIVEN TRANSFORMATION OF WOODWORK TECHNOLOGY EDUCATION FOR SUSTAINABLE WORKFORCE DEVELOPMENT IN TERTIARY INSTITUTIONS IN LAGOS STATE

Abstract

This study investigated the AI-driven transformation of Woodwork Technology Education for sustainable workforce development in Lagos State, Nigeria. It evaluated the extent of artificial intelligence (AI) integration, its influence on practical skill acquisition, and the technical bottlenecks hindering its adoption within technical and vocational education and training (TVET) frameworks. A descriptive survey design was adopted, utilizing a total enumeration technique to capture 43 specialized respondents (13 facilitators, 30 industrial experts). Primary data collected via a structured questionnaire (AIDT-WTESWDQ) yielded sub-scale Cronbach‘s alpha coefficients from 0.84 to 0.87. Data were analyzed using mean and standard deviation descriptive statistics against a 3.50 criterion threshold. Findings revealed that AI-driven tools,
like cloud-based CAD simulations, significantly enhance technical skills and graduate
employability, actual current integration remains low and confined to theoretical applications. Descriptive analysis verified erratic public power supply, inadequate software funding, and low internet bandwidth actively neutralize these digital learning paths during workshop sessions. The study concluded that operational success depends entirely on dismantling these infrastructural deficits. The study recommended that institutions prioritize alternative energy installations and localized offline servers, establish public-private software partnerships, and collaborate with the National Board for Technical Education (NBTE) to mandate a balanced digital-to-physical curriculum split