AWARENESS AND ENGAGEMENT WITH ARTIFICIAL INTELLIGENCE TECHNOLOGIES AS PREDICTORS OF UNDERGRADUATES' READINESS IN BUILDING AND WOODWORK TECHNOLOGY FOR CONSTRUCTION PRACTICE IN BENUE STATE

This study investigates the levels of awareness and engagement with Artificial Intelligence (AI) technologies among undergraduate students in building and woodwork technology programmes in Nigeria, and examines their preparedness for professional practice in the construction industry. Employing a quantitative research design, data were collected from 167 students across universities, polytechnics, and colleges of education using a validated 20-item questionnaire (Cronbach's α = 0.78). Descriptive statistics revealed moderate levels of AI awareness (Mt = 1.97, SDt = 0.77) and engagement (Mt = 2.28, SDt = 0.79), with polytechnic students demonstrating the highest awareness and university students reporting the greatest engagement. However, students exhibited limited readiness (Mt = 2.16, SDt = 0.85) to apply AI technologies in real-world construction scenarios. Regression and correlation analyses (α = 0.05) indicated a statistically significant positive relationship between AI awareness, engagement, and industry readiness, though the explained variance was modest. The findings underscore critical gaps in current curricular integration of AI applications, such as machine learning and automated systems, within construction-related disciplines. Based on these results, the study recommends targeted interventions, including enhanced AI-focused coursework, practical training initiatives, and faculty development programmes, to bridge the disparity between academic training and industry requirements.

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-05-08
DOI
https://doi.org/10.5281/zenodo.15365237
Primary Topic
Photodynamic Therapy Research Studies
Type
article
Field-Weighted Citation Impact
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article

AWARENESS AND ENGAGEMENT WITH ARTIFICIAL INTELLIGENCE TECHNOLOGIES AS PREDICTORS OF UNDERGRADUATES' READINESS IN BUILDING AND WOODWORK TECHNOLOGY FOR CONSTRUCTION PRACTICE IN BENUE STATE

Zenodo (CERN European Organization for Nuclear Research)
Photodynamic Therapy Research Studies
article

AWARENESS AND ENGAGEMENT WITH ARTIFICIAL INTELLIGENCE TECHNOLOGIES AS PREDICTORS OF UNDERGRADUATES' READINESS IN BUILDING AND WOODWORK TECHNOLOGY FOR CONSTRUCTION PRACTICE IN BENUE STATE

article en

Abstract

This study investigates the levels of awareness and engagement with Artificial Intelligence (AI) technologies among undergraduate students in building and woodwork technology programmes in Nigeria, and examines their preparedness for professional practice in the construction industry. Employing a quantitative research design, data were collected from 167 students across universities, polytechnics, and colleges of education using a validated 20-item questionnaire (Cronbach's α = 0.78). Descriptive statistics revealed moderate levels of AI awareness (Mt = 1.97, SDt = 0.77) and engagement (Mt = 2.28, SDt = 0.79), with polytechnic students demonstrating the highest awareness and university students reporting the greatest engagement. However, students exhibited limited readiness (Mt = 2.16, SDt = 0.85) to apply AI technologies in real-world construction scenarios. Regression and correlation analyses (α = 0.05) indicated a statistically significant positive relationship between AI awareness, engagement, and industry readiness, though the explained variance was modest. The findings underscore critical gaps in current curricular integration of AI applications, such as machine learning and automated systems, within construction-related disciplines. Based on these results, the study recommends targeted interventions, including enhanced AI-focused coursework, practical training initiatives, and faculty development programmes, to bridge the disparity between academic training and industry requirements.

Zenodo (CERN European Organization for Nuclear Research)
Industry, innovation and infrastructure
Openalex Percentile: Top 37%
Photodynamic Therapy Research Studies
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