INTEGRATING ARTIFICIAL INTELLIGENCE IN CONSTRUCTION EDUCATION: A PEDAGOGICAL FRAMEWORK FOR ENHANCING STUDENT COMPETENCE AND INDUSTRY READINESS

Abstract

Artificial Intelligence (AI) is transforming education by enabling personalized, adaptive, and technology-driven learning experiences. In construction education, however, traditional pedagogical approaches remain predominant, which may not adequately prepare students for the AI-driven demands of the modern construction industry. As AI becomes integral to predictive analysis, risk management, and automated construction processes, aligning educational practices with industry requirements is essential. This study aimed to develop a pedagogical framework for integrating AI in construction education to enhance student competence, digital literacy, and industry readiness. Specifically, it assessed current AI integration, identified competencies required by the industry, examined student perceptions of AI-supported learning, analyzed the effectiveness of AI-enhanced pedagogy, explored ethical and instructional challenges, and proposed a structured framework for sustainable implementation. Employing a mixed-methods research design, the study collected quantitative data through structured questionnaires administered to 50 students, and qualitative data via semi-structured interviews with 20 educators and 30 industry professionals. Document analysis of curriculum and AI-supported instructional modules was also conducted. Quantitative data were analyzed using descriptive and inferential statistics, while qualitative data underwent thematic analysis. Findings were triangulated to ensure validity and comprehensiveness in the development of the AI-based pedagogical framework. AI integration in construction education was moderate, with teaching strategies showing higher adoption than curriculum content. Students perceived AI-supported learning as beneficial for engagement, understanding, and career relevance. Industry-required competencies included technical proficiency, analytical skills, and problem-solving abilities. Key challenges involved educator preparedness, resource constraints, and ethical considerations. The study proposes a structured AI-based pedagogical framework emphasizing technical skills, critical thinking, digital literacy, and ethical AI use. This framework bridges classroom learning with professional practice, preparing graduates for the evolving, AI-driven construction industry.

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