Transforming Construction Education through Artificial Intelligence and Simulation-Based Work Integrated Learning: A Systematic Literature Review

Abstract

The rapid advancement of Artificial Intelligence (AI) is transforming higher education, particularly in professionally oriented fields such as construction education. At the Central University of Technology, Work Integrated Learning (WIL) plays a vital role in preparing students for industry readiness and digital transformation. However, limited industry placements, assessment integrity, and growing digitalisation have increased interest inmsimulation-based and AI-enabled WIL models. This systematic literature review (SLR) investigates the integration of AI into simulation-based WIL in construction education. Using PRISMA principles, literature published between 2016 and 2026 was systematically reviewed and analysed. 38 scholarly articles were reviewed. Thematic analysis identified key themes including AI-enabled pedagogy, simulation-based WIL, assessment transformation, governance and ethics, and student readiness. Findings indicate that AI can enhance simulated WIL through reflective learning, technical report writing, problem-solving, adaptive learning, and digital collaboration. AI integration further improves student engagement, workplace preparedness, and access to construction knowledge where traditional placements are limited. Despite these benefits, concerns remain regarding assessment authenticity, overreliance on generative AI, digital literacy inequalities, ethical risks, and weak governance frameworks. The review concludes that effective AI-supported WIL requires a balanced pedagogical approach that combines authentic assessment, educator supervision, simulation-based learning, and responsible AI governance.