Identifying Structural Barriers in the Digital-Intelligent Integration of Construction-Engineering Education

Abstract

This study examined how data-driven and intelligent technologies are embedded across the core instructional processes of the Intelligent Construction program, including curriculum design, classroom delivery, learning assessment, and quality enhancement. Although tools such as BIM platforms, IoT systems, digital twins, and AI-based learning analytics have been introduced, their pedagogical value remains limited. The findings indicate three structural constraints: insufficient alignment between curriculum objectives and digital-intelligent competencies, fragmented technology deployment with low inter-platform interoperability and limited data feedback loops, and inconsistent use of process-based evidence in learning evaluation. Additionally, institutional support and data governance frameworks remain underdeveloped, restricting the depth of integration. In response, this study proposes a coordinated improvement pathway emphasizing conceptual renewal, institutional support, capacity building, and technological synergy. The work provides an empirical foundation for constructing an integrated, industry-linked talent cultivation model in intelligent construction.