Abstract
Simulation, augmented by artificial intelligence, is increasingly reshaping MSc-level construction and project-management education by transforming it from a content-driven model into a data-informed, evidence-producing learning system. This study advances a two-layer adaptive framework in which pedagogical enablers—game design, game management, and tutor capability—create the conditions for learning, while an integrated validation layer enables the objective assessment of professional competence. Drawing on mixed-methods evidence from simulation-based teaching, including pre- and post-intervention skill assessment, tutor interviews, and longitudinal behavioural data, the framework demonstrates how AI enhances simulation authenticity through dynamic scenario generation, supports tutors via analytics-driven insight and facilitation cues, and enables adaptive orchestration through real-time monitoring of decisions, errors, and learning trajectories. At its core, the framework shifts emphasis from perceived learning gains to verified, standards-aligned competence, evidenced through authentic project artefacts and mapped to recognised professional frameworks such as the IPMA Individual Competence Baseline and the APM Body of Knowledge. By embedding governance, decision-making, and reflective practice within immersive simulation environments, the approach aligns assessment with industry expectations and prepares graduates for the complexity, uncertainty, and accountability of contemporary project delivery. The findings position AI-enabled simulation not merely as an engaging pedagogical tool, but as a robust mechanism for developing and validating work-ready, digitally fluent project-management professionals.