SIMULATION-DRIVEN RESILIENCE: FROM CDIO TO CDI'S' ASSESSMENTS TO OUTSMART AI SHORTCUTS

The Conceive–Design–Implement–Operate (CDIO) framework has played a central role in aligning engineering education with professional practice through authentic, project-based learning and outcome-oriented assessment. By embedding learning within realistic workflows, CDIO has shifted emphasis from content delivery to demonstrated competence. However, in management-oriented engineering domains such as supply chain management, operations strategy, and complex project environments, the Operate phase presents structural limitations. Real operational systems cannot be physically enacted in educational contexts due to constraints of scale, cost, risk, time, and ethical responsibility, often leading to simplified case-based or report-driven approximations that weaken experiential authenticity. At the same time, higher education faces growing challenges related to assessment integrity arising from the widespread availability of generative artificial intelligence. Traditional written assessments, including those embedded within CDIO projects, are increasingly vulnerable to AI-assisted production that obscures student reasoning and professional judgement. This paper proposes CDIS (Conceive–Design–Implement–Simulate) as an extension of the CDIO framework in which simulation replaces physical operation as the primary mechanism for experiential learning and assessment. Simulation-based environments enable complexity, uncertainty, delayed feedback, and cross-functional decision-making without the risks of real-world replication. Using The Fresh Connection supply chain simulation as an illustrative implementation, the paper argues that CDIS supports authentic, data-driven, and AI-resilient assessment. By embedding learning within dynamic systems governed by real-time KPIs and iterative decision cycles, CDIS strengthens deep learning while preserves the epistemological intent of CDIO in complex engineering and management education contexts.