Abstract
Intelligent Transport Systems (ITS) require engineers skilled in systems thinking and decision-making under uncertainty; however, traditional pedagogy struggles to simulate dynamic, multi-agent interactions. This mixed-methods study evaluates the efficacy of
OpenTTD
, an open-source transport simulation game, as a scalable and reproducible game-based learning (GBL) tool in undergraduate ITS education. Quantitative results revealed significantly higher post-test scores in applied and strategic domains for the experimental group, particularly in transport network design and scenario-based problem-solving. A post-intervention questionnaire assessed psychological constructs including enjoyment, engagement, competence, immersion, perceived difficulty, learning value, satisfaction, and future intention. Correlational analyses supported key hypotheses derived from Self-Determination Theory, Flow Theory, and the Technology Acceptance Model, revealing that enjoyment and engagement were strong predictors of perceived learning value. Furthermore, participants’ perceived competence and recognition of the learning value of the simulation, not merely immediate satisfaction or difficulty, were the main drivers of their intention to adopt GBL in future studies. The complexity of the high-fidelity simulation, although perceived as challenging, was interpreted as cognitively stimulating and promoted persistence. These findings provide theory-based domain-specific evidence for integrating open-source simulations into engineering curricula and contribute to a more nuanced understanding of the motivational and cognitive mechanisms underlying GBL. This study demonstrates how to transform ITS laboratories into low-risk, high-fidelity resilience simulators, supports reproducible pedagogy, and advances both student outcomes and engineering education.