Eliciting and Modelling Expertise for Serious Games in Project Management

Serious game development for complex professional domains often relies on intuitive, craft-based methods that lack empirical rigor. To address this, a systematic three-stage methodology integrates Applied Cognitive Task Analysis with Belief-Desire-Intention frameworks to transform expert knowledge into predictable, evidence-based game design. By shifting the focus from generic execution tasks to high-value cognitive challenges, this approach ensures that pedagogical objectives are directly mapped to specific game mechanics and non-player character behaviors.

The research draws upon insights from 26 international project management experts, resulting in the identification and modeling of over 300 distinct task elements. Through a process of knowledge audits and simulation interviews, the methodology successfully isolates the most cognitively demanding aspects of project management, such as scope definition. This data-driven foundation allows designers to translate expert strategies and common novice errors into concrete, actionable features, thereby enhancing the efficacy of simulation-based training.

This framework provides a repeatable, structured alternative to traditional design practices, bridging the gap between cognitive science and interactive learning environments. By grounding game mechanics in validated expert decision-making models, the methodology improves the quality of serious games intended for professional development. Ultimately, this approach establishes a robust standard for capturing and representing complex expertise, ensuring that digital training tools remain aligned with the nuanced realities of high-stakes project management environments.