Design methodology of analytical games for knowledge acquisition

Analytical games explore a problem or a domain with a research purpose. Considerable research is ongoing to investigate improvements to analytical game design, execution and exploitation. Moreover, the fast-paced technological developments in many fields, such as artificial intelligence and virtual reality, make it even more compelling to account for the advantages and limitations of these new capabilities. In game design, the use of digital means is often regarded as a mere technical factor that relates to the platform selection, facilitator support and data recording processes. In this work a shift in perspective is proposed, to move from technology-oriented design selection criteria towards a broader assessment of the design choices. In fact, the introduction of technology (i.e., automation and autonomy) will not lead to a substitution of tasks, but will intrinsically change the game environment. This work introduces a framework to provide a structured guidance on the aspects to be factored in the different design phases of an analytical game, including the potential impact of the adoption of automation and autonomy. The proposed approach is based on previous research in the field of simulation-based serious gaming, model-driven engineering and human factors engineering. The framework is applied to a Knowledge Acquisition Analytical Game as a case study.