Towards Game-based Assessment at Scale

Games are increasingly being recognized as valuable tools for learning. In addition, they are also being explored for their potential to provide valid and reliable assessments, as they allow to create authentic and engaging assessment contexts through interactive and immersive environments. However, there are challenges to enable Game-based Assessment (GBA) at scale, including the need for interoperability between assessment models and machinery, and the complexity of managing and processing large amounts of data generated by users' interaction with games. In this study, we propose a novel approach that combines the use of ontologies and Big Data technologies for developing interoperable GBAs. The architecture enables assessments to be performed using data from different games, and we also designed and implemented a service API that facilitates the Game-Based Assessment as a Service (GBAaaS) paradigm. GBAaaS simplifies the GBA development process and enables its adoption at scale, making it a promising approach for future developments in this field.