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The existing common video game genres lack clarity as well as consistency and thus cannot serve as a solid reference to inform the research on digital educational games (DEG), which are increasingly used as learning tools. To address this basic issue of game classification, we have developed a web-based survey to collect data on how people play and perceive video games that they know well. The survey is grounded in our Game Elements-Attributes Model (GEAM). 321 valid responses were analysed using established hierarchical clustering methods and a novel mapping technique that computes the degree of relevance of individual game attributes to game types and visualises them with hues of grey. The game genre map so obtained can improve the existing game classification.
Heintz et al. (Mon,) studied this question.