Comparative visualization of player behavior for serious game analytics

\u3cp\u3eTelemetry opens new possibilities for the assessment of serious games through the continuous, unobtrusive, monitoring of in-game behavior. Data obtained through telemetry thus not only contains information about the outcomes but also about the intermediate processes. In this sense, telemetry data can be of value for various stakeholders of serious games, including developers, educators, and learners themselves to increase the effectiveness of the intervention. In doing so, particular significance should be attached to differences among individuals and demographic groups in order to understand and better accommodate for these variations. However, the large amounts of data gathered via telemetry can make it challenging to derive meaningful information from it. Visualizations can support this process by providing a means to explore, to compare, and to draw insights from the data sets. In this chapter, we discuss three common visual design strategies that facilitate comparative data analysis. Several examples, drawn from the game-based learning literature and related areas as well as two detailed case studies are used to illustrate how these strategies can be leveraged in the context of serious game analytics.\u3c/p\u3