Integrating Learning Analytics into a Game Authoring Tool Ivan J. Perez-Colado, Victor M. Perez-Colado, Manuel Freire-Moran, Ivan Martinez-Ortiz, and Baltasar Fernandez-Manjon (&) Department of Software Engineering and Artificial Intelligence, Facultad de Informática, Universidad Complutense de Madrid, Madrid, Spain {ivanjper,victormp}@ucm.es, {manuel.freire,imartinez,balta}@fdi.ucm.es Abstract. Educational games can greatly benefit from integrating support for learning analytics. Game authoring tools that make this integration as easy as possible are therefore an important step towards improving adoption of edu- cational games. We describe the process of integrating full support for game learning analytics into uAdventure, a serious game authoring tool. We argue that such integrations greatly systematize, simplify and reduce both the cost and the knowledge required to apply analytics to serious games. In uAdventure, we have used an analytics model for serious games and its supporting implementation as a xAPI application. We describe how player interactions are automatically traced, and provide an interaction-model-trace table with the general game traces that are generated by the editor. Also, we describe the custom editors that simplify the task of authoring game-dependant analytics. Thanks to these inte- grated analytics, games developed with uAdventure provide detailed tracking information that can be sent to a cloud analytics server, to be analyzed and visualized with dashboards that provide game developers and educators with insights into how games are being played. Keywords: Game learning analytics Á Analytics Á Serious games Á Games authoring Á xAPI 1 Introduction Game analytics (GA, also called telemetry) is the process of collecting and analyzing videogame user interactions to generate a better insight of the game experience for game designers and developers to take decisions in the next project iterations [1]. For example, such an analysis can reveal which levels are too hard for the average user, or provide insights on how to increase monetization. Similarly, learning analytics (LA) is the analysis of user ’s interactions with educational purposes [2], for instance providing information that allows educators to better understand how the learners are applying domain knowledge in an e-learning system, and improve the educational experience in some way (e.g. evaluate student progress). Game learning analytics (GLA) is the combination of both GA and LA to allow both game designers and educators to analyze player/learner interactions to improve the use of the games in education [3]. © Springer International Publishing AG 2017 H. Xie et al. (Eds.): ICWL 2017, LNCS 10473, pp. 51–61, 2017. DOI: 10.1007/978-3-319-66733-1_6