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Please use this identifier to cite or link to this item: http://hdl.handle.net/1820/7619
Title: Systematizing game learning analytics for serious games
Authors: Alonso-Fernandez, Cristina
Calvo-Morata, Antonio
Freire, Manuel
Martinez-Ortiz, Ivan
Fernandez-Manjon, Baltasar
Keywords: game analytics
serious games
e-learning
dashboard
xAPI
Issue Date: Apr-2017
Publisher: IEEE
Citation: Cristina Alonso-Fernandez, Antonio Calvo-Morata, Manuel Freire, Iván Martínez-Ortiz, Baltasar Fernández-Manjón (2017): Systematizing game learning analytics for serious games. IEEE Global Engineering Education Conference (EDUCON), 25-28 April 2017, Athens, Greece.
Abstract: Applying games in education provides multiple benefits clearly visible in entertainment games: their engaging, goal-oriented nature encourages students to improve while they play. Educational games, also known as Serious Games (SGs) are video games designed with a main purpose other than pure entertainment; their main purpose may be to teach, to change an attitude or behavior, or to create awareness of a certain issue. As educators and game developers, the validity and effectiveness of these games towards their defined educational purposes needs to be both measurable and measured. Fortunately, the highly interactive nature of games makes the application of Learning Analytics (LA) perfect to capture students’ interaction data with the purpose of better understanding or improving the learning process. However, there is a lack of widely adopted standards to communicate information between games and their tracking modules. Game Learning Analytics (GLA) combines the educational goals of LA with technologies that are commonplace in Game Analytics (GA), and also suffers from a lack of standards adoption that would facilitate its use across different SGs. In this paper, we describe two key steps towards the systematization of GLA: 1), the use of a newly-proposed standard tracking model to exchange information between the SG and the analytics platform, allowing reusable tracker components to be developed for each game engine or development platform; and 2), the use of standardized analysis and visualization assets to provide general but useful information for any SG that sends its data in the aforementioned format. These analysis and visualizations can be further customized and adapted for particular games when needed. We examine the use of this complete standard model in the GLA system currently under development for use in two EU H2020 SG projects.
URI: http://hdl.handle.net/1820/7619
Appears in Collections:1. RAGE Publications

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