Educational games (aka serious games, SG) are powerful educational contents. However, they are costly to develop, and once developed, SGs become dependent on software and hardware combinations that may become obsolete, such as Adobe Flash or Java Applets. Addressing these problems would allow a much greater use of SGs in education. The eAdventure authoring tool, developed by the e-UCM research group, addressed high development costs, and resulted in the creation of multiple SGs in collaboration with different institutions. However, eAdventure's Java Applets have become increasingly difficult to run due to platform obsolescence. To maintain the benefits of the eAdventure platform and user base, we have created new platform called uAdventure: an SG editor built on top of the game engine Unity that allows for the creation of educational adventure games without requiring programming. Since Unity is supported on a majority of platforms (including mobile). By developing SGs with uAdventure, the games become future-proof, as they can be updated and retargeted for new platforms as required. In this sense, uAdventure improves the lifecycle of SGs by reducing both authoring and maintenance costs.
Game learning analytics has a great potential to provide insight and improve the use of games in different educational situations. However, it is necessary to clearly establish what the learner's requirements are and to set realistic expectations about the learning process and outcomes. Application of game learning analytics requires pedagogically informed policies that settle the learning goals and relate them to analysis and visualization; and a supporting infrastructure that provides the mechanism on top of which it is executed. Both concerns can be addressed separated: on the one hand, there is a Learning Analytics Model (LAM) which describes how the analysis is carried out, interpreted as learning, and presented to stakeholders; and on the other hand, an underlying analytics system that concentrates on performance, security, flexibility and generality. An important advantage of this separation is that it allows LAM authors to concentrate on their area of expertise, limiting their exposition to the actual mechanism used underneath. However, LAMs built for a single game fail to account for the frequent case where games and their analytics are aggregated into larger, overarching plots, games or courses. This work describes an extension to an existing game learning analytics system, used in RAGE and BEACONING H2020 projects, which manages multilevel analytics through improvements to both policy and mechanism; and introduces meta-Learning Analytic Models, which characterize learning in hierarchical structures.
Serious games validation is a highly complex and burdensome process. To ensure that games meet their intended educational goals, it is necessary to have a clear experimental design and the necessary tools to minimize the errors that may appear in the process. In this article, after describing the most common problems that we have found while validating our own games, we present Simva, a tool designed to simplify the process of validating serious games with formal questionnaires and relating them with learning analytics data, reducing time, cost, and error rates. Serious Games; experiments; validation; learning analytics; game-based learning;I.
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 educational 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 integrated 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.
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