This document describes the core components to create customizable game analytics and dashboards: their present status; links to their full designs and downloadable versions; and how to configure them, and take advantage of the analytics visualizations and the underlying architecture of the platform. All the dashboard components are working with data collected using the xAPI data format that the RAGE project has developed in collaboration with ADL Co-Lab. ; This study is part of the RAGE project. The RAGE project has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 644187. This publication reflects only the author's view. The European Commission is not responsible for any use that may be made of the information it contains.
For seizing the potential of serious games, the RAGE project - funded by the Horizon-2020 Programme of the European Commission - will make available an interoperable set of advanced technology components (software assets) that support game studios at serious game development. This paper describes the overall software architecture and design conditions that are needed for the easy integration and reuse of such software assets in existing game platforms. Based on the component-based software engineering paradigm the RAGE architecture takes into account the portability of assets to different operating systems, different programming languages and different game engines. It avoids dependencies on external software frameworks and minimizes code that may hinder integration with game engine code. Furthermore it relies on a limited set of standard software patterns and well-established coding practices. The RAGE architecture has been successfully validated by implementing and testing basic software assets in four major programming languages (C#, C++, Java and Typescript/JavaScript, respectively). A demonstrator implementation of asset integration with an existing game engine was created and validated. The presented RAGE architecture paves the way for large scale development and application of cross-engine reusable software assets for enhancing the quality and diversity of serious gaming. ; This study is part of the RAGE project. The RAGE project has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 644187. This publication reflects only the author's view. The European Commission is not responsible for any use that may be made of the information it contains.
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. ; This study is part of the RAGE project. The RAGE project has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 644187. This publication reflects only the author's view. The European Commission is not responsible for any use that may be made of the information it contains.
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. ; This study is part of the RAGE project. The RAGE project has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 644187. This publication reflects only the author's view. The European Commission is not responsible for any use that may be made of the information it contains.
This document describes the final bundle of dashboard components used to create customizable analytics and dashboards. This deliverable describes the main RAGE components (previously described as assets) regarding dashboard components. The final state of the architecture provides a default set of game-independent visualizations that can be applied to a whole range of different applied games. Moreover, those visualizations can be extended and adapted to include game-dependent visualizations if needed for specific requirements. All the dashboard components are ready to work with data collected using the Experience API Serious Game Profile (xAPI-SG) that has been developed in the project in collaboration with ADL (USA). This deliverable updates the previous deliverable on dashboard components (D2.5), and details the final descriptions, status and links to their full designs and downloadable versions, as well as how to configure and create specific visualizations. Notice that as in all open software projects, the most up-to-date version of components is always available online at the open public repository (i.e. in our case GitHub), as improvements may occur until the end of the project and beyond. Also note that, to improve readability, this deliverable briefly describes the client (game tracker) and the server-side (storage and analysis) analytics. The dashboard components consider several issues to comply with the regulations and the security guidelines defined in RAGE (including aspects of anonymization when possible) and to comply with the law on personal data storage and protection in accordance with EC data regulations (GDPR, 2016)-(Article 29, 2018). ; This study is part of the RAGE project. The RAGE project has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 644187. This publication reflects only the author's view. The European Commission is not responsible for any use that may be made of the information it contains.
Learning Analytics is an emerging field focused on analyzing learners' interactions with educational content. One of the key open issues in learning analytics is the standardization of the data collected. This is a particularly challenging issue in serious games, which generate a diverse range of data. This paper reviews the current state of learning analytics, data standards and serious games, studying how serious games are tracking the interactions from their players and the metrics that can be distilled from them. Based on this review, we propose an interaction model that establishes a basis for applying Learning Analytics into serious games. This paper then analyzes the current standards and specifications used in the field. Finally, it presents an implementation of the model with one of the most promising specifications: Experience API (xAPI). The Experience API relies on Communities of Practice developing profiles that cover different use cases in specific domains. This paper presents the Serious Games xAPI Profile: a profile developed to align with the most common use cases in the serious games domain. The profile is applied to a case study (a demo game), which explores the technical practicalities of standardizing data acquisition in serious games. In summary, the paper presents a new interaction model to track serious games and their implementation with the xAPI specification. ; This study is part of the RAGE project. The RAGE project has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 644187. This publication reflects only the author's view. The European Commission is not responsible for any use that may be made of the information it contains.
Video games have become one of the largest entertainment industries, and their power to capture the attention of players worldwide soon prompted the idea of using games to improve education. However, these educational games, commonly referred to as serious games, face different challenges when brought into the classroom, ranging from pragmatic issues (e.g. a high development cost) to deeper educational issues, including a lack of understanding of how the students interact with the games and how the learning process actually occurs. This chapter explores the potential of data-driven approaches to improve the practical applicability of serious games. Existing work done by the entertainment and learning industries helps to build a conceptual model of the tasks required to analyze player interactions in serious games (gaming learning analytics or GLA). The chapter also describes the main ongoing initiatives to create reference GLA infrastructures and their connection to new emerging specifications from the educational technology field. Finally, it explores how this data-driven GLA will help in the development of a new generation of more effective educational games and new business models that will support their expansion. This results in additional ethical implications, which are discussed at the end of the chapter. ; This study is part of the RAGE project. The RAGE project has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 644187. This publication reflects only the author's view. The European Commission is not responsible for any use that may be made of the information it contains.
This deliverable (D1.4) is an intermediate document, expressly included to inform the first project review about RAGE's methodology of software asset creation and management. The final version of the methodology description (D1.1) will be delivered in Month 29. The document explains how the RAGE project defines, develops, distributes and maintains a series of applied gaming software assets that it aims to make available. It describes a high-level methodology and infrastructure that are needed to support the work in the project as well as after the project has ended. ; This study is part of the RAGE project. The RAGE project has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 644187. This publication reflects only the author's view. The European Commission is not responsible for any use that may be made of the information it contains.
This document describes the final bundle of client-side components, including descriptions of their functionality, and links to their full designs and downloadable versions. This bundle aggregates only the WP2 assets. Other client-side assets not covered here will be addressed in the final WP3 deliverables. Those assets created and licenced as open software will be continuously improved and maintained by their creators until the end of the project (the task has been extended to month 48) and beyond. For a full description of the related server-side components, please refer to D2.2 - Final Bundle of Server-side Components. ; This study is part of the RAGE project. The RAGE project has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 644187. This publication reflects only the author's view. The European Commission is not responsible for any use that may be made of the information it contains.
Together with the intermediate deliverable D1.4 (Month 18), this document explains how the RAGE project defines, develops, distributes and maintains a series of applied gaming software assets through a high-level methodology and infrastructure that are needed to support the work in the project, as well as after the project has ended. The asset creation methodology, the quality assurance considerations and the asset metadata requirements are merged together and implemented into a single asset creation wizard, which supports and guides asset owners through the process of asset submission to the Ecosystem portal. It complements the metadata editor that was developed earlier, but which in some respects turned out to be demanding for asset developers. The wizard was used and evaluated by all RAGE's asset developers. Also, the metadata-viewer tool is briefly explained in this deliverable. Already before the (soft) external launch of the ecosystem portal, which is scheduled in month 36 (January 2018) external parties will be involved to explore the asset creation system and make judgements about its usability. Overall, the asset creation part and its alignment with the RAGE ecosystem portal has now been fully covered. ; This study is part of the RAGE project. The RAGE project has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 644187. This publication reflects only the author's view. The European Commission is not responsible for any use that may be made of the information it contains.
