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Detection of learning curves of player metrics is very important for the serious (or so called applied) games, because it provides an indicator representing how players master the game tasks by acquiring cognitive abilities, knowledge, and necessary skills for solving the game challenges. Real time identification of specific patterns in the learning curve of a particular player may be applied for dynamic adjusting of learning task difficulty and audio-visual features of the game. The paper presents a method for automatic and straightforward detection of specific learning curves at run time within a 3D video game of car driving in various weather conditions. The method uses a client-side software component called "Player-centric rule-and-pattern-based adaptation asset" and developed in the scope of the RAGE (Realising and Applied Gaming Ecosystem) H2020 project. This component is integrated within the video game in order to detect dynamically specific player learning curve patterns of moving average of overall player performance. The paper explains how these patterns were identified while players play the game and, next, how are defined formally within the asset for a detection at run time. The presented results show that the patterns are found in consecutive game sessions, although the changes in player performance and playing time. ; 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.

In recent years, the interest to the area of computer games for educational purposes increased due to their positive outcomes and effects in technology-enhanced learning. One of their chief merits is retaining the learning motivation and engagement of players during all time of the game. Therefore, it is necessary educational games to be able to adjust their features such as task difficulty, object speed, learning content, etc. according to the current emotional state of the player and, as well, to his/her playing style. In this paper, we present a dynamic mechanism for affective game adaptation based on both emotion and arousal estimation. The mechanism is implemented within an applied video game named "Rush for Gold" designed for implicit recognition of playing or learning styles. The paper outlines, analyzes and discusses results of an experimental study related to player´s engagement in affective applied adaptation. ; 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.

In recent years, many researchers have reported positive outcomes and effects from applying computer games to the educational process. The main preconditions for an effective game-based learning process include the presence of high learning interest and the desire to study hard. Therefore, educational game design has to tailor gameplay to the psycho-cognitive abilities, attitudes and skills of an individual player, in order to foster the player's motivation and creativity. To achieve this goal, it is necessary to draw a parallel between learning and playing styles, and to investigate the correlations between these types of constructs. The article presents a new playing style family based on Kolb's experiential learning theory that is appropriate to be used for educational games. This family is composed of four playing styles: Competitor, Dreamer, Logician and Strategist, and corresponds to Honey and Mumford's learning styles. To measure the four playing styles, a 40-item questionnaire was designed. In order to verify the consistency, validity, and reliability of that questionnaire as an accurate tool for recognizing the four suggested player styles, a pilot study was conducted. The article reports the results obtained from the study, along with their analysis and applicability. ; 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 first bundle of core WP2 (user data analytics) client side components, including their specifications, usecases, and working prototypes. Included assets contain a description of their current status, and links to their full designs and downloadable versions. This deliverable only describes operational SW assets (even though beta) that are tested and documented. It should be noted, however, that various additional software assets (2.2d Cognitive Capacity Measurement and 2.3a Realtime Emotion Detection) are near completion for inclusion in games during the first pilot round. Those assets are still scheduled for inclusion in the final bundle deliverable D2.2. ; 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 is the first out of three iterations of the DMP that will be formally delivered during the project. Version 2 is due in month 24 and version 3 towards the end of the project. The DMP thus is not a fixed document; it evolves and gains more precision and substance during the lifespan of the project. In this first version we describe the planned research data sets related to the RAGE evaluation and validation activities, and the fifteen principles that will guide data management in RAGE. The former are described in the format of the EU data management template, and the latter in terms of their guiding principle, how we propose to implement them, and when they will be implemented. This document is thus first of all relevant to WP5 and WP8 members. ; This publication has been produced in the context of the RAGE project. The project has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 644187. However, this deliverable reflects only the author's view and the European Commission is not responsible for any use that may be made of the information it contains.

This document is the second out of three iterations of the DMP that will be formally delivered during the project. Version 3 is due towards the end of the project. The DMP thus is not a fixed document; it evolves and gains more precision and substance during the lifespan of the project. This version 2 of the DMP is informed by the following project results: 1) In January 2016 WP8 delivered D8.1 - RAGE Evaluation Framework and Guidelines including extensive guidelines on how to apply the principles of ethics, privacy and open access in the RAGE evaluations; 2) In July 2016 the Executive Management Board selected the OpenAIRE-Zenodo as the preferred open access repository to manage the consortium's research data. The selection of Zenodo addresses a number of issues that were left open in version 1 of this DMP; 3) In November 2016 WP8 delivered the MS8 - First Pilot Validation Instruments document, outlining procedures and tools to be used in the pilot evaluations, including a chapter on the use of Zenodo. The MS8-document provides an update of the data sets that will be generated as part of the pilot evaluations, as compared to the data sets initially specified in version 1 of this DMP. This document is thus first of all relevant to WP5 and WP8 members. ; 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 paper describes the structural architecture of the RAGE repository, which is a unique and dedicated infrastructure that provides access to a wide variety of advanced technologies (RAGE software assets) for applied game development. These software assets are reusable across a wide diversity of game engines, game platforms and programming languages. The RAGE repository allows applied game developers and studios to search for software assets for inclusion in applied games. The repository is designed as an asset life-cycle management system for defining, publishing, updating, searching and packaging for distribution of these assets. The RAGE repository provides storage space for assets and their artefacts. It will be embedded in a social platform for networking among asset developers and other users. A dedicated Asset Repository Manager provides the main functionality of the repository and its integration with other systems. Tools supporting the Asset Manager are presented and discussed. When the RAGE repository is in full operation, applied game developers will be able to easily enhance the quality of their games by including advanced game technology assets. ; 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 presents and describes the first delivery of assets that are part of the core social agency bundle. In total, the bundle includes 16 assets, divided into 4 main categories. Each category is related to a type of challenge that developers of applied games are typically faced with and the aim of the included assets is to provide solutions to those challenges. The main goal of this document is to provide the reader with a description for each included asset, accompanied by links to their source code, distributable versions, demonstrations and documentation. A short discussion of what are the future steps for each asset is also given. The primary audience for the contents of this deliverable are the game developers, both inside and outside of the project, which can use this document as an official list of the current social agency assets and their associated resources. Note that the information about which RAGE use cases are using which of these assets is described in Deliverable 4.2. ; 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 paper presents the architecture of the RAGE repository, which is a unique and dedicated infrastructure that provides access to a wide variety of advanced technology components for applied game development. The RAGE project, which is the principal Horizon2020 research and innovation project in applied gaming, will develop software components (RAGE software assets) that are reusable across a variety of game engines, game platforms and programming languages. The RAGE repository provides storage space for these assets and associated artefacts and is designed as an asset life-cycle management system for defining, publishing, updating, searching and packaging for distribution of the assets. The repository will be embedded in a social platform for asset developers and other stakeholders. A dedicated Asset Repository Manager provides the main functionality of the repository and its integration with other systems. Additional Tools supporting the Asset Manager are also presented and discussed. When the RAGE repository is fully operational, applied game developers will be able to enhance the quality of their games through the application of selected advanced game software assets. By making available the RAGE repository system and software assets the RAGE project's aim is to stimulate the development and uptake of the Applied Games Industry in Europe. ; 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.

Software assets are key output of the RAGE project and they can be used by applied game developers to enhance the pedagogical and educational value of their games. These software assets cover a broad spectrum of functionalities – from player analytics including emotion detection to intelligent adaptation and social gamification. In order to facilitate integration and interoperability, all of these assets adhere to a common model, which describes their properties through a set of metadata. In this paper the RAGE asset model and asset metadata model is presented, capturing the detail of assets and their potential usage within three distinct dimensions – technological, gaming and pedagogical. The paper highlights key issues and challenges in constructing the RAGE asset and asset metadata model and details the process and design of a flexible metadata editor that facilitates both adaptation and improvement of the asset metadata model. ; 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.