Amplifying applied game development and uptake

The established (digital) leisure game industry is historically one dominated by large international hardware vendors (e.g. Sony, Microsoft and Nintendo), major publishers and supported by a complex network of development studios, distributors and retailers. New modes of digital distribution and development practice are challenging this business model and the leisure games industry landscape is one experiencing rapid change. The established (digital) leisure games industry, at least anecdotally, appears reluctant to participate actively in the applied games sector (Stewart et al., 2013). There are a number of potential explanations as to why this may indeed be the case including ; A concentration on large-scale consolidation of their (proprietary) platforms, content, entertainment brand and credibility which arguably could be weakened by association with the conflicting notion of purposefulness (in applied games) in market niches without clear business models or quantifiable returns on investment. In contrast, the applied games industry exhibits the characteristics of an emerging, immature industry namely: weak interconnectedness, limited knowledge exchange, an absence of harmonising standards, limited specialisations, limited division of labour and arguably insufficient evidence of the products efficacies (Stewart et al., 2013; Garcia Sanchez, 2013) and could, arguably, be characterised as a dysfunctional market. To test these assertions the Realising an Applied Gaming Ecosystem (RAGE) project will develop a number of self contained gaming assets to be actively employed in the creation of a number of applied games to be implemented and evaluated as regional pilots across a variety of European educational, training and vocational contexts. RAGE is a European Commission Horizon 2020 project with twenty (pan European) partners from industry, research and education with the aim of developing, transforming and enriching advanced technologies from the leisure games industry into self-contained gaming assets (i.e. solutions showing economic value potential) that could support a variety of stakeholders including teachers, students, and, significantly, game studios interested in developing applied games. RAGE will provide these assets together with a large quantity of high-quality knowledge resources through a self-sustainable Ecosystem, a social space that connects research, the gaming industries, intermediaries, education providers, policy makers and end-users in order to stimulate the development and application of applied games in educational, training and vocational contexts. The authors identify barriers (real and perceived) and opportunities facing stakeholders in engaging, exploring new emergent business models ,developing, establishing and sustaining an applied gaming eco system in Europe.

Expressing Sentiments in Game Reviews

Opinion mining and sentiment analysis are important research areas of Natural Language Processing (NLP) tools and have become viable alternatives for automatically extracting the affective information found in texts. Our aim is to build an NLP model to analyze gamers’ sentiments and opinions expressed in a corpus of 9750 game reviews. A Principal Component Analysis using sentiment analysis features explained 51.2 % of the variance of the reviews and provides an integrated view of the major sentiment and topic related dimensions expressed in game reviews. A Discriminant Function Analysis based on the emerging components classified game reviews into positive, neutral and negative ratings with a 55 % accuracy.

Game Learning Analytics: Learning Analytics for Serious Games

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.

The RAGE Software Asset Model and Metadata Model

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.