8 resultados para Location-based Game

em Open University Netherlands


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This paper presents and validates a methodology for integrating reusable software components in diverse game engines. While conforming to the RAGE com-ponent-based architecture described elsewhere, the paper explains how the interac-tions and data exchange processes between a reusable software component and a game engine should be implemented for procuring seamless integration. To this end, a RAGE-compliant C# software component providing a difficulty adaptation routine was integrated with an exemplary strategic tile-based game “TileZero”. Implementa-tions in MonoGame, Unity and Xamarin, respectively, have demonstrated successful portability of the adaptation component. Also, portability across various delivery platforms (Windows desktop, iOS, Android, Windows Phone) was established. Thereby this study has established the validity of the RAGE architecture and its un-derlying interaction processes for the cross-platform and cross-game engine reuse of software components. The RAGE architecture thereby accommodates the large scale development and application of reusable software components for serious gaming.

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Digital learning games are useful educational tools with high motivational potential. With the application of games for instruction there comes the need of acknowledging learning game experiences also in the context of educational assessment. Learning analytics provides new opportunities for supporting assessment in and of educational games. We give an overview of current learning analytics methods in this field and reflect on existing challenges. An approach of providing reusable software assets for interaction assessment and evaluation in games is presented. This is part of a broader initiative of making available advanced methodologies and tools for supporting applied game development.

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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.

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Although many scholars recognise the great potential of games for teaching and learning, the EU-based industry for such “serious” games” is highly fragmented and its growth figures remain well behind those of the leisure game market. Serious gaming has been designated as a priority area by the European Commission in its Horizon 2020 Framework Programme for Research and Innovation. The RAGE project, which is funded as part of the Horizon 2020 Programme, is a technology-driven research and innovation project that will make available a series of self-contained gaming software modules that support game studios in the development of serious games. As game studios are a critical factor in the uptake of serious games, the RAGE projects will base its work on their views and needs as to achieve maximum impact. This paper presents the results of a survey among European game studios about their development related needs and expectations. The survey is aimed at identifying a baseline reference for successfully supporting game studios with advanced ICTs for serious games.

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Toma, I., Dascalu, M., & Trausan-Matu, S. (2015). Seeker: A Serious Game for Improving cognitive Abilities. In 14th IEEE Int. Conf. RoEduNet (pp. 73–79). Craiova, Romania: IEEE.

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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.

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The presentation explains the approach of the RAGE project. It presents three examples of RAGE software components and how these can be easily reused for applied game development.

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The large upfront investments required for game development pose a severe barrier for the wider uptake of serious games in education and training. Also, there is a lack of well-established methods and tools that support game developers at preserving and enhancing the games’ pedagogical effectiveness. The RAGE project, which is a Horizon 2020 funded research project on serious games, addresses these issues by making available reusable software components that aim to support the pedagogical qualities of serious games. In order to easily deploy and integrate these game components in a multitude of game engines, platforms and programming languages, RAGE has developed and validated a hybrid component-based software architecture that preserves component portability and interoperability. While a first set of software components is being developed, this paper presents selected examples to explain the overall system’s concept and its practical benefits. First, the Emotion Detection component uses the learners’ webcams for capturing their emotional states from facial expressions. Second, the Performance Statistics component is an add-on for learning analytics data processing, which allows instructors to track and inspect learners’ progress without bothering about the required statistics computations. Third, a set of language processing components accommodate the analysis of textual inputs of learners, facilitating comprehension assessment and prediction. Fourth, the Shared Data Storage component provides a technical solution for data storage - e.g. for player data or game world data - across multiple software components. The presented components are exemplary for the anticipated RAGE library, which will include up to forty reusable software components for serious gaming, addressing diverse pedagogical dimensions.