66 research outputs found

    Flavor text generation for role-playing video games

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    Game Design Patterns for Learning

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    Kelle, S. (2012). Game Design Patterns for Learning. November, 9, 2012, Heerlen, The Netherlands: Open Universiteit in the Netherlands, CELSTEC. Aachen: Shaker Verlag.What do learning games consist of? How to design learning games and what to keep in mind? How to balance educational objectives with good gameplay? What to do if you are a game designer and you want to use e-learning standards for your game? And what to do if you are an instructional designer and you are in desperate need to gamify your content? This publication aims at illuminating these questions, presenting results from a 4 year long PhD project run at CELSTEC, the Center of Learning Sciences and Technologies at the Open University of The Netherlands. Sebastian Kelle is a multidisciplinary researcher, currently building up a new center for higher education didactics at Stuttgart Media University.EU ICOPER Projec

    Game Design Patterns for Learning

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    This demonstration presents a novel interactive online shopping application based on visual search technologies. When users want to buy something on a shopping site, they usually have the requirement of looking for related information from other web sites. Therefore users need to switch between the web page being browsed and other websites that provide search results. The proposed application enables users to naturally search products of interest when they browse a web page, and make their even causal purchase intent easily satisfied. The interactive shopping experience is characterized by: 1) in session - it allows users to specify the purchase intent in the browsing session, instead of leaving the current page and navigating to other websites; 2) in context - -the browsed web page provides implicit context information which helps infer user purchase preferences; 3) in focus - users easily specify their search interest using gesture on touch devices and do not need to formulate queries in search box; 4) natural-gesture inputs and visual-based search provides users a natural shopping experience. The system is evaluated against a data set consisting of several millions commercial product images. © 2012 Authors

    Design Strategies for Adaptive Social Composition: Collaborative Sound Environments

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    In order to develop successful collaborative music systems a variety of subtle interactions need to be identified and integrated. Gesture capture, motion tracking, real-time synthesis, environmental parameters and ubiquitous technologies can each be effectively used for developing innovative approaches to instrument design, sound installations, interactive music and generative systems. Current solutions tend to prioritise one or more of these approaches, refining a particular interface technology, software design or compositional approach developed for a specific composition, performer or installation environment. Within this diverse field a group of novel controllers, described as ‘Tangible Interfaces’ have been developed. These are intended for use by novices and in many cases follow a simple model of interaction controlling synthesis parameters through simple user actions. Other approaches offer sophisticated compositional frameworks, but many of these are idiosyncratic and highly personalised. As such they are difficult to engage with and ineffective for groups of novices. The objective of this research is to develop effective design strategies for implementing collaborative sound environments using key terms and vocabulary drawn from the available literature. This is articulated by combining an empathic design process with controlled sound perception and interaction experiments. The identified design strategies have been applied to the development of a new collaborative digital instrument. A range of technical and compositional approaches was considered to define this process, which can be described as Adaptive Social Composition. Dan Livingston

    Generic adaptation framework for unifying adaptive web-based systems

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    The Generic Adaptation Framework (GAF) research project first and foremost creates a common formal framework for describing current and future adaptive hypermedia (AHS) and adaptive webbased systems in general. It provides a commonly agreed upon taxonomy and a reference model that encompasses the most general architectures of the present and future, including conventional AHS, and different types of personalization-enabling systems and applications such as recommender systems (RS) personalized web search, semantic web enabled applications used in personalized information delivery, adaptive e-Learning applications and many more. At the same time GAF is trying to bring together two (seemingly not intersecting) views on the adaptation: a classical pre-authored type, with conventional domain and overlay user models and data-driven adaptation which includes a set of data mining, machine learning and information retrieval tools. To bring these research fields together we conducted a number GAF compliance studies including RS, AHS, and other applications combining adaptation, recommendation and search. We also performed a number of real systems’ case-studies to prove the point and perform a detailed analysis and evaluation of the framework. Secondly it introduces a number of new ideas in the field of AH, such as the Generic Adaptation Process (GAP) which aligns with a layered (data-oriented) architecture and serves as a reference adaptation process. This also helps to understand the compliance features mentioned earlier. Besides that GAF deals with important and novel aspects of adaptation enabling and leveraging technologies such as provenance and versioning. The existence of such a reference basis should stimulate AHS research and enable researchers to demonstrate ideas for new adaptation methods much more quickly than if they had to start from scratch. GAF will thus help bootstrap any adaptive web-based system research, design, analysis and evaluation

    Model-Driven Development of Interactive Multimedia Applications

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    The development of highly interactive multimedia applications is still a challenging and complex task. In addition to the application logic, multimedia applications typically provide a sophisticated user interface with integrated media objects. As a consequence, the development process involves different experts for software design, user interface design, and media design. There is still a lack of concepts for a systematic development which integrates these aspects. This thesis provides a model-driven development approach addressing this problem. Therefore it introduces the Multimedia Modeling Language (MML), a visual modeling language supporting a design phase in multimedia application development. The language is oriented on well-established software engineering concepts, like UML 2, and integrates concepts from the areas of multimedia development and model-based user interface development. MML allows the generation of code skeletons from the models. Thereby, the core idea is to generate code skeletons which can be directly processed in multimedia authoring tools. In this way, the strengths of both are combined: Authoring tools are used to perform the creative development tasks while models are used to design the overall application structure and to enable a well-coordinated development process. This is demonstrated using the professional authoring tool Adobe Flash. MML is supported by modeling and code generation tools which have been used to validate the approach over several years in various student projects and teaching courses. Additional prototypes have been developed to demonstrate, e.g., the ability to generate code for different target platforms. Finally, it is discussed how models can contribute in general to a better integration of well-structured software development and creative visual design

    AI in Learning: Designing the Future

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    AI (Artificial Intelligence) is predicted to radically change teaching and learning in both schools and industry causing radical disruption of work. AI can support well-being initiatives and lifelong learning but educational institutions and companies need to take the changing technology into account. Moving towards AI supported by digital tools requires a dramatic shift in the concept of learning, expertise and the businesses built off of it. Based on the latest research on AI and how it is changing learning and education, this book will focus on the enormous opportunities to expand educational settings with AI for learning in and beyond the traditional classroom. This open access book also introduces ethical challenges related to learning and education, while connecting human learning and machine learning. This book will be of use to a variety of readers, including researchers, AI users, companies and policy makers
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