Anastasiadou, Despina

Lameras, Petros

This paper investigates the development of a classification of features inherent in the design and development of Location Based Experiences (LBEs) with a special focus on games for teaching and learning. The paper aims to identify and associate learning features, such as feedback, activities, outcomes and assessment with location-driven mechanics, such as location-based activities, entities, conditions and actions that constitute the overarching elements of a proprietary location-based games authoring tool. We anticipate that this will pave the way for developing a model taxonomy that may be utilised to support and optimise future end-user profiles for serious game creation, games design for informal learning paths in science museums, science centres and field trips, learning methodologies development and metadata creation. The classification draws on the findings of a tailored approach applied to design and develop an authoring environment, the MAGELLAN platform, for creating location-based games and mobile location-driven scenarios directly influenced by end-user requirements and evaluation of trainee's feedback. Ultimately, the classification is conceived as part of a broader framework that defines and enables the creation of location-driven games by associating them with learning elements, through visualised design for expert and non-expert users as potential game authors. In an iterative process, the MAGELLAN Authoring Tool and subsequent user training and piloting process is featured as a test-bed, where the proposed taxonomy will be applied and evaluated

Coventry University Pure Portal

Identifying and classifying learning entities for designing location-based serious games

Despina Anastasiadou

Petros Lameras

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https://pure.coventry.ac.uk/ws/files/4015715/Identifying-classifying-Anastasiadou.pdf

Identifying and classifying learning entities for designing location-based serious games

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Coventry University Pure Portal

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