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Simplifying location-based serious game authoring

Authors: Víctor Manuel Pérez-Colado; Iván José Pérez-Colado; Iván Martínez-Ortiz; Manuel Freire-Morán; Baltasar Fernández-Manjón;

Simplifying location-based serious game authoring

Abstract

Pervasive gaming has been a field of exploration for the gaming industry the recent years. With the exceptional success of Pokémon GO and some others such as Ingress users are more than ever ready to experiment with games that are more focused into their actions and their playing contexts. In the serious game industry, the implementation of pervasive games is a very promising way to improve students learning process with a more cohesive and realistic experience. To take advantage of this opportunity we have developed a model for location-based serious games intended to be used along with other game genres such the adventure one. We have implemented this model in the uAdventure (uA) authoring tool, allowing non-experts for the simple creation for location-based adventure games without programming or complex geopositioning knowledge requirements. With uA we address to simplify the creation of gymkhanas, tours or guided visits with the added value of the adventure games. Finally, to improve the quality of the games, we have incorporated learning analytics into the system and tested the platform with a small experiment that showed promising results.

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Keywords

Serious games, xAPI, Ubiquity, GPS, Augmented map, Augmented reality, Learning analytics, Location-based, Pervasive

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selected citations
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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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