Design, Large-Scale Usage Testing, and Important Metrics for Augmented Reality Gaming Applications

摘要

Augmented Reality (AR) offers the possibility to enrich the real world with digital mediated content, increasing in this way the quality of many everyday experiences. While in some research areas such as cultural heritage, tourism, or medicine there is a strong technological investment, AR for game purposes struggles to become a widespread commercial application. In this article, a novel framework for AR kid games is proposed, already developed by the authors for other AR applications such as Cultural Heritage and Arts. In particular, the framework includes different layers such as the development of a series of AR kid puzzle games in an intermediate structure which can be used as a standard for different applications development, the development of a smart configuration tool, together with general guidelines and long-life usage tests and metrics. The proposed application is designed for augmenting the puzzle experience, but can be easily extended to other AR gaming applications. Once the user has assembled the real puzzle, AR functionality within the mobile application can be unlocked, bringing to life puzzle characters, creating a seamless game that merges AR interactions with the puzzle reality. The main goals and benefits of this framework can be seen in the development of a novel set of AR tests and metrics in the pre-release phase (in order to help the commercial launch and developers), and in the release phase by introducing the measures for long-life app optimization, usage tests and hint on final users together with a measure to design policy, providing a method for automatic testing of quality and popularity improvements. Moreover, smart configuration tools, as part of the general framework, enabling multi-app and eventually also multi-user development, have been proposed, facilitating the serialization of the applications. Results were obtained from a large-scale user test with about 4 million users on a set of eight gaming applications, providing the scientific community a workflow for implicit quantitative analysis in AR gaming. Different data analytics developed on the data collected by the framework prove that the proposed approach is affordable and reliable for long-life testing and optimization.