Supervisor System for New Generation Mobile Educational Games

OData support
Supervisor:
Dr. Forstner Bertalan
Department of Automation and Applied Informatics

Nowadays the market is flooded with ever-renewing mobile devices, whose new functions and features may seem hard to follow. Due to the intense development and great investments in this field, one can hardly find a part of everyday life where these devices cannot be at our aid. There is a substantial demand for smart phones, which come with new and new features, more processing speed, more storage and better looking displays. With the help of this technology learning methods and techniques can also be excessively modernized, so that they become even more efficient.

Currently I take part in a project, in which these two scientific fields are targeted in a way that we are developing a system on mobile technology, which can be used as a tool to support a new method of learning for children with learning disorders and difficulties. We aim at providing the opportunity of learning through playing with the help of devices currently available on market, for example Android-based tablets. During the gameplay we not only intend to record the interactions between the player and the game, but we also would like to examine the actual mental state of the player, which can also be used to alter game scenarios. An easy-mountable headset is placed on the player that measures brain activity, and may influence the difficulty of the current game. This is called biofeedback.

Because of the great complexity that comes with this method, there is a need for a supervisor system that provides information about the current state of both the player and the game to a teacher or mentor. This information may consist of various types of data such as the current feelings of the player, or details about the current game session. The work I carried out for this project includes the creation and development of a supervisor system that effectively monitors the game and the player. Furthermore I have spent significant amount of time developing the mental workload extraction and processing, an area of which I am going to provide details about.

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