The evolution and spread of Android tablets made it possible for them to be used in education. Interactive educational software, used by such tables can produce better results than traditional school-books. Amongst these, educational games are shown to be the most successful especially with the younger age groups.
Studies in neuroscience, indicates that human learning works similar to reinforcement training. Knowing this, learning efficiency can be improved with the help of biofeedback devices.
The aim of this thesis is to design a framework, which supports the development of educational games, to maximize learning by monitoring the emotional and cognitive state of the user during learning and choosing difficulty level and reward based on data collected and analyzed through biofeedback devices. A further objective is to design and develop two educational games for the framework, and to add a heart rate monitor to the list of supported biofeedback sensors.
The thesis provides an overview of neuroscience, on which the design and operation of the framework is based on. It also presents planning decisions made during the design of the framework and game architecture, including game implementation details, and how they were connected to the framework. The process of connecting the heart rate monitor and the analysis of the signal processing are also presented.