Classification algorithm for biofeedback framework

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

Children with learning disabilities (e.g. dyscalculia, dyslexia) perform worse in school than others who are healthy, but their abilities can be improved significantly with the help of special education. Special educators find learning games the most effective way to help children learn. Computerized learning games are becoming more and more popular, but they have a common drawback: their users don’t always have an experience of flow, as in the lack of feedback, the computer is unable to determine how difficult the student finds each exercise.

Our goal is to develop an Android learning game framework for children with a learning disability, which uses the student’s physiological signals as feedback to calculate the difficulty level of each exercise optimally by determining the student's mental state using a classification algorithm. A game for children with dyscalculia is also in development using the framework, based on the professional experience of special educators who cooperate in the project.

Downloads

Please sign in to download the files of this thesis.