An interactive system to enhance social and verbal communication skills of children withautism spectrum disorders

Affecting one in every 68 children, Autism Spectrum Disorder (ASD) is one
of the fastest growing developmental disabilities. Scientific research has proven that
early behavioral intervention can improve learning, communication, and social skills.
Similarly, studies have shown that the usage of of-the-shelf technology boosts
motivation in children diagnosed with ASD while increasing their attention span and
ability to interact socially. Embracing perspectives from different fields of study can
lead to the development of an effective tool to complement traditional treatment
of those with ASD. This thesis documents the re-engineering, extension, and evolu-
tion of Ying, an existing web application designed to aid in the learning of autistic
children. The original methodology of Ying combines expertise from other research
areas including developmental psychology, semantic learning, and computer science.
In this work, Ying is modifed to incorporate aspects of traditional treatment, such
as Applied Behavior Analysis. Using cutting-edge software technology in areas like
voice recognition and mobile device applications, this project aspires to use software
engineering approaches and audio-visual interaction with the learner to enhance social behavior and reinforce verbal communication skills in children with ASD, while
detecting and storing learning patterns for later study.