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    A pictorial mobile application for improving communication skills in non-verbal autism

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    Date
    2015
    Author
    Abou El-Seoud, Samir
    Karkar, AbdelGhani
    Al Ja'am, Jihad
    Karam, Omar
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    Abstract
    It is estimated that as many as 25 percent of individuals living with autism spectrum disorders are nonverbal. That is, they cannot functionally communicate with others using their voice. Despite that substantial fraction, we still know very little about these individuals, their abilities, and their needs. "We still know very little about the cognitive capabilities of nonverbal people with autism, and how best to help them learn to communicate," said Geri Dawson, Ph.D., Autism Speaks chief science officer. communicate normally using natural languages. They can, however, learn to communicate through specific symbols and images. Special education instructors have adopted this method of communication to teach non-verbal people with autism. They introduce the symbols and images to them through different methodologies. This learning process appeared to be effective but it is very long. The process is carried out manually and requires a lots of times, dedication, and resources. The instructors should find the materials in different formats and circumstances. They should repeat the lessons several times and normally in a faceto- face framework. We propose in this paper a mobilebased application that allows non- verbal people with autism to learn and communicate with their surroundings using a smart device. They can then be taught to use specific symbols and images through the smart mobile phones. They can form simple words and sentences to express their feelings and needs. The application is flexible and allows the addition of new contents very easily. To assess the progress of the users, different exercises and puzzles are proposed. These allow the users to improve their skills and to continue learning outside the classrooms.
    DOI/handle
    http://dx.doi.org/10.3991/ijim.v9i4.4699
    http://hdl.handle.net/10576/53250
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    • Computer Science & Engineering [‎2428‎ items ]

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