Please use this identifier to cite or link to this item: https://rda.sliit.lk/handle/123456789/1525
Title: Individualized Edutainment and Parent Supportive Tool for ADHD Children
Authors: Thennakoon, A.
Perera, D.
Sugathapala, S.
Weerasingha, S.
Samarasinghe, P.
Dahanayake, D.
Piyawardan, V.S.
Keywords: ADHD
Machine learning
Attention span
Edutainment
Time management
Learning disabilities
Issue Date: 10-Dec-2020
Publisher: 2020 2nd International Conference on Advancements in Computing (ICAC), SLIIT
Series/Report no.: Vol.1;
Abstract: Attention-Deficit/Hyperactivity Disorder (ADHD) is a comorbid disorder that can impact a child and his/her family. ADHD children have considerable obstacles in managing time, understanding instructions, and paying attention to the activities. To address these perplexities, this research has designed a mobile application to help parents to have better interaction with the children and for the children to enjoy their learning activities. The specialty of this application is the models are trained on individual child skills and needs. Issues with time management are handled by the Scheduler component while the Instruction Predictor module supports the parent in recognizing the child's understandability level. Furthermore, the children are provided with edutainment activities based on their attention and ability levels. Different models have been used in predicting the results through these modules and the prediction result accuracy exceeds 90% in most of the cases. Out of the many models, The Random Forest model resulted in the best overall performance. The application was tried by many parents and health professionals and received satisfactory and commendable reviews.
URI: 978-1-7281-8412-8
http://rda.sliit.lk/handle/123456789/1525
Appears in Collections:2nd International Conference on Advancements in Computing (ICAC) | 2020
Research Papers - Department of Civil Engineering
Research Papers - IEEE
Research Publications -Dept of Information Technology

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