An Optimization Model for Learning Disorder Children to Support Learning Development Plan

Headed By Dr. Ely Salwana Binti Mat Surin.

Skim Geran Penyelidikan Fundamental (FRGS)

 

 

Children with learning disorder (LD) may have problems on how to understand, remember and respond to new information. Despite of their condition, the LD children also need to be considered to make decisions on their learning development based on their ability. However, in reality the children as well as their parents have limited guidance in choosing an appropriate learning development plan. Although several studies are available for use in an educational setting, there is no specific optimization model that can be used for learning disorder in relation to learning development plan. Thus, the objective of this study is to assist them to plan for their learning development based on their talent and ability. In order to achieve it, the study was designed to develop an optimization model in order to determine and understand the ability of LD children and assist them to make a better learning development plan. The model combines the ability of deep learning algorithm to analyze the data, with a consideration on current plan used, to determine outcome-related factors. The optimization model will be developed based on classification techniques to predict LD child learning performance using deep learning which automatically learns multiple levels of representation. We will train model on a relatively large real-world LDs dataset, and the result hopefully will be contributing into the learning development plan mechanism. The model can be used to identify the ability of the LD children and suggest most suitable plan for the learning development of the children. The outcome of the study not only will assist the practitioner, LD children and their parents themselves but also can support the policy of Malaysian government to allow at least 75 per cent of children with disabilities to participate in education, both formal and informal with reasonable support services.