Authors : Abdul Wahab, Norhaslinda Kamaruddin and Nurul Izzati Mat Razi
Abstract: Many developing countries are looking at means and ways to implement inclusive education, although, most do not seem to understand on the way to handle different learning abilities of individuals. Normal children with average learning capabilities may be generalized to a common learning experience but individuals with Learning Disabilities (LD) cannot cope with the learning capabilities of the normal children. It is thus, important to introduce personalized learning for individual such that students with different LD can effectively learn at their own pace, although, in an inclusive environment. Thus, this study takes the opportunity to understand the brain functionality and to allow student to be profiled for differentiated learning experience. The availability of Electroencephalogram (EEG) devices and its ability to measure and capture brain waves for analysis makes it easier for researchers to use them in understanding the functionality and state of the brain. The mobility and low-cost EEG devices, recently, makes it attractive for researchers and teachers in the long run to provide profiling of every students. In general, this can help students to self-pace their learning experience. Moreover, various engineering tools and method were also introduced to improve the performance of the detection system for early childhood developmental disorder. In this research, 10 students with Autism Spectrum Disorder (ASD) and normal children were measured for brain wave pattern differences through, the use of EEG in detecting ASD. An extended application of the EEG processing using the neurophysiological interface of affect were also, used to understand behavior through personality traits providing new avenue and possibilities of profiling students effectively.
Abdul Wahab, Norhaslinda Kamaruddin and Nurul Izzati Mat Razi, 2019. Profiling Students for Effective Learning based on Neuro-Physiological Interface of Affect. Journal of Engineering and Applied Sciences, 14: 6160-6164.