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Articles by Norhaslinda Kamaruddin
Total Records ( 3 ) for Norhaslinda Kamaruddin
  Norhaslinda Kamaruddin and Abdul Wahab Abdul Rahman
  Effective learning for children requires the matching of both teaching and learning style in such a way that both teachers and learners can enjoy and absorb the knowledge. Young aged children may not be able to understand the different learning styles, hence, disregard its adoption in learning. Such situation may slow down the children rate of understanding of the learned subject. Moreover, teachers need to manage the learning environment to suit the children learning needs to optimize absorption of information. With variety of education aids that are produced in a fast manner and in a large volume, it is assumed that one technique fits all is impossible to achieved. Such scenario results to the unfulfilled lesson plan objective because each individual has their individual learning style to adapt with the contents. Hence, learning style analytics is required to help teachers to channel their effort for better information dissemination and selection of suitable educational tools. This research focuses on investigating the different characterizations of learning style and suitable learning stimuli to ignite the brain activation function, especially, for children where they may not even understand the different learning styles. It will distinguish the impact of different learning stimuli to the different brain signals reflected by various learning style. The different learning style analytics will help teachers to be able to optimize the learning style for each group of students. The brain activation is mapped onto the affective space model because emotion influences learning motivation. The valence and arousal axes of the affective space model will be plotted and compare with learner’s style analytics. The validation of the proposed model is presented by modelling the correlation between learning style and emotion using neurophysiological input from Electroencephalogram (EEG). In the future, the proposed model can be used by learners for self-assessment to reflect continuous learning improvement and for teachers to plan supporting intervention for better teaching pedagogy. This aspiration is in line with the direction of Ministry of Education to transform Malaysia’s education in preparation for the future education needs moving forward to industrial revolution (IR4.0).
  Abdul Wahab , Norhaslinda Kamaruddin and Nurul Izzati Mat Razi
  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.
  Norhaslinda Kamaruddin , Abdul Wahab , Muhammad Jaliluddin Mazlan and Norul Ayny Norzilan
  Culture refers to the cumulative knowledge, beliefs, values and concepts that are accepted by a group of people. Such information are shared and inherited from the previous generations in order for one to be blended and accepted in a society. Different cultural groups communicate differently that is distinct and unique making homogeneous interpretation of underlying emotional contents are more accurate. However, universality of cultural-influenced speech can be observed when cross cultural speeches are being interacted from different cultural groups to one another especially with the advancement of communication technology. In this study, two different cultural-influenced speech datasets representing American (NTU-American) and European (Netherland EmoSpeech) are employed to investigate their similarity and dissimilarity in term of heterogeneous listener’s perception on the underlying emotional contents. The Mel Frequency Cepstral Coefficient (MFCC) feature extraction method and Multi Layer Perceptron (MLP) classifier are coupled to determine four different emotions, namely; anger, happiness, sadness and neutral acting as emotionless state. From the experimental result, it is noted that the proposed approach yielded accuracy performance of two times better than chance guessing. Moreover, the Netherland EmoSpeech dataset managed to obtain comparative accuracy with the established NTU-American dataset demonstrating that the data is satisfactory for speech emotion recognition purposes.
 
 
 
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