Title of article :
Kolb’s Learning Style correlate to Extraversion using EEG and Clustering Analysis
Author/Authors :
Abdul Rashid, N. University Technology Malaysia - Faculty of Biosciences and Bioengineering, Malaysia , Taib, M.N. Universiti Teknologi MARA - Electrical Engineering Faculty, Malaysia , Murat, Z. H. Universiti Teknologi MARA - Electrical Engineering Faculty, Malaysia , Abdul Kadir, R. S. S. Universiti Teknologi MARA - Electrical Engineering Faculty, Malaysia , Lias, S. Universiti Teknologi MARA - Electrical Engineering Faculty, Malaysia , Sulaiman, N. Universiti Teknologi MARA - Electrical Engineering Faculty, Malaysia
Abstract :
Individual Learning style (LS) had gained an enormous attention as learning process became more independent and student-centered. Furthermore, studies had shown that a congruence learning and teaching style could lead to a successful learning process. One of the frequently used instruments to determine student’s LS is Kolb’s Learning Style Inventory (LSI). According to the Kolb’s model, the LSI would establish the LS of Diverger, Assimilator, Converger or Accommodator. On the other hand, Personality Traits had been considered as one of the student’s important attribute. As such, several studies had been embarked to find the relationship between LS and Personality Traits but it were always confined to the usage of traditional instruments mostly adopting questionnaire-based methodology. In this research, the LS and Personality Traits were correlated using Electroencephalogram (EEG) technology. Initially, the participants’ LS (N=41) were determined using Kolb’s LSI. Then their brainwaves were recorded at baseline resting condition of Open Eyes and Closed Eyes using EEG. The EEG Alpha band was selected and analyze using SPSS 2Step Cluster analysis module. The findings show that 100% clustering had been achieved and Converger and Accommodator had been correctly detected as the Extraversionbound LS in most experiment.
Keywords :
Learning style , Personality Traits , Extraversion , EEG , Clustering
Journal title :
International Journal Of Electrical and Electronic Systems Research
Journal title :
International Journal Of Electrical and Electronic Systems Research