Appraisal of EEG Beta summative power towards Learning Style classification

• Published in: Proceedings - 2015 2nd International Conference on Biomedical Engineering, ICoBE 2015
• Main Author: Bin Abdul Rashid N.; Bin Taib M.N.; Murat Z.B.H.; Kadir R.S.B.S.A.; Bin Lias S.; Bin Sulaiman N.
• Format: Conference paper
• Language: English
• Published: Institute of Electrical and Electronics Engineers Inc. 2015
• Online Access: https://www.scopus.com/inward/record.uri?eid=2-s2.0-84962892898&doi=10.1109%2fICoBE.2015.7235124&partnerID=40&md5=55174590e0975075f26a7d252717974a
• DOI: 10.1109/ICoBE.2015.7235124

Advancement in Neuroscience namely EEG technology had been serving in education-related research with immense contributions. On the other hand, Learning Style (LS) had emerged as an important study in education frontier. In this research, the classification of participants (N=131) LS is implemented using EEG Beta Summative Power Spectrum Density (PSD) and Kolb's Learning Style Inventory questionnaire. The LS clustering process with EEG Beta Summative PSD dataset is fulfilled using SPSS Two-steps Cluster Analysis tool. The findings established that EEG Beta Summative power had been successful in classifying the LS with high percentage obtained. Meanwhile, the classification dissimilarity caused by EEG Beta Summative PSD in different construct was considered as minimal and Accommodators had been discovered as the best LS classified using EEG Beta Summative PSD. © 2015 IEEE.