Appraisal of EEG Beta summative power towards Learning Style classification

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.

[1]  Norizam Sulaiman,et al.  Implementation of Cluster analysis for Learning Style classification using brain Asymmetry , 2011, 2011 IEEE 7th International Colloquium on Signal Processing and its Applications.

[2]  M. Teplan.  FUNDAMENTALS OF EEG MEASUREMENT , 2002 .

[3]  İbrahim Yaşar Kazu.  The Effect of Learning Styles on Education and the Teaching Process , 2009 .

[4]  Mohd Nasir Taib,et al.  Determination of Vigilance-bound Learning Style based on EEG , 2012 .

[5]  Shintaro Okazaki,et al.  What do we know about mobile Internet adopters? A cluster analysis , 2006, Inf. Manag..

[6]  Marcia W. Keyser,et al.  Active learning and cooperative learning: understanding the difference and using both styles effectively , 2000 .

[7]  John Hall.  Neuroscience and Education A review of the contribution of brain science to teaching and learning , 2005 .

[8]  Zunairah Hj Murat,et al.  Summative EEG alpha classification relates learning style and openness , 2014, EDUCON.

[9]  Mohd Nasir Taib,et al.  Learners’ Learning Style Classification related to IQ and Stress based on EEG , 2011 .

[10]  Wageeh Boles,et al.  Influences on Student Learning in Engineering: Some Results from Case Study Fieldwork , 2010 .

[11]  Carmen R. Wilson VanVoorhis,et al.  Understanding Power and Rules of Thumb for Determining Sample Sizes , 2007 .

[12]  Norizam Sulaiman,et al.  Classification of learning style based on Kolb's Learning Style Inventory and EEG using cluster analysis approach , 2010, 2010 2nd International Congress on Engineering Education.

[13]  William M. Bart,et al.  On the Effect of Learning Style on Scholastic Achievement. , 2013 .

[14]  Francesco Carlo Morabito,et al.  Wavelet-ICA methodology for efficient artifact removal from Electroencephalographic recordings , 2007, 2007 International Joint Conference on Neural Networks.

[15]  Norizam Sulaiman,et al.  EEG analysis of frontal hemispheric asymmetry for learning styles , 2011, 2011 IEEE Control and System Graduate Research Colloquium.