Correlation of Student’s Precursor Emotion towards Learning Science Interest using EEG

Abstract

Mathematics and science are two important subjects for students to do well in school. Unfortunately majority of the students are having difficulties in coping with these subjects. Malaysia is ranked third lowest in the Program for International Student Assessment (PISA) for mathematics and science. An emotionally disturbed student seems to have problem coping with the learning of mathematics and science thus it is important to identify the demotivating factors affecting the performance of such students. In this paper, it analyze the correlation of precursor emotion towards student interest in learning mathematics and science using electroencephalogram (EEG) device. This correlation and their respective emotion can be analyzed based on the 2-D Affective Space Model (ASM) using four basic emotions of happiness, calmness, fear and sadness as reference stimuli. EEG device was used to extract brain waves signal while answering the mathematics and science questions. The EEG signals were captured on the scalp of the student and features extracted using Mel Frequency Cepstral Coefficient (MFCC). Neural network classifier of Multilayer Perceptron (MLP) was used to classify the valence and arousal axes for the ASM. Preliminary results show the relationship of precursor emotion and the dynamic emotions of the student while taking the mathematics and science test. We hope that these results can help us further relate the behavior and interest of students towards the learning of mathematics and science.