A pupil data based classification model for education learning states

Abstract

In this paper, we propose a classification model for learning state based on individual biometric data. In particular, we use the pupil size as a biometric data and the data has been collected from 72 participants. We also deploy the support vector machine (SVM) in conjunction with k-fold validation as an analysis tool. In order to improve the performance of the SVM, the we remove outliers from the data set and normalize it. Our experiment results show that the accuracy of the proposed classification model is up to 68.8% and thus confirm the effectiveness of the proposed classification model using the pupil data. © 2017 IEEE.