抄録
Providing attractive and interesting e-learning courses material as well as normal lecture in the class is one of important issues in e-learning society. Knowing about this issue, first, it is essential to investigate student interest about topic and types of e-learning courses delivered by measuring their responses. Thus, this study engages in student's responses initiated by two distinction e-learning materials; one is characterized by an interactive material and the other one is non-interactive material, based on physiological signals or biosignals, i.e., hemodynamic responses. Use of multilinear principal component analysis (MPCA) was then proposed in this study to extract the representative features of hemodynamic responses. Finally, the classification was performed by support vector machine (SVM) to discriminate hemodynamic response of student.
