Experimental study for a computational model in ITS to predict the learners' state

Yoshimasa Tawatsuji, Keiichi Muramatsu, Tatsunori Matsui

Abstract: Cognitive architecture plays essential role in Intelligent Tutoring System (ITS). For effective learning support, dynamic model subserving the function of the prediction of learners’ states should be incorporated. In this paper, we proposed a neural network-based architecture in progress that can incorporate the dynamic model to generate the prediction of leaners’ perceptual states when categorical ambiguous stimulus and the instruction of category were given.