E-Learning is an important media that an educational institution must have. Successful information design for e-learning depends on its user’s characteristics. This study explores differences between novice and expert users’ eye movement data. This differences between expert and novice users were compared and identified based on gaze features. Each participant must do three main tasks of e-learning. This paper gives the result that there are differences between gaze features of experts and novices.
Remote eye trackers with consumer price have been used for various applications on flat computer screen. On the other hand, 3D gaze tracking in physical environment has been useful for visualizing gaze behavior, robots controller, and assistive technology. Instead of using affordable remote eye trackers, 3D gaze tracking in physical environment has been performed using corporate-level head mounted eye trackers, limiting its practical usage to niche user. In this research, we propose a novel method to estimate 3D gaze using consumer-level remote eye tracker. We implement geometric approach to obtain 3D point of gaze from binocular lines-of-sight. Experimental results show that the proposed method yielded low errors of 3.47±3.02 cm, 3.02±1.34 cm, and 2.57±1.85 cm in X, Y , and Z dimensions, respectively. The proposed approach may be used as a starting point for designing interaction method in 3D physical environment.