Reading Behavior Analysis with Gaze Tracking Data
Wen-Chung Kao, Chun-Wei Shen, Chao‐Jung Wu · 2018
Gaze tracking has become one of the most attractive human machine interfaces on consumer electronics. In addition to providing intelligent interactive functions on the consumer electronics, it also makes possible to collect the data of user attention. Furthermore, the data could be analyzed to predict the reading behavior and the information processing in the brain. In this paper, we propose an automatic tool for the gaze data analysis. A mathematic examination system is used for demonstrating the system performance. According to the gaze data, the experimental results show the feasibility of estimating the learner's ability, and the accuracy has achieved higher than 90%.