Distance Learning (DL) systems have been growing recently due to the rapid advancement of Information and Communication Technology (ICT). However, each learner, who is attracted to take distance learning courses due to its convenience is always isolated. Therefore, it would be useful to take care of the learners more if the instructor could get information of the learner's condition such as where the learner is looking at and how long the learner takes to look at that particular point. This information is important to detect learners' concentration to the class, and thus it can be used for designing the content style of the class based on the learner's preference. In this study, the novel automatic approach to detect learner's concentration based on the content preference will be proposed. The main goal is to detect each learner's concentration based on the content style in a distance learning class session. In addition, this study will focus on real time distance learning class systems. During a real time class lesson, biological information such as fixation duration, fixation frequency, and saccade will be recorded in the eye tracking system and these data will be analysed. If the number of learners who are not concentrated on the content is larger than a threshold value, the alerting system will send a message to the instructor's display. Therefore, the instructor will change the content style accordingly. The proposed approach will be very useful in assisting the instructor to understand and determine the best content's model style to be used in the distance learning class based on learners preference.
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