Abstract
The trend of distance learning education has increased year by year because of the rapid advancement of information and communication technologies. Distance learning system can be regarded as one of ubiquitous computing applications since the learners can study anywhere even in mobile environments. However, the instructor cannot know if the learners comprehend the lecture or not since each learner is physically isolated. Therefore, a framework which detects the learners’ concentration condition is required. If a distance learning system obtains the information that many learners are not concentrated on the class due to the incomprehensible lecture style, the instructor can perceive it through the system and change the presentation strategy. This is a context-aware technology which is widely used for ubiquitous computing services. In this paper, an efficient distance learning system, which accurately detects learners’ concentration condition during a class, is proposed. The proposed system uses multiple biological information which are learners’ eye movement metrics, i.e. fixation counts, fixation rate, fixation duration and average saccade length obtained by an eye tracking system. The learners’ concentration condition is classified by using machine learning techniques. The proposed system has performed the detection accuracy of 90.7% when Multilayer Perceptron is used as a classifier. In addition, the effectiveness of the proposed eye metrics has been confirmed. Furthermore, it has been clarified that the fixation duration is the most important eye metric among the four metrics based on the investigation of evaluation experiment.
Highlights
Distance learning system can be regarded as a ubiquitous computing application because it has relieved learners from fixed learning places and realized education opportunity anywhere
If a distance learning system obtains the information that many learners are not concentrated on the class due to the incomprehensible lecture style, the instructor can perceive it through the system and change the presentation strategy
It has been clarified that the fixation duration is the most important eye metric among the four metrics based on the investigation of evaluation experiment
Summary
Distance learning system can be regarded as a ubiquitous computing application because it has relieved learners from fixed learning places and realized education opportunity anywhere. Assessment of learners’ condition in distance learning systems has gained a lot of attentions in Human Computer Interaction (HCI) research. It is necessary for an instructor to ensure the learners’ participation in learning process and assist them based on their condition during the class. One of the promising approaches to detect learners’ emotions is the use of biological signals [1]. Biological signals such as eye movements, heart rate and skin temperature are controlled without human’s consciousness [2]. This technique is considered as one of the best methods to detect learners’ emotions [3]. If the learner is taking a class with such a negative emotion, he/she may not concentrate well on the ongoing lecture
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
