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General Information
ISSN:
2377-2891(Print); 2377-2905(Online)
Frequency:
Bimonthly
Editor-in-Chief:
Prof. Eric C. K. Cheng
Associate Executive Editor:
Ms. Jenny Jiang
DOI:
10.18178/ijlt
Abstracting/Indexing:
Google Scholar; Crossref, CNKI,
etc.
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IJLT Editorial Office
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Editor-in-Chief
Prof. Eric C. K. Cheng
Professor & Vice President (Academic)
Yew Chung College of Early Childhood Education, Hong Kong, China
As the Editor-in-Chief of IJLT, I invite you to contribute your scholarly work to our esteemed publication. IJLT serves as a beacon for original and impactful academic contributions in the realm of education, fostering multidisciplinary research and development to enhance teaching-learning processes globally. We welcome submissions spanning a wide spectrum of topics, from innovative program development to the integration of digital tools in education. Our scope encompasses areas such as student leadership, diversity in education, and collaborative initiatives, reflecting our commitment to a sustainable and inclusive society. [
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What's New
2024-02-29
Vol. 10, No. 1, 2024 has been published!
2024-02-07
Welcome Prof. Eric C. K. Cheng from Yew Chung College of Early Childhood Education, Hong Kong, China to join IJLT Editorial Board as Editor-in-Chief!
2023-12-13
IJLT will adopt Article-by-Article Work Flow from 2024. For the Bimonthly journal, each issue will be released at the end of the issue month.
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Volume 3, No. 2, June 2017
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Scan Path Based Approach to Detect Learner’s Concentration in Distance Learning System
Nizetha Daniel Kimario and Eiji Kamioka
Shibaura Institute of Technology, Tokyo, Japan
Abstract
—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
Index Terms
—concentration, distance learning, fixation duration, saccade, learner
Cite: Nizetha Daniel Kimario and Eiji Kamioka, "Scan Path Based Approach to Detect Learner’s Concentration in Distance Learning System," International Journal of Learning and Teaching, Vol. 3, No. 2, pp. 124-129, June 2017. doi: 10.18178/ijlt.3.2.124-129
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