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Sensors and Materials
is an international peer-reviewed open access journal to provide a forum for researchers working in multidisciplinary fields of sensing technology.
Online: ISSN 2435-0869
Sensors and Materials
is an international peer-reviewed open access journal to provide a forum for researchers working in multidisciplinary fields of sensing technology.
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Sensors and Materials
is covered by Science Citation Index Expanded (Clarivate Analytics), Scopus (Elsevier), and other databases.
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is covered by Science Citation Index Expanded (Clarivate Analytics), Scopus (Elsevier), and other databases.
Instructions to authors
English 日本語
Instructions for manuscript preparation
English 日本語
Template
English
Publisher
MYU K.K.
Sensors and Materials
1-23-3-303 Sendagi,
Bunkyo-ku, Tokyo 113-0022, Japan
Tel: 81-3-3827-8549
Fax: 81-3-3827-8547
MYU Research, a scientific publisher, seeks a native English-speaking proofreader with a scientific background. B.Sc. or higher degree is desirable. In-office position; work hours negotiable. Call 03-3827-8549 for further information.
MYU Research
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MYU K.K.
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The Art of Writing Scientific Papers
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(Japanese Only)
Sensors and Materials, Volume 33, Number 6(2) (2021)
Copyright(C) MYU K.K.
Copyright(C) MYU K.K.
|
pp. 2045-2062
S&M2592 Research Paper of Special Issue https://doi.org/10.18494/SAM.2021.3287 Published: June 9, 2021 Use of Sensor Technologies in Online Courses in Post-COVID-19 Era [PDF] Tung-Lung Wu, Ming-Yuan Hsieh, Kao-Wei Min, Ming-Ta Yu, and Chi-Ting Ho (Received December 31, 2020; Accepted April 19, 2021) Keywords: sensor technology, online-course technology, Massive Open Online Courses (MOOCs), multiple-criteria decision-making (MCDM) methodology
In this study, educational social learning theory and a statistical multiple-criteria decision-making (MCDM) methodology are creatively cross-employed to comprehensively cross-evaluate online courses and sensor technologies. This was accomplished by means of an in-depth survey of large-scale current online-course users and professional experts with the highest research reliability, validity, accuracy, and representativeness. The three most valuable and contributive conclusions of this study are as follows: (1) The repurposing technology function (RTF) of online-course technology can combine software sensor (SS), motion sensor (MS), and environment sensor (ES) technologies to not only detect moving objects but also achieve cognition in the environment (e.g., by using a face sensor) to extract emotions of course participants in response to words and phrases during lectures to increase online-course learning performance. (2) The course professionalization technology function (CPTF) of online-course technology can merge SS, MS, and ES technologies to control online-course hardware sensor devices and equipment to control the depth and span of online-course content to strengthen online-course learning performance. (3) The course evaluation technology function (CETF) of online-course technology can consolidate SS, MS, and ES technologies to not only empirically evaluate online-course implementation but also indirectly appraise online-course learning performance.
Corresponding author: Ming-Yuan Hsieh  This work is licensed under a Creative Commons Attribution 4.0 International License. Cite this article Tung-Lung Wu, Ming-Yuan Hsieh, Kao-Wei Min, Ming-Ta Yu, and Chi-Ting Ho, Use of Sensor Technologies in Online Courses in Post-COVID-19 Era, Sens. Mater., Vol. 33, No. 6, 2021, p. 2045-2062. |
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