Abstract
In this study, educational social learning theory and a statistical multiple-criteria decisionmaking (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. © 2021 M Y U Scientific Publishing Division. All rights reserved.
Highlights
In the official announcement of the World Health Organization on March 11, 2020, the spread of the coronavirus disease 2019 (COVID-19) was characterized as a global pandemic
The Ministry of Education in Taiwan has started a series of measures to support online courses, as well as policies and regulations to ensure students’ right to education while minimizing the risk of becoming infected with COVID-19
Self-regulation learning performance, improve the evaluation system of educational institutions, and promote corporate recognition and identification, the use of sensor technologies in online courses in the post-COVID-19 era has been a major area of research across all forms of Taiwanese educational institutions, including senior high schools, vocational schools, colleges and universities, and adult continuous educational institutions
Summary
In the official announcement of the World Health Organization on March 11, 2020, the spread of the coronavirus disease 2019 (COVID-19) was characterized as a global pandemic. As shown in the 2020 empirical reports from the Department of Information and Technological Education of the Ministry of Education in Taiwan, there were 341 online courses in the official Massive Open Online Courses (MOOCs) provided by 63 Taiwanese universities and colleges in 2018. According to official reports from the Department of Information and Technological Education of the Ministry of Education in Taiwan in 2020 after the COVID-19 outbreak, only 12% of registered users of Taiwanese MOOCs could obtain official certificates for online-course credits and degrees through the diverse applied Internet of Things (IoT) platforms. Self-regulation learning performance, improve the evaluation system of educational institutions, and promote corporate recognition and identification, the use of sensor technologies in online courses in the post-COVID-19 era has been a major area of research across all forms of Taiwanese educational institutions, including senior high schools, vocational schools, colleges and universities, and adult continuous educational institutions.
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