A Cloud Based Solution for Smart Education

Alam, M. Afshar; Saiyeda, Anam

doi:10.4018/ijseus.2020040103

Cited by 13 publications

(4 citation statements)

References 10 publications

(1 reference statement)

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“…Design. The configuration structure of hardware equipment in the education wisdom platform based on big data is shown in Figure 2 [22]. It usually includes servers, switches, firewalls, network cabinets, cameras, audio-visual distributors and handwriting monitors, and two computers.…”

Section: Platform Hardware Device Configuration Structurementioning

confidence: 99%

Application of Data Mining Model in Smart Chemistry Education

Fei¹

2022

Wireless Communications and Mobile Computing

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In order to solve the problem that the activities of teachers and students in traditional teaching methods are constrained by lesson plans, the teaching methods are aging, and they do not have the ability to expand students’ learning through big data; due to the problem of low self-learning and extracurricular communication ability of students after class, the author proposes the application of a data mining model in smart chemistry education. The author designs an educational wisdom platform based on big data, and its overall structure includes physical layer, virtual resource layer, logic layer, presentation layer, application layer, network layer, and user layer; the big data center module in the platform collects all business data through devices such as networks and sensors and stores the business data in mass data storage devices; the software design part uses the multi-feature fusion acquisition algorithm to collect student data and completes the early warning of student performance through the performance early warning algorithm based on correlation analysis technology. The results showed that only 5.15% and 4.49% of the students who designed the platform could not improve their after-class autonomous learning and extracurricular communication skills, and more than 95% of the students had good feedback after using the platform. Conclusion. It shows that the design platform can effectively improve the students’ ability of self-learning and extracurricular communication after class, and the application efficiency is high.

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Section: Platform Hardware Device Configuration Structurementioning

confidence: 99%

Application of Data Mining Model in Smart Chemistry Education

Fei¹

2022

Wireless Communications and Mobile Computing

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“…Throughput mainly describes the amount of data received by the wireless network communication system in a unit of time. The performance change curve of the wireless network communication system under different simulation times and three wireless network channel allocation methods is shown in Figure 7 [23]. It shows that the wireless channel allocation method used in this paper is relatively stable to the changes in the performance of the wireless communication system; it shows that the performance of the wireless network communication system is unstable.…”

Section: Throughput Comparison Of Wireless Networkmentioning

confidence: 86%

Autonomous Mobile Learning Model of Cloud Education Based on Intelligent Algorithm of Wireless Network Communication

Chen

Zhu

2021

Wireless Communications and Mobile Computing

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The rapid development of a new generation of information technology and its widespread application in colleges and universities have promoted profound changes in campus informatization. On the one hand, wireless campus networks as the main infrastructure of digital campuses are gradually popularized in domestic colleges and universities, expanding the campus information network coverage. This article is aimed at studying the addition of intelligent algorithms to wireless network communications to optimize and build autonomous mobile learning for cloud education. In order for children to communicate with teachers face to face, no matter where they are, this article proposes how to reduce the energy loss in wireless communication and find the best intelligent algorithm to realize the cloud education mobile learning platform. Experimental results show that the transmission delay of the wireless communication system of this method is significantly shorter than that of the other two methods, close to 5%, which speeds up the data transmission speed of the wireless communication system. It can be implemented under time-sensitive conditions and has high practical application value. The wireless network communication system of this method has a low packet loss rate and less wireless network data transmission errors, which is nearly 10% lower than the other two methods, thereby improving the data transmission power of the wireless communication network.

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“…With the use of cutting-edge technology such as IoT and cloud computing, academies are getting smarter. It improves the typical classroom setting to help students learn more effectively [5].…”

Section: Cloud Computingmentioning

confidence: 99%

Interactive and innovative technologies for smart education

Omonayajo

Al‐Turjman²,

Çavuş

2022

COMSIS J

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New concepts and ideas have emerged in the process of obtaining and disseminating cognitive, ethical, and public knowledge. In the current state of education, learners, tutors, and the knowledge being transferred are all present, and smart education has made the process of acquiring knowledge more flexible. This concept is accomplished through the use of smart devices and technologies that are interconnected to access digital resources. Smart education refers to a new way of learning that has gotten a lot of attention, notably during the 2020 Covid-19 Pandemic. This article examines the technologies that have aided smart education in achieving its educational goals. With smart technological solutions, modern technologies are enhancing the teaching - learning process in today?s education. It is with great hope that the use of modern technologies in smart education will improve educational quality while also making teaching and learning more convenient.

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A Cloud Based Solution for Smart Education

Cited by 13 publications

References 10 publications

Application of Data Mining Model in Smart Chemistry Education

Application of Data Mining Model in Smart Chemistry Education

Autonomous Mobile Learning Model of Cloud Education Based on Intelligent Algorithm of Wireless Network Communication

Interactive and innovative technologies for smart education

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