SLM-OJ: Surrogate Learning Mechanism during Outbreak Juncture

Author:

Ashraf Shahzad1,A. Arfeen Zeeshan2,A. Khan Muhammad3,Ahmed Tauqeer1

Affiliation:

1. Hohai University, Changzhou, Jiangsu, China

2. University College of Engineering & Technology, The Islamia University of Bahawalpur, Pakistan

3. Department of Information and Communication Engineering,Dongguk University, Seoul, South Korea

Abstract

During epidemic outbreak it is hard to continue formal leaning and training routines specially when whole world is facing corona virus fistula. It is crucial to identify and share the best practices and innovations to enable teaching and learning to take place during outbreak juncture. This will reinforce the basis for more sustainable and balanced schooling solutions as the crisis decreases. The biggest solution to cuts of schools is to plunge into cyberspace and distance learning, establishing a symbiosis between humans and the computers. Ideally, specific contents, learning outcomes, and a set of instructions are desirable. Use various media and technology, students can learn more in different ways and obtain varying results at various levels. Technologies can be compared along several characteristics. These features form a foundation for evaluating emerging innovations, seeing where they fit into the current environment and determining their potential benefits and limitations. Today, technology appears to become more communicative and richer in media, thereby giving educators and students powerful resources to achieve desired learning outcomes.

Publisher

International Journal for Modern Trends in Science and Technology (IJMTST)

Subject

Ocean Engineering

Cited by 9 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. What is the consequence of metals on human health?;Archives of Community Medicine and Public Health;2022-05-11

2. Adopting proactive results by developing the Shrewd model of pandemic COVID-19;Archives of Community Medicine and Public Health;2022-04-28

3. Identifying the Branch of Kiwifruit Based on Unmanned Aerial Vehicle (UAV) Images Using Deep Learning Method;Sensors;2021-06-29

4. Bodacious-Instance Coverage Mechanism for Wireless Sensor Network;Wireless Communications and Mobile Computing;2020-11-27

5. NRSM: node redeployment shrewd mechanism for wireless sensor network;Iran Journal of Computer Science;2020-10-31

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3