冠状病毒封锁期间移动技术和大数据在物理教育中的应用的影响

IF 7.7 1区 计算机科学 Q1 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE Big Data Mining and Analytics Pub Date : 2023-04-07 DOI:10.26599/BDMA.2022.9020013
Edeh Michael Onyema;Rijwan Khan;Nwafor Chika Eucheria;Tribhuwan Kumar
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引用次数: 0

摘要

2019冠状病毒疾病的传播速度导致了全球封锁和学术部门的混乱。这项研究考察了封锁期间移动技术对物理教育的影响。数据通过在线调查收集,随后使用回归工具、频率和方差分析(ANOVA)进行评估。研究结果显示,在冠状病毒封锁期间,移动技术的使用对物理老师和学生的学业产生了统计上的显著影响。大多数参与者承认,在疫情限制期间,使用智能手机、笔记本电脑、PDA、Zoom、移动应用程序等移动技术非常有用,有助于继续教育。在不同平台上使用智能手机和笔记本电脑进行封锁期间,在线教学非常有效。这篇论文引起了人们对移动技术解决方案在物理教育中日益强大的影响力的关注。
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Impact of Mobile Technology and Use of Big Data in Physics Education During Coronavirus Lockdown
The speed of spread of Coronavirus Disease 2019 led to global lockdowns and disruptions in the academic sector. The study examined the impact of mobile technology on physics education during lockdowns. Data were collected through an online survey and later evaluated using regression tools, frequency, and an analysis of variance (ANOVA). The findings revealed that the usage of mobile technology had statistically significant effects on physics instructors' and students' academics during the coronavirus lockdown. Most of the participants admitted that the use of mobile technologies such as smartphones, laptops, PDAs, Zoom, mobile apps, etc. were very useful and helpful for continued education amid the pandemic restrictions. Online teaching is very effective during lock-down with smartphones and laptops on different platforms. The paper brings the limelight to the growing power of mobile technology solutions in physics education.
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来源期刊
Big Data Mining and Analytics
Big Data Mining and Analytics Computer Science-Computer Science Applications
CiteScore
20.90
自引率
2.20%
发文量
84
期刊介绍: Big Data Mining and Analytics, a publication by Tsinghua University Press, presents groundbreaking research in the field of big data research and its applications. This comprehensive book delves into the exploration and analysis of vast amounts of data from diverse sources to uncover hidden patterns, correlations, insights, and knowledge. Featuring the latest developments, research issues, and solutions, this book offers valuable insights into the world of big data. It provides a deep understanding of data mining techniques, data analytics, and their practical applications. Big Data Mining and Analytics has gained significant recognition and is indexed and abstracted in esteemed platforms such as ESCI, EI, Scopus, DBLP Computer Science, Google Scholar, INSPEC, CSCD, DOAJ, CNKI, and more. With its wealth of information and its ability to transform the way we perceive and utilize data, this book is a must-read for researchers, professionals, and anyone interested in the field of big data analytics.
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Contents Front Cover Incremental Data Stream Classification with Adaptive Multi-Task Multi-View Learning Attention-Based CNN Fusion Model for Emotion Recognition During Walking Using Discrete Wavelet Transform on EEG and Inertial Signals Gender-Based Analysis of User Reactions to Facebook Posts
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