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Impact of SARS-CoV-2 in Online Education, Predicting and Contrasting Mental Stress of Young Students: A Machine Learning Approach
The nation has already had to contend with such a major public health issue when this COVID-19 disease was propagated in March 2020. The corona's propagation does have an effect on all areas of people's lives. The hostile effect on education systems throughout all locations is indeed a div...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Singapore
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8184403/ http://dx.doi.org/10.1007/s41133-021-00048-0 |
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author | Parthiban, K. Pandey, Digvijay Pandey, Binay Kumar |
author_facet | Parthiban, K. Pandey, Digvijay Pandey, Binay Kumar |
author_sort | Parthiban, K. |
collection | PubMed |
description | The nation has already had to contend with such a major public health issue when this COVID-19 disease was propagated in March 2020. The corona's propagation does have an effect on all areas of people's lives. The hostile effect on education systems throughout all locations is indeed a diverse expansion impact. A complete shutdown keeps adding fresh problems for students to learn and also for educators to effectively manage the class, likely to result in the conversion of such an offline education system into a virtual class. This study investigated and described various online learning platforms, as well as teaching resource distribution technology and modern technologies used to ensure that students can study. Overall, this relates to channels that can be used to create a confidential environment in order to prevent copying in online tests. This also outlines so many difficulties in managing online teaching methods, like learners' perceptions of e-learning being more traumatic and having a negative impact on general wellbeing and social relationships. So, a technique has been proposed to provide learners with a superior online classroom teaching experience, allowing the online classroom to be as good as, if not better than, a single online classroom. This study focused on daily teaching methods that employ online learning supported by a machine teaching approach to provide an individual with a relevant stress-free solution. |
format | Online Article Text |
id | pubmed-8184403 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Springer Singapore |
record_format | MEDLINE/PubMed |
spelling | pubmed-81844032021-06-08 Impact of SARS-CoV-2 in Online Education, Predicting and Contrasting Mental Stress of Young Students: A Machine Learning Approach Parthiban, K. Pandey, Digvijay Pandey, Binay Kumar Augment Hum Res Original Paper The nation has already had to contend with such a major public health issue when this COVID-19 disease was propagated in March 2020. The corona's propagation does have an effect on all areas of people's lives. The hostile effect on education systems throughout all locations is indeed a diverse expansion impact. A complete shutdown keeps adding fresh problems for students to learn and also for educators to effectively manage the class, likely to result in the conversion of such an offline education system into a virtual class. This study investigated and described various online learning platforms, as well as teaching resource distribution technology and modern technologies used to ensure that students can study. Overall, this relates to channels that can be used to create a confidential environment in order to prevent copying in online tests. This also outlines so many difficulties in managing online teaching methods, like learners' perceptions of e-learning being more traumatic and having a negative impact on general wellbeing and social relationships. So, a technique has been proposed to provide learners with a superior online classroom teaching experience, allowing the online classroom to be as good as, if not better than, a single online classroom. This study focused on daily teaching methods that employ online learning supported by a machine teaching approach to provide an individual with a relevant stress-free solution. Springer Singapore 2021-06-08 2021 /pmc/articles/PMC8184403/ http://dx.doi.org/10.1007/s41133-021-00048-0 Text en © The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd. 2021 This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic. |
spellingShingle | Original Paper Parthiban, K. Pandey, Digvijay Pandey, Binay Kumar Impact of SARS-CoV-2 in Online Education, Predicting and Contrasting Mental Stress of Young Students: A Machine Learning Approach |
title | Impact of SARS-CoV-2 in Online Education, Predicting and Contrasting Mental Stress of Young Students: A Machine Learning Approach |
title_full | Impact of SARS-CoV-2 in Online Education, Predicting and Contrasting Mental Stress of Young Students: A Machine Learning Approach |
title_fullStr | Impact of SARS-CoV-2 in Online Education, Predicting and Contrasting Mental Stress of Young Students: A Machine Learning Approach |
title_full_unstemmed | Impact of SARS-CoV-2 in Online Education, Predicting and Contrasting Mental Stress of Young Students: A Machine Learning Approach |
title_short | Impact of SARS-CoV-2 in Online Education, Predicting and Contrasting Mental Stress of Young Students: A Machine Learning Approach |
title_sort | impact of sars-cov-2 in online education, predicting and contrasting mental stress of young students: a machine learning approach |
topic | Original Paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8184403/ http://dx.doi.org/10.1007/s41133-021-00048-0 |
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