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E-learning enhancement through educational data mining with Covid-19 outbreak period in backdrop: A review
E-learning is fast becoming an integral part of the teaching- learning process, particularly after the outbreak of Covid-19 pandemic. Educational institutions across the globe are striving to enhance their e-learning instructional mechanism in accordance with the aspirations of present-day students...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier Ltd.
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10196156/ https://www.ncbi.nlm.nih.gov/pubmed/37255844 http://dx.doi.org/10.1016/j.ijedudev.2023.102814 |
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author | Aulakh, Kudratdeep Roul, Rajendra Kumar Kaushal, Manisha |
author_facet | Aulakh, Kudratdeep Roul, Rajendra Kumar Kaushal, Manisha |
author_sort | Aulakh, Kudratdeep |
collection | PubMed |
description | E-learning is fast becoming an integral part of the teaching- learning process, particularly after the outbreak of Covid-19 pandemic. Educational institutions across the globe are striving to enhance their e-learning instructional mechanism in accordance with the aspirations of present-day students who are widely using numerous technological tools — computers, tablets, mobiles, and Internet for educational purposes. In the wake of the evident incorporation of e-learning into the educational process, research related to the application of Educational Data Mining (EDM) techniques for enhancing e-learning systems has gained significance in recent times. The various data mining techniques applied by researchers to study hidden trends or patterns in educational data can provide valuable insights for educational institutions in terms of making the learning process adaptive to student needs. The insights can help the institutions achieve their ultimate goal of improving student academic performance in technology-assisted learning systems of the modern world. This review paper aims to comprehend EDM’s role in enhancing e-learning environments with reference to commonly-used techniques, along with student performance prediction, the impact of Covid-19 pandemic on e-learning and priority e-learning focus areas in the future. |
format | Online Article Text |
id | pubmed-10196156 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Elsevier Ltd. |
record_format | MEDLINE/PubMed |
spelling | pubmed-101961562023-05-19 E-learning enhancement through educational data mining with Covid-19 outbreak period in backdrop: A review Aulakh, Kudratdeep Roul, Rajendra Kumar Kaushal, Manisha Int J Educ Dev Article E-learning is fast becoming an integral part of the teaching- learning process, particularly after the outbreak of Covid-19 pandemic. Educational institutions across the globe are striving to enhance their e-learning instructional mechanism in accordance with the aspirations of present-day students who are widely using numerous technological tools — computers, tablets, mobiles, and Internet for educational purposes. In the wake of the evident incorporation of e-learning into the educational process, research related to the application of Educational Data Mining (EDM) techniques for enhancing e-learning systems has gained significance in recent times. The various data mining techniques applied by researchers to study hidden trends or patterns in educational data can provide valuable insights for educational institutions in terms of making the learning process adaptive to student needs. The insights can help the institutions achieve their ultimate goal of improving student academic performance in technology-assisted learning systems of the modern world. This review paper aims to comprehend EDM’s role in enhancing e-learning environments with reference to commonly-used techniques, along with student performance prediction, the impact of Covid-19 pandemic on e-learning and priority e-learning focus areas in the future. Elsevier Ltd. 2023-09 2023-05-19 /pmc/articles/PMC10196156/ /pubmed/37255844 http://dx.doi.org/10.1016/j.ijedudev.2023.102814 Text en © 2023 Elsevier Ltd. All rights reserved. Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active. |
spellingShingle | Article Aulakh, Kudratdeep Roul, Rajendra Kumar Kaushal, Manisha E-learning enhancement through educational data mining with Covid-19 outbreak period in backdrop: A review |
title | E-learning enhancement through educational data mining with Covid-19 outbreak period in backdrop: A review |
title_full | E-learning enhancement through educational data mining with Covid-19 outbreak period in backdrop: A review |
title_fullStr | E-learning enhancement through educational data mining with Covid-19 outbreak period in backdrop: A review |
title_full_unstemmed | E-learning enhancement through educational data mining with Covid-19 outbreak period in backdrop: A review |
title_short | E-learning enhancement through educational data mining with Covid-19 outbreak period in backdrop: A review |
title_sort | e-learning enhancement through educational data mining with covid-19 outbreak period in backdrop: a review |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10196156/ https://www.ncbi.nlm.nih.gov/pubmed/37255844 http://dx.doi.org/10.1016/j.ijedudev.2023.102814 |
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