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Prioritization of Influence Factors for Selecting E–Learning Systems
COVID-19 pandemic affects not only daily life activities but also traditional education systems. Based on the current developments, to stick by their academic calendars, most of the educational institutions continue their classes via online channels. Since the selection of the most appropriate e–lea...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7351576/ http://dx.doi.org/10.1007/978-3-030-51156-2_63 |
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author | Karasan, Ali Erdogan, Melike |
author_facet | Karasan, Ali Erdogan, Melike |
author_sort | Karasan, Ali |
collection | PubMed |
description | COVID-19 pandemic affects not only daily life activities but also traditional education systems. Based on the current developments, to stick by their academic calendars, most of the educational institutions continue their classes via online channels. Since the selection of the most appropriate e–learning platform depends on multi–criteria, the evaluation of this selection process can be dealt with decision support systems. In this study, cognitive mapping extended with intuitionistic fuzzy sets is introduced for prioritizing the e–learning platform selection factors under fuzzy environment based on the multi–expert judgments. Based on the results, infrastructure and ease of use are determined as the most effective factors. For further studies, a sensitivity analysis based on the initial vector determination can be studied to check its effect on the outputs. |
format | Online Article Text |
id | pubmed-7351576 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
record_format | MEDLINE/PubMed |
spelling | pubmed-73515762020-07-13 Prioritization of Influence Factors for Selecting E–Learning Systems Karasan, Ali Erdogan, Melike Intelligent and Fuzzy Techniques: Smart and Innovative Solutions Article COVID-19 pandemic affects not only daily life activities but also traditional education systems. Based on the current developments, to stick by their academic calendars, most of the educational institutions continue their classes via online channels. Since the selection of the most appropriate e–learning platform depends on multi–criteria, the evaluation of this selection process can be dealt with decision support systems. In this study, cognitive mapping extended with intuitionistic fuzzy sets is introduced for prioritizing the e–learning platform selection factors under fuzzy environment based on the multi–expert judgments. Based on the results, infrastructure and ease of use are determined as the most effective factors. For further studies, a sensitivity analysis based on the initial vector determination can be studied to check its effect on the outputs. 2020-06-10 /pmc/articles/PMC7351576/ http://dx.doi.org/10.1007/978-3-030-51156-2_63 Text en © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 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 | Article Karasan, Ali Erdogan, Melike Prioritization of Influence Factors for Selecting E–Learning Systems |
title | Prioritization of Influence Factors for Selecting E–Learning Systems |
title_full | Prioritization of Influence Factors for Selecting E–Learning Systems |
title_fullStr | Prioritization of Influence Factors for Selecting E–Learning Systems |
title_full_unstemmed | Prioritization of Influence Factors for Selecting E–Learning Systems |
title_short | Prioritization of Influence Factors for Selecting E–Learning Systems |
title_sort | prioritization of influence factors for selecting e–learning systems |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7351576/ http://dx.doi.org/10.1007/978-3-030-51156-2_63 |
work_keys_str_mv | AT karasanali prioritizationofinfluencefactorsforselectingelearningsystems AT erdoganmelike prioritizationofinfluencefactorsforselectingelearningsystems |