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Expert judgement of collaborative cloud classroom quality and its criteria using the many-facets rasch model
Collaborative Cloud Classroom (3CR) is an educational application that provides flexibility in the learning process. This specialized tool is designed to improve analytical and teambuilding skills, as well as enable students to document ideas, which are subsequently developed into bubble diagrams an...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10570598/ https://www.ncbi.nlm.nih.gov/pubmed/37842603 http://dx.doi.org/10.1016/j.heliyon.2023.e20596 |
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author | Ramadhani, Rahmi Syahputra, Edi Simamora, Elmanani Soeharto, Soeharto |
author_facet | Ramadhani, Rahmi Syahputra, Edi Simamora, Elmanani Soeharto, Soeharto |
author_sort | Ramadhani, Rahmi |
collection | PubMed |
description | Collaborative Cloud Classroom (3CR) is an educational application that provides flexibility in the learning process. This specialized tool is designed to improve analytical and teambuilding skills, as well as enable students to document ideas, which are subsequently developed into bubble diagrams and text outlines. This study aims to assess and analyze the menu qualities possessed by the 3CR application using the Many-Facet Rasch Model (MFRM) analysis using 5 raters and 6 menus. A rating assessment was applied to 5 criteria, namely usability, functionality, visual communication, learning design, and security. In this case, a total of 135 from 150 data points were coded into FACETS software. The results showed that the six menus in the 3CR application were valid and reliable, as well as met the quality standards of learning tools. Security criteria were also the most difficult standards for raters to measure in all the application menus. The study also found that Rater A was more severe, and Rater E was more lenient in rating the 3CR menu. Rater B has overfitting and detected bias between rater gender and 3CR's menu (Discussion Forum and Learning Reflection menu) based on MFRM analysis. |
format | Online Article Text |
id | pubmed-10570598 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-105705982023-10-14 Expert judgement of collaborative cloud classroom quality and its criteria using the many-facets rasch model Ramadhani, Rahmi Syahputra, Edi Simamora, Elmanani Soeharto, Soeharto Heliyon Research Article Collaborative Cloud Classroom (3CR) is an educational application that provides flexibility in the learning process. This specialized tool is designed to improve analytical and teambuilding skills, as well as enable students to document ideas, which are subsequently developed into bubble diagrams and text outlines. This study aims to assess and analyze the menu qualities possessed by the 3CR application using the Many-Facet Rasch Model (MFRM) analysis using 5 raters and 6 menus. A rating assessment was applied to 5 criteria, namely usability, functionality, visual communication, learning design, and security. In this case, a total of 135 from 150 data points were coded into FACETS software. The results showed that the six menus in the 3CR application were valid and reliable, as well as met the quality standards of learning tools. Security criteria were also the most difficult standards for raters to measure in all the application menus. The study also found that Rater A was more severe, and Rater E was more lenient in rating the 3CR menu. Rater B has overfitting and detected bias between rater gender and 3CR's menu (Discussion Forum and Learning Reflection menu) based on MFRM analysis. Elsevier 2023-10-05 /pmc/articles/PMC10570598/ /pubmed/37842603 http://dx.doi.org/10.1016/j.heliyon.2023.e20596 Text en © 2023 The Authors. Published by Elsevier Ltd. https://creativecommons.org/licenses/by/4.0/This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Research Article Ramadhani, Rahmi Syahputra, Edi Simamora, Elmanani Soeharto, Soeharto Expert judgement of collaborative cloud classroom quality and its criteria using the many-facets rasch model |
title | Expert judgement of collaborative cloud classroom quality and its criteria using the many-facets rasch model |
title_full | Expert judgement of collaborative cloud classroom quality and its criteria using the many-facets rasch model |
title_fullStr | Expert judgement of collaborative cloud classroom quality and its criteria using the many-facets rasch model |
title_full_unstemmed | Expert judgement of collaborative cloud classroom quality and its criteria using the many-facets rasch model |
title_short | Expert judgement of collaborative cloud classroom quality and its criteria using the many-facets rasch model |
title_sort | expert judgement of collaborative cloud classroom quality and its criteria using the many-facets rasch model |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10570598/ https://www.ncbi.nlm.nih.gov/pubmed/37842603 http://dx.doi.org/10.1016/j.heliyon.2023.e20596 |
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