Feasibility comparison of HAC algorithm on usability performance and self-reported metric features for MAR learning
Augmented reality; Cluster analysis; Learning systems; Usability engineering; Agglomerative clustering; English language teaching; Mobile augmented reality; Unsupervised machine learning; Usability; Clustering algorithms
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IOS Press
2023
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my.uniten.dspace-239792023-05-29T14:53:49Z Feasibility comparison of HAC algorithm on usability performance and self-reported metric features for MAR learning Cheng L.K. Selamat A. Zabil M.H.M. Selamat M.H. Alias R.A. Puteh F. Mohamed F. Krejcar O. Herrera-Viedma E. Fujita H. 57188850203 24468984100 35185866500 57215520379 25928253600 57202529348 55416008900 14719632500 7004240703 35611951900 Augmented reality; Cluster analysis; Learning systems; Usability engineering; Agglomerative clustering; English language teaching; Mobile augmented reality; Unsupervised machine learning; Usability; Clustering algorithms This paper highlights the current literatures in usability studies, performance metrics, self-reported metrics and hierarchical agglomerative clustering algorithms. A literature review is done in these three areas of studies to find a research gap that can be explored further. The paper will then propose a research methodology to study comparatively feature selection based on performance and self-reported usability data. This paper will highlight methods used to compare the feasibility and performance of hierarchical agglomerative clustering algorithms on both performance and self-reported data. The results of the experiment will then be presented and discussed before proceeding to the conclusion and future works of this study. � 2018 The authors and IOS Press. All rights reserved. Final 2023-05-29T06:53:49Z 2023-05-29T06:53:49Z 2018 Conference Paper 10.3233/978-1-61499-900-3-896 2-s2.0-85063371964 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85063371964&doi=10.3233%2f978-1-61499-900-3-896&partnerID=40&md5=9c72d727ad676ea7143553e5d7e09813 https://irepository.uniten.edu.my/handle/123456789/23979 303 896 910 IOS Press Scopus |
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| description |
Augmented reality; Cluster analysis; Learning systems; Usability engineering; Agglomerative clustering; English language teaching; Mobile augmented reality; Unsupervised machine learning; Usability; Clustering algorithms |
| author2 |
57188850203 |
| author_facet |
57188850203 Cheng L.K. Selamat A. Zabil M.H.M. Selamat M.H. Alias R.A. Puteh F. Mohamed F. Krejcar O. Herrera-Viedma E. Fujita H. |
| format |
Conference Paper |
| author |
Cheng L.K. Selamat A. Zabil M.H.M. Selamat M.H. Alias R.A. Puteh F. Mohamed F. Krejcar O. Herrera-Viedma E. Fujita H. |
| spellingShingle |
Cheng L.K. Selamat A. Zabil M.H.M. Selamat M.H. Alias R.A. Puteh F. Mohamed F. Krejcar O. Herrera-Viedma E. Fujita H. Feasibility comparison of HAC algorithm on usability performance and self-reported metric features for MAR learning |
| author_sort |
Cheng L.K. |
| title |
Feasibility comparison of HAC algorithm on usability performance and self-reported metric features for MAR learning |
| title_short |
Feasibility comparison of HAC algorithm on usability performance and self-reported metric features for MAR learning |
| title_full |
Feasibility comparison of HAC algorithm on usability performance and self-reported metric features for MAR learning |
| title_fullStr |
Feasibility comparison of HAC algorithm on usability performance and self-reported metric features for MAR learning |
| title_full_unstemmed |
Feasibility comparison of HAC algorithm on usability performance and self-reported metric features for MAR learning |
| title_sort |
feasibility comparison of hac algorithm on usability performance and self-reported metric features for mar learning |
| publisher |
IOS Press |
| publishDate |
2023 |
| _version_ |
1806426004227358720 |
| score |
13.222552 |