Triangulating the implementation of hierarchical agglomerative clustering on MAR-learning usability data
Augmented reality; Clustering algorithms; Machine learning; Usability engineering; English language teaching; Hierarchical agglomerative clustering; Mobile augmented reality; Performance metrics; Self-reported metrics; Usability; Hierarchical clustering
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2023
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my.uniten.dspace-244892023-05-29T15:23:57Z Triangulating the implementation of hierarchical agglomerative clustering on MAR-learning usability data Lim K.C. Selamat A. Mohamed Zabil M.H. Yusoff Y. Selamat M.H. Alias R.A. Puteh F. Mohamed F. Krejcar O. 57188850203 24468984100 35185866500 56921898900 57215520379 25928253600 57202529348 55416008900 14719632500 Augmented reality; Clustering algorithms; Machine learning; Usability engineering; English language teaching; Hierarchical agglomerative clustering; Mobile augmented reality; Performance metrics; Self-reported metrics; Usability; Hierarchical clustering This paper presents fractions of research outcome from a bigger project involving machine learning, Hierarchical Agglomerative Clustering (HAC) Algorithms on usability data gathered through performance and self-reported data. This paper highlights the common problems in usability studies where the conventional analysis was frequently utilized while prioritizing usability issues. The utilization of clustering techniques is limited in the area of this study. A previous publication has shown how HAC was used in clustering usability problems in Mobile Augmented Reality (MAR) learning applications. However, there has not been a triangulation effort to confirm the first gathered results due to small datasets. This research presents a methodology adopted from previous studies in confirming earlier usability analysis results. The experiments found consistent evidence approving the feasibility of HAC in clustering and prioritizing Usability performance and self-reported data. � 2019 The authors and IOS Press. All rights reserved. Final 2023-05-29T07:23:57Z 2023-05-29T07:23:57Z 2019 Conference Paper 10.3233/FAIA190075 2-s2.0-85082080723 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85082080723&doi=10.3233%2fFAIA190075&partnerID=40&md5=4b64006fced34966cd199f9e082d1328 https://irepository.uniten.edu.my/handle/123456789/24489 318 500 511 IOS Press Scopus |
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Augmented reality; Clustering algorithms; Machine learning; Usability engineering; English language teaching; Hierarchical agglomerative clustering; Mobile augmented reality; Performance metrics; Self-reported metrics; Usability; Hierarchical clustering |
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57188850203 |
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57188850203 Lim K.C. Selamat A. Mohamed Zabil M.H. Yusoff Y. Selamat M.H. Alias R.A. Puteh F. Mohamed F. Krejcar O. |
format |
Conference Paper |
author |
Lim K.C. Selamat A. Mohamed Zabil M.H. Yusoff Y. Selamat M.H. Alias R.A. Puteh F. Mohamed F. Krejcar O. |
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Lim K.C. Selamat A. Mohamed Zabil M.H. Yusoff Y. Selamat M.H. Alias R.A. Puteh F. Mohamed F. Krejcar O. Triangulating the implementation of hierarchical agglomerative clustering on MAR-learning usability data |
author_sort |
Lim K.C. |
title |
Triangulating the implementation of hierarchical agglomerative clustering on MAR-learning usability data |
title_short |
Triangulating the implementation of hierarchical agglomerative clustering on MAR-learning usability data |
title_full |
Triangulating the implementation of hierarchical agglomerative clustering on MAR-learning usability data |
title_fullStr |
Triangulating the implementation of hierarchical agglomerative clustering on MAR-learning usability data |
title_full_unstemmed |
Triangulating the implementation of hierarchical agglomerative clustering on MAR-learning usability data |
title_sort |
triangulating the implementation of hierarchical agglomerative clustering on mar-learning usability data |
publisher |
IOS Press |
publishDate |
2023 |
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1806423227463892992 |
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13.222552 |