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A taxonomic overview and pilot study for evaluation of Augmented Reality based posture matching technique using Technology Acceptance Model

Artificial intelligence; Augmented reality; Dance learning; Dance training systems; Hierarchical structures; Kinect; Learning paradigms; Learning technology; pose matching; Technology acceptance model; Learning systems

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Bibliographic Details
Main Authors: Iqbal J., Sidhu M.S.
Other Authors: 57200394167
Format: Conference Paper
Published: Elsevier B.V. 2023
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spelling my.uniten.dspace-248492023-05-29T15:27:53Z A taxonomic overview and pilot study for evaluation of Augmented Reality based posture matching technique using Technology Acceptance Model Iqbal J. Sidhu M.S. 57200394167 56259597000 Artificial intelligence; Augmented reality; Dance learning; Dance training systems; Hierarchical structures; Kinect; Learning paradigms; Learning technology; pose matching; Technology acceptance model; Learning systems Motor skill training, posture matching and Augmented Reality (AR) based learning technology are considered to be the cornerstones of dance learning paradigm. In this paper, an AR based posture matching technique is presented based upon skeletal mapping and movement matching where each posture is modelled by a sequence of pivotal movements and continuous data frames. An extension of the previously published work by the authors, this paper aims to provide a taxonomic overview of dance learning/ training technologies with respect to existing learning theories. Furthermore, the proposed system is evaluated using the Technology Acceptance Model (TAM) and a pilot study is carried out to assess the acceptability of the system. The results of the pilot study are also utilized for identifying flaws and to calculate the sample size for further evaluation using a larger group of subjects. This research also aims at providing a taxonomical knowledge and categorization of the proposed Augmented Reality Dance Training System (ARDTS) in the state-of-art hierarchical structure of learning theories. � 2019 The Authors. Published by Elsevier B.V. Final 2023-05-29T07:27:52Z 2023-05-29T07:27:52Z 2019 Conference Paper 10.1016/j.procs.2019.12.117 2-s2.0-85081165183 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85081165183&doi=10.1016%2fj.procs.2019.12.117&partnerID=40&md5=f67297f30e284f07044e5d2c5d4e8fa9 https://irepository.uniten.edu.my/handle/123456789/24849 163 345 351 All Open Access, Gold Elsevier B.V. Scopus
institution Universiti Tenaga Nasional
building UNITEN Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Tenaga Nasional
content_source UNITEN Institutional Repository
url_provider http://dspace.uniten.edu.my/
description Artificial intelligence; Augmented reality; Dance learning; Dance training systems; Hierarchical structures; Kinect; Learning paradigms; Learning technology; pose matching; Technology acceptance model; Learning systems
author2 57200394167
author_facet 57200394167
Iqbal J.
Sidhu M.S.
format Conference Paper
author Iqbal J.
Sidhu M.S.
spellingShingle Iqbal J.
Sidhu M.S.
A taxonomic overview and pilot study for evaluation of Augmented Reality based posture matching technique using Technology Acceptance Model
author_sort Iqbal J.
title A taxonomic overview and pilot study for evaluation of Augmented Reality based posture matching technique using Technology Acceptance Model
title_short A taxonomic overview and pilot study for evaluation of Augmented Reality based posture matching technique using Technology Acceptance Model
title_full A taxonomic overview and pilot study for evaluation of Augmented Reality based posture matching technique using Technology Acceptance Model
title_fullStr A taxonomic overview and pilot study for evaluation of Augmented Reality based posture matching technique using Technology Acceptance Model
title_full_unstemmed A taxonomic overview and pilot study for evaluation of Augmented Reality based posture matching technique using Technology Acceptance Model
title_sort taxonomic overview and pilot study for evaluation of augmented reality based posture matching technique using technology acceptance model
publisher Elsevier B.V.
publishDate 2023
_version_ 1806424251899576320
score 13.187197

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