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Evaluating students' emotional response in video-based learning using Kansei Engineering / Hazlina Adnan

In less than ten years, a well-designed video-based online learning material can be a powerful learning tool that evokes students' positive emotions while using it. This rewards a valuable learning experience for all students. To enable the development of such learning materials, the knowledge...

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Main Author: Adnan, Hazlina
Format: Thesis
Language:English
Published: 2016
Subjects:
TJ Mechanical engineering and machinery
Online Access:https://ir.uitm.edu.my/id/eprint/63270/1/63270.pdf
https://ir.uitm.edu.my/id/eprint/63270/
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spelling my.uitm.ir.632702022-08-04T07:20:29Z https://ir.uitm.edu.my/id/eprint/63270/ Evaluating students' emotional response in video-based learning using Kansei Engineering / Hazlina Adnan Adnan, Hazlina TJ Mechanical engineering and machinery In less than ten years, a well-designed video-based online learning material can be a powerful learning tool that evokes students' positive emotions while using it. This rewards a valuable learning experience for all students. To enable the development of such learning materials, the knowledge of how design elements influence emotion should be continued so that we could engineer the emotion into video-based online learning materials. That is the main objectives of this research. The research was conducted using Kansei Engineering approach which has been adapted from the pioneer of KE, Prof. Dr. Mitsuo Nagamachi. Using 10 specimens of video obtained from YouTube, 55 Kansei Emotion Words (KW), and 32 evaluation subjects, this research performed evaluation experiment to assess students' emotional response to video-based online learning materials. Multivariate analysis were performed to the averaged evaluation result acquired from subjects to identify the semantic space for video-based online learning material for higher education and investigate the associated design elements to be used as a guide in designing video-based online learning material, which embeds target emotion in its design. The findings in this research reveal five pillars of Kansei semantic space of emotions for video-based online learning materials. Based on Factor Analysis, it reveals three main pillars; professional-motivated, fun, joking-humorous and two additional pillars; deceptive and puzzled. Other than that, this research also described design elements of video-based online learning materials that evoke specific emotions based on five pillars that identified after performed Partial Least Square Analysis. Although there are some limitations and constraints during the research are conducted, they have contributed little portion of knowledge to confirm some important emotions in an online learning environment particularly in video-based learning. 2016 Thesis NonPeerReviewed text en https://ir.uitm.edu.my/id/eprint/63270/1/63270.pdf Evaluating students' emotional response in video-based learning using Kansei Engineering / Hazlina Adnan. (2016) Masters thesis, thesis, Universiti Teknologi MARA.
institution Universiti Teknologi Mara
building Tun Abdul Razak Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Mara
content_source UiTM Institutional Repository
url_provider http://ir.uitm.edu.my/
language English
topic TJ Mechanical engineering and machinery
spellingShingle TJ Mechanical engineering and machinery
Adnan, Hazlina
Evaluating students' emotional response in video-based learning using Kansei Engineering / Hazlina Adnan
description In less than ten years, a well-designed video-based online learning material can be a powerful learning tool that evokes students' positive emotions while using it. This rewards a valuable learning experience for all students. To enable the development of such learning materials, the knowledge of how design elements influence emotion should be continued so that we could engineer the emotion into video-based online learning materials. That is the main objectives of this research. The research was conducted using Kansei Engineering approach which has been adapted from the pioneer of KE, Prof. Dr. Mitsuo Nagamachi. Using 10 specimens of video obtained from YouTube, 55 Kansei Emotion Words (KW), and 32 evaluation subjects, this research performed evaluation experiment to assess students' emotional response to video-based online learning materials. Multivariate analysis were performed to the averaged evaluation result acquired from subjects to identify the semantic space for video-based online learning material for higher education and investigate the associated design elements to be used as a guide in designing video-based online learning material, which embeds target emotion in its design. The findings in this research reveal five pillars of Kansei semantic space of emotions for video-based online learning materials. Based on Factor Analysis, it reveals three main pillars; professional-motivated, fun, joking-humorous and two additional pillars; deceptive and puzzled. Other than that, this research also described design elements of video-based online learning materials that evoke specific emotions based on five pillars that identified after performed Partial Least Square Analysis. Although there are some limitations and constraints during the research are conducted, they have contributed little portion of knowledge to confirm some important emotions in an online learning environment particularly in video-based learning.
format Thesis
author Adnan, Hazlina
author_facet Adnan, Hazlina
author_sort Adnan, Hazlina
title Evaluating students' emotional response in video-based learning using Kansei Engineering / Hazlina Adnan
title_short Evaluating students' emotional response in video-based learning using Kansei Engineering / Hazlina Adnan
title_full Evaluating students' emotional response in video-based learning using Kansei Engineering / Hazlina Adnan
title_fullStr Evaluating students' emotional response in video-based learning using Kansei Engineering / Hazlina Adnan
title_full_unstemmed Evaluating students' emotional response in video-based learning using Kansei Engineering / Hazlina Adnan
title_sort evaluating students' emotional response in video-based learning using kansei engineering / hazlina adnan
publishDate 2016
url https://ir.uitm.edu.my/id/eprint/63270/1/63270.pdf
https://ir.uitm.edu.my/id/eprint/63270/
_version_ 1740829087710052352
score 13.211869

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