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Predicting user acceptance of e-learning applications: web usage mining approach / Noraida Haji Ali ... [et al.]

The successful implementation of e-learning applications is closely related to user acceptance. Previous studies show the use of log files data in the web usage mining to predict user acceptance. However, the log files data did not record the entire behaviour of users who use the e-learning applicat...

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Main Authors: Haji Ali, Noraida, W. Hamzah, W.M. Amir Fazamin, Yusoff, Hafiz, Saman, Md Yazid
Format: Article
Language:English
Published: UPENA 2015
Online Access:https://ir.uitm.edu.my/id/eprint/59613/1/59613.pdf
https://ir.uitm.edu.my/id/eprint/59613/
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id my.uitm.ir.59613
record_format eprints
spelling my.uitm.ir.596132022-05-15T16:19:24Z https://ir.uitm.edu.my/id/eprint/59613/ Predicting user acceptance of e-learning applications: web usage mining approach / Noraida Haji Ali ... [et al.] Haji Ali, Noraida W. Hamzah, W.M. Amir Fazamin Yusoff, Hafiz Saman, Md Yazid The successful implementation of e-learning applications is closely related to user acceptance. Previous studies show the use of log files data in the web usage mining to predict user acceptance. However, the log files data did not record the entire behaviour of users who use the e-learning applications that are embedded in a website. Therefore, this study has proposed the web usage mining using Tin Can API to gather user’s data. The Tin Can API will be used to track and to record user behaviours in e-learning applications. The generated data have been mapped to the Unified Theory of Acceptance and Use of Technology (UTAUT) for predicting of user acceptance of e-learning applications. From regression analysis, the results showed the performance expectancy and effort expectancy were found directly and significantly related to the intention to use e-learning applications. Behavioural intention and facilitating conditions also were found directly and significantly related to the behaviour of use of e-learning applications. Thus, the approach of web usage mining using Tin Can API can be used to gather usage data for predicting user acceptance of e-learning applications. UPENA 2015 Article PeerReviewed text en https://ir.uitm.edu.my/id/eprint/59613/1/59613.pdf (2015) Predicting user acceptance of e-learning applications: web usage mining approach / Noraida Haji Ali ... [et al.]. International Journal on E-Learning and Higher Education (IJELHE), 4 (5). pp. 81-96. ISSN 1985-8620
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
description The successful implementation of e-learning applications is closely related to user acceptance. Previous studies show the use of log files data in the web usage mining to predict user acceptance. However, the log files data did not record the entire behaviour of users who use the e-learning applications that are embedded in a website. Therefore, this study has proposed the web usage mining using Tin Can API to gather user’s data. The Tin Can API will be used to track and to record user behaviours in e-learning applications. The generated data have been mapped to the Unified Theory of Acceptance and Use of Technology (UTAUT) for predicting of user acceptance of e-learning applications. From regression analysis, the results showed the performance expectancy and effort expectancy were found directly and significantly related to the intention to use e-learning applications. Behavioural intention and facilitating conditions also were found directly and significantly related to the behaviour of use of e-learning applications. Thus, the approach of web usage mining using Tin Can API can be used to gather usage data for predicting user acceptance of e-learning applications.
format Article
author Haji Ali, Noraida
W. Hamzah, W.M. Amir Fazamin
Yusoff, Hafiz
Saman, Md Yazid
spellingShingle Haji Ali, Noraida
W. Hamzah, W.M. Amir Fazamin
Yusoff, Hafiz
Saman, Md Yazid
Predicting user acceptance of e-learning applications: web usage mining approach / Noraida Haji Ali ... [et al.]
author_facet Haji Ali, Noraida
W. Hamzah, W.M. Amir Fazamin
Yusoff, Hafiz
Saman, Md Yazid
author_sort Haji Ali, Noraida
title Predicting user acceptance of e-learning applications: web usage mining approach / Noraida Haji Ali ... [et al.]
title_short Predicting user acceptance of e-learning applications: web usage mining approach / Noraida Haji Ali ... [et al.]
title_full Predicting user acceptance of e-learning applications: web usage mining approach / Noraida Haji Ali ... [et al.]
title_fullStr Predicting user acceptance of e-learning applications: web usage mining approach / Noraida Haji Ali ... [et al.]
title_full_unstemmed Predicting user acceptance of e-learning applications: web usage mining approach / Noraida Haji Ali ... [et al.]
title_sort predicting user acceptance of e-learning applications: web usage mining approach / noraida haji ali ... [et al.]
publisher UPENA
publishDate 2015
url https://ir.uitm.edu.my/id/eprint/59613/1/59613.pdf
https://ir.uitm.edu.my/id/eprint/59613/
_version_ 1732948407294623744
score 13.211869

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