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...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Penerbit UiTM (UiTM Press)
2016
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| Online Access: | https://ir.uitm.edu.my/id/eprint/16122/ |
| _version_ | 1848803924163690496 |
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| author | Haji Ali, Noraida W. Hamzah, W.M. Amir Fazamin Yusoff, Hafiz Saman, Md Yazid |
| author_facet | Haji Ali, Noraida W. Hamzah, W.M. Amir Fazamin Yusoff, Hafiz Saman, Md Yazid |
| author_sort | Haji Ali, Noraida |
| building | UiTM Institutional Repository |
| collection | Online Access |
| 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. |
| first_indexed | 2025-11-14T21:46:58Z |
| format | Article |
| id | uitm-16122 |
| institution | Universiti Teknologi MARA |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-14T21:46:58Z |
| publishDate | 2016 |
| publisher | Penerbit UiTM (UiTM Press) |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | uitm-161222017-02-16T04:46:13Z https://ir.uitm.edu.my/id/eprint/16122/ Predicting user acceptance of e-learning applications: web usage mining approach / Noraida Haji Ali … [et al.] ijelhe Haji Ali, Noraida W. Hamzah, W.M. Amir Fazamin Yusoff, Hafiz Saman, Md Yazid Computers in education. Information technology Blended learning. Computer assisted instruction. Programmed instruction 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. Penerbit UiTM (UiTM Press) 2016 Article PeerReviewed text en https://ir.uitm.edu.my/id/eprint/16122/1/AJ_NORAIDA%20HAJI%20ALI%20IJEL%2016.pdf Haji Ali, Noraida and W. Hamzah, W.M. Amir Fazamin and Yusoff, Hafiz and Saman, Md Yazid (2016) Predicting user acceptance of e-learning applications: web usage mining approach / Noraida Haji Ali … [et al.]. (2016) International Journal on E-Learning and Higher Education (IJELHE) <https://ir.uitm.edu.my/view/publication/International_Journal_on_E-Learning_and_Higher_Education_=28IJELHE=29.html>, 4. pp. 82-95. ISSN 1985-8620 https://journalined.uitm.edu.my/ |
| spellingShingle | Computers in education. Information technology Blended learning. Computer assisted instruction. Programmed instruction 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.] |
| title | 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_short | 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.] |
| topic | Computers in education. Information technology Blended learning. Computer assisted instruction. Programmed instruction |
| url | https://ir.uitm.edu.my/id/eprint/16122/ https://ir.uitm.edu.my/id/eprint/16122/ |