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

Haji Ali, Noraida and W. Hamzah, W.M. Amir Fazamin and Yusoff, Hafiz and Saman, Md Yazid (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

Abstract

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.

Metadata

Item Type: Article
Creators:
Creators
Email / ID Num.
Haji Ali, Noraida
UNSPECIFIED
W. Hamzah, W.M. Amir Fazamin
UNSPECIFIED
Yusoff, Hafiz
UNSPECIFIED
Saman, Md Yazid
UNSPECIFIED
Divisions: Universiti Teknologi MARA, Selangor
Journal or Publication Title: International Journal on E-Learning and Higher Education (IJELHE)
ISSN: 1985-8620
Volume: 4
Number: 5
Page Range: pp. 81-96
Date: 2015
URI: https://ir.uitm.edu.my/id/eprint/59613
Edit Item
Edit Item

Download

[thumbnail of 59613.pdf] Text
59613.pdf

Download (812kB)

ID Number

59613

Indexing

Statistic

Statistic details