Data warehouse system for blended learning in institutions of higher education/ Azman Ta’a …[et al.]

Ta'a, Azman and Abu Bakar, Mohamad Shahbani (2017) Data warehouse system for blended learning in institutions of higher education/ Azman Ta’a …[et al.]. e-Academia Journal, 6 (2). pp. 144-155. ISSN 2289-6589

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Abstract

Online learning is a growing trend for lecturers and students in Malaysian Institutions of Higher Education (IHE) today. Malaysia’s National e-Learning Policy aims that 30% of all higher education courses is delivered online by 2015. Currently, 90% of Malaysian IHEs have online learning policy, and almost 70 percent have imposed it on their lecturers and students. However, there is a lack of approaches to systematically monitor the effectiveness of online learning implementation. This paper demonstrates the integration of several data sources of online learning systems in UUM (known as UUMLearning) to systematically monitor the usage of blended learning system. The information required to be captured and analyzed is determined prior to performing data preprocessing, and produce results of monitoring blended learning usage. The Business Intelligence and Data Warehouse method have been used to capture, process, integrate and analyze the blended learning data in order to monitor the usage of blended e-learning technology among the lecturers. The results have shown that the usage of blended learning can be monitored successfully by lecturers and university management.

Item Type: Article
Creators:
CreatorsEmail
Ta'a, Azmanazman@uum.edu.my
Abu Bakar, Mohamad ShahbaniUNSPECIFIED
UNSPECIFIEDUNSPECIFIED
Subjects: L Education > LB Theory and practice of education > Blended learning. Computer assisted instruction. Programmed instruction
Divisions: Universiti Teknologi MARA, Terengganu
Journal or Publication Title: e-Academia Journal
ISSN: 2289-6589
Volume: 6
Number: 2
Page Range: pp. 144-155
Official URL: http://journale-academiauitmt.uitm.edu.my/v2/index...
Item ID: 18808
Uncontrolled Keywords: Online learning; Blended learning; Business intelligence; Data warehouse; Data analytic
Last Modified: 30 Jan 2018 06:52
Depositing User: Perpustakaan Cendekiawan UiTM Caw Terengganu
URI: http://ir.uitm.edu.my/id/eprint/18808

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