Please use this identifier to cite or link to this item: https://hdl.handle.net/1959.11/21961
Title: A Multifactorial Analysis of the Acceptance of Recommender System for Saudi Universities the Literature Revisited
Contributor(s): Alharbi, Hadeel (author); Sandhu, Kamaljeet  (author)
Publication Date: 2017
Handle Link: https://hdl.handle.net/1959.11/21961
Abstract: Technology for learning is increasingly about enhancing users' interactions with the technology to improve learning outcomes. Of particular importance however to improving educational outcomes is the need to complement the technological advancements with advances in the educational practices of teachers to broaden the uptake of new technologies for learning. Recommender Systems are personalised services that aim to predict a learner's interest in some services or items such as courses, grades, references, links, etc. available in e-learning applications and to provide appropriate recommendations. Such systems can potentially enhance student learning by providing students with a more hands on, interactive and tailored learning experience.
Publication Type: Book Chapter
Source of Publication: Design Solutions for User-Centric Information Systems, p. 90-105
Publisher: Information Science Reference
Place of Publication: Hershey, United States of America
ISBN: 9781522519447
Field of Research (FOR): 080611 Information Systems Theory
080609 Information Systems Management
080610 Information Systems Organisation
HERDC Category Description: B1 Chapter in a Scholarly Book
Other Links: http://nla.gov.au/anbd.bib-an59614885
Series Name: Advances in Human and Social Aspects of Technology (AHSAT)
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Appears in Collections:Book Chapter

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