Please use this identifier to cite or link to this item:
https://hdl.handle.net/1959.11/55314
Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Alharbi, Hadeel | en |
dc.contributor.author | Sandhu, Kamaljeet | en |
dc.date.accessioned | 2023-07-21T23:24:53Z | - |
dc.date.available | 2023-07-21T23:24:53Z | - |
dc.date.issued | 2019-01 | - |
dc.identifier.citation | International Journal of Innovation in the Digital Economy, 10(1), p. 31-42 | en |
dc.identifier.issn | 1947-8313 | en |
dc.identifier.issn | 1947-8305 | en |
dc.identifier.uri | https://hdl.handle.net/1959.11/55314 | - |
dc.description.abstract | <p>This article adopts e-learning analytics principles to provide a new model to explain the acceptance behaviour of recommendersystems adoption with e-learning in the Saudi Arabian context and reflects the increasing focus of the Saudi Arabian Ministry of Education on delivering online educational services. This focus has come at the necessity to improve overall access to the education system, and higher education and has been driven with evidence of improving learning outcomes with electronic learning (e-learning) information and instructional technology with the use of e-learning analyticsrecommendersystems. Thisreview utilisesthe technology acceptance model as a theoretical framework to generate a set of interlocked hypothesesthat go to explaining student behaviourstowards technological acceptance and continued usage intention of recommender systems.</p> | en |
dc.language | en | en |
dc.publisher | IGI Global | en |
dc.relation.ispartof | International Journal of Innovation in the Digital Economy | en |
dc.title | New Discoveries for User Acceptance of E-Learning Analytics Recommender Systems in Saudi Arabia | en |
dc.type | Journal Article | en |
dc.identifier.doi | 10.4018/IJIDE.2019010103 | en |
local.contributor.firstname | Hadeel | en |
local.contributor.firstname | Kamaljeet | en |
local.profile.school | UNE Business School | en |
local.profile.email | ksandhu@une.edu.au | en |
local.output.category | C1 | en |
local.record.place | au | en |
local.record.institution | University of New England | en |
local.publisher.place | United States of America | en |
local.format.startpage | 31 | en |
local.format.endpage | 42 | en |
local.peerreviewed | Yes | en |
local.identifier.volume | 10 | en |
local.identifier.issue | 1 | en |
local.contributor.lastname | Alharbi | en |
local.contributor.lastname | Sandhu | en |
dc.identifier.staff | une-id:ksandhu | en |
local.profile.orcid | 0000-0003-4624-6834 | en |
local.profile.role | author | en |
local.profile.role | author | en |
local.identifier.unepublicationid | une:1959.11/55314 | en |
dc.identifier.academiclevel | Academic | en |
dc.identifier.academiclevel | Academic | en |
local.title.maintitle | New Discoveries for User Acceptance of E-Learning Analytics Recommender Systems in Saudi Arabia | en |
local.output.categorydescription | C1 Refereed Article in a Scholarly Journal | en |
local.search.author | Alharbi, Hadeel | en |
local.search.author | Sandhu, Kamaljeet | en |
local.uneassociation | Yes | en |
local.atsiresearch | No | en |
local.sensitive.cultural | No | en |
local.year.published | 2019 | en |
local.fileurl.closedpublished | https://rune.une.edu.au/web/retrieve/0a1d1093-d5c9-49e1-95eb-ed3b17efe145 | en |
local.subject.for2020 | 350303 Business information systems | en |
local.subject.seo2020 | 220408 Information systems | en |
local.profile.affiliationtype | UNE Affiliation | en |
local.profile.affiliationtype | UNE Affiliation | en |
Appears in Collections: | Journal Article UNE Business School |
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