A Check on Planning Access for Blended Learning
Chong Pei Yee1, Zamhar Iswandono bin Awang Ismail2, Esmadi Abu Abu Seman3

1Chong Pei Yee, Department of Computer Science Unit, Labuan Matriculation College, Labuan Federal Territory, Malaysia.
2Zamhar Iswandono bin Awang Ismail, Department of Computing and Informatics, University Malaysia Sabah Labuan International Campus, Labuan Federal Territory, Malaysia.
3Esmadi Abu Abu Seman, Department of Computing and Informatics, University Malaysia Sabah Labuan International Campus, Labuan Federal Territory, Malaysia.
Manuscript received on 21 August 2019 | Revised Manuscript received on 11 September 2019 | Manuscript Published on 17 September 2019 | PP: 1338-1345 | Volume-8 Issue-2S8 August 2019 | Retrieval Number: B10640882S819/2019©BEIESP | DOI: 10.35940/ijrte.B1064.0882S819
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: Higher learning institutions favor implementing blended learning to achieve their educational goals and learning objectives. The purpose of this review is to analyze the ideal blended learning model and the recommendations for planning future blended learning activities. Nine articles published from 2013 to 2018 which provided the frameworks or models and future suggestions were appraised. This review revealed that blended learning is not about using Information, Communication, and Technology (ICT) tools anymore but how the learning process is being blended to deliver effectiveness in learning. The review also discovered that in future blended learning design has to include collaboration among educators and how is the learning process can be applied to actual life. The culture of an educational organization is also an important focus.
Keywords: Blended Learning, Technology in Education, Educational Framework, Curriculum Design, Higher Education.
Scope of the Article: Artificial Intelligence and Machine Learning