A knowledge management framework for e-learning based on human factor engineering

Citation

Chin, Sylvia Ping Ping (2015) A knowledge management framework for e-learning based on human factor engineering. PhD thesis, Multimedia University.

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Abstract

Remote and rural communities are often disadvantaged in terms of access to infrastructure, information and opportunities. Two specific problems are crucial to promote sustainable online learning for the remote communities. First, presenting learning content may not be sufficient to help students to improve their learning as they are not competent to make meaning from the information presented. Second, students are often not competent to articulate information from different perspectives or discuss complex issue. The author investigated whether Knowledge Management (KM) processes, e-learning Principles and Human factors engineering will promote meaningful learning and consequently sustainable online learning for the remote community. The contributions are in five aspects: (i) instructional design of learning activities especially role playing (ii) design of learning content, (iii) design of hint-based teaching-learning strategies to scaffold learning and (iv) design of technology-enhanced collaborative learning and (v) the design and development of an integrated systematic web and system usability evaluation format to help with the design and development of usability-efficient and usability-effective learning activities and consequently, learner-centered, learner effective and cost effective solution. The author has customized the interactive e-learning course content in the KM-e-learning usability framework. This framework has been used for the development of an instructional model incorporating a germane pedagogical setup which coalesce interactive learning activities and learner-centered factors. The author illustrates this process with a unique case study from the SMK Bario, Sarawak to show the proposed framework have been adopted to make a successful transition to a blended learning community approach that combines face-to-face sessions with distance and asynchronous communication.

Item Type: Thesis (PhD)
Additional Information: Call No.: QA76.9.H85 C45 2015
Uncontrolled Keywords: Human-computer interaction
Subjects: Q Science > QA Mathematics > QA71-90 Instruments and machines > QA75.5-76.95 Electronic computers. Computer science
Divisions: Faculty of Computing and Informatics (FCI)
Depositing User: Ms Nurul Iqtiani Ahmad
Date Deposited: 27 Jan 2016 08:53
Last Modified: 27 Jan 2016 08:53
URII: http://shdl.mmu.edu.my/id/eprint/6294

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