4.5 Article

Predicting instructional effectiveness of cloud-based virtual learning environment

Journal

INDUSTRIAL MANAGEMENT & DATA SYSTEMS
Volume 116, Issue 8, Pages 1557-1584

Publisher

EMERALD GROUP PUBLISHING LTD
DOI: 10.1108/IMDS-11-2015-0475

Keywords

Self Determination Theory; Artificial neural networks; Virtual learning environment (VLE); Channel expansion theory; Instructional effectiveness

Funding

  1. University of Malaya [PG037-2014B]

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Purpose - Cloud computing technology is advancing and expanding at an explosive rate. These advancements have further extended the capabilities of the virtual learning environment (VLE) to provide accessibility anywhere, anytime where educational resources can be saved, modified, retrieved and shared on the cloud. The purpose of this paper is to examine the predictors of instructional effectiveness of cloud computing VLE by extending the Self Determination and Channel Expansion Theory with external constructs of VLE interactivity, content design, school support, trust in website, knowledge sharing attitude and demographic variables. Design/methodology/approach - Random sampling data were collected in two waves of nation-wide survey and analyzed with artificial neural network approach. Findings - SDT, CET, content design, interactivity, trust in website, school support and demographics significantly predict instructional effectiveness. Research limitations/implications - The study has provided a new paradigm shift from investigating the behavioral intention and continuance intention to the effectiveness of an information system. It advocates that quality of research may be improved by adhering to the basic research methodology starting from rigorous instrument development and validation to future research direction. Practical implications - The research provides implications to Ministry of Education, the VLE content and service providers, scholars and practitioners. Social implications - The findings of the study may further improve the quality of living of the society when the instructional effectiveness of the cloud-based VLE is further enhanced. Originality/value - Existing grid computing VLE studies have focussed on the acceptance of students and teachers and not its instructional effectiveness. Unlike existing studies that examined extrinsic motivational factors (e.g. TAM, UTAUT), this study uses intrinsic motivational factors (e.g. relatedness, competence and autonomy) as well as perceived media richness. Malaysia is the first nation to implement the VLE at a national scale and the findings from this study will provide a new insight on the determinants of instructional effectiveness of the VLE system.

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