Applying Channel Expansion and Self-Determination Theory in predicting use behaviour of cloud-based VLE

Teck-Soon Hew and Sharifah Latifah Syed A. Kadir

Behaviour and Information Technology, 2017, vol. 36, issue 9, 875-896

Abstract: Existence of cloud computing has led to the emergence of cloud-based virtual learning environments (VLEs). Unlike existing grid-based VLE studies which engaged extrinsic motivational drivers, e.g. TAM, UTAUT, etc., this study examined the effects of intrinsic motivational factors namely the Self-Determination Theory. The existing studies also focused on the perspective of intention to use or continuance intention among undergraduates. However, this study examined the actual use behaviour and instructional effectiveness of a cloud-based VLE among teachers. Channel Expansion Theory, VLE attributes and demographics are also incorporated in predicting use behaviour. The instrument has been rigorously developed and validated and 608 teachers were selected in two waves (T1 and T2) of survey using random sampling from 351 schools nationwide. multi-layer perceptron (MLP) using neural network was used to analyse the data. All predictors were found to be relevant in predicting use behaviour. The study may offer an opportunity for a new paradigm shift from behavioural intention and continuance intention to actual use behaviour. It also provides the theoretical foundation for parametric hypothesis testing in future related studies. Several theoretical and practical implications for scholars, Ministry of Education, VLE providers, school authorities and educationists were discussed.

Date: 2017
References: Add references at CitEc
Citations: View citations in EconPapers (2)

Downloads: (external link)
http://hdl.handle.net/10.1080/0144929X.2017.1307450 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:taf:tbitxx:v:36:y:2017:i:9:p:875-896

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/tbit20

DOI: 10.1080/0144929X.2017.1307450

Access Statistics for this article

Behaviour and Information Technology is currently edited by Dr Panos P Markopoulos

More articles in Behaviour and Information Technology from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().