The impact of self-efficacy and perceived system efficacy on effectiveness of virtual training systems
Dawei Jia,
Asim Bhatti and
Saeid Nahavandi
Behaviour and Information Technology, 2014, vol. 33, issue 1, 16-35
Abstract:
This study developed and tested a research model which examined the impact of user perceptions of self-efficacy (SE) and virtual environment (VE) efficacy on the effectiveness of VE training systems. The model distinguishes between the perceptions of one's own capability to perform trained tasks effectively and the perceptions of system performance, regarding the established parameters from literature. Specifically, the model posits that user perceptions will have positive effects on task performance and memory. Seventy-six adults participated in a VE in a controlled experiment, designed to empirically test the model. Each participant performed a series of object assembly tasks. The task involved selecting, rotating, releasing, inserting and manipulating 3D objects. Initially, the results of factor analysis demonstrated dimensionality of two user perception measures and produced a set of empirical validated factors underlining the VE efficacy. The results of regression analysis revealed that SE had a significant positive effect on perceived VE efficacy. No significant effects were found of perceptions on performance and memory. Furthermore, the study provided insights into the relationships between the perception measures and performance measures for assessing the efficacy of VE training systems. The study also addressed how well users learn, perform, adapt to and perceive the VE training, which provides valuable insight into the system efficacy. Research and practical implications are presented at the end of the paper.
Date: 2014
References: Add references at CitEc
Citations:
Downloads: (external link)
http://hdl.handle.net/10.1080/0144929X.2012.681067 (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:33:y:2014:i:1:p:16-35
Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/tbit20
DOI: 10.1080/0144929X.2012.681067
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 ().