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DOI: 10.14569/IJARAI.2014.031105
PDF

Mobile Learning-system usage: Scale development and empirical tests

Author 1: Saleh Alharbi
Author 2: Steve Drew

International Journal of Advanced Research in Artificial Intelligence(IJARAI), Volume 3 Issue 11, 2014.

  • Abstract and Keywords
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Abstract: Mobile technologies have changed the shape of learning for learners, society, and education providers. Consequently, mobile learning has become a core component in modern education. Nevertheless, introducing mobile learning systems does not automatically guarantee that learners will develop a positive behavioural intention to use it and therefore use it. Thus, acceptance-of-technology and system-success studies have increased. As yet, however, much of the research regarding understanding students’ behavioural intention to use mobile learning systems seems to suffer from several shortcomings. On top of that, there is no common cognitive theoretical foundation. This study introduces a theoretical framework that combines the Unified Theory of Acceptance and Use of Technology (UTAUT) and Information System (IS) Success Model. This integration resulted in three success measures and two acceptance constructs. The success measures included the following: a) information quality, b) system quality, and c) user satisfaction; whilst the following were the acceptance measures: a) effort expectancy, b) performance expectancy, and c) social influence. Further, this study introduces lecture attitude as a new construct that is believed to moderate students’ behavioural intention. The relationships between the different factors form the research hypotheses.

Keywords: Mobile learning; Mobile learning; Higher education; UTAUT; IS Success

Saleh Alharbi and Steve Drew, “Mobile Learning-system usage: Scale development and empirical tests” International Journal of Advanced Research in Artificial Intelligence(IJARAI), 3(11), 2014. http://dx.doi.org/10.14569/IJARAI.2014.031105

@article{Alharbi2014,
title = {Mobile Learning-system usage: Scale development and empirical tests},
journal = {International Journal of Advanced Research in Artificial Intelligence},
doi = {10.14569/IJARAI.2014.031105},
url = {http://dx.doi.org/10.14569/IJARAI.2014.031105},
year = {2014},
publisher = {The Science and Information Organization},
volume = {3},
number = {11},
author = {Saleh Alharbi and Steve Drew}
}



Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.

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