Factors predicting mobile learning utilization among undergraduates in a public university, Oman
Recently, the use of mobile learning has become widespread. Mobile learning refers to the use of mobile or handheld devices such as mobile phones, laptops, smart phones, and tablets in order to support learning at any place and at any time in teaching and learning. Despite the advantages of using mo...
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| Main Author: | |
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| Format: | Thesis |
| Language: | English |
| Published: |
2017
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| Online Access: | http://psasir.upm.edu.my/id/eprint/70706/1/FPP%202017%2010%20IR.pdf http://psasir.upm.edu.my/id/eprint/70706/ |
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| Summary: | Recently, the use of mobile learning has become widespread. Mobile learning refers to the use of mobile or handheld devices such as mobile phones, laptops, smart phones, and tablets in order to support learning at any place and at any time in teaching and learning. Despite the advantages of using mobile learning for learning purposes in enhancing the quality of learning, it is not fully used in higher education in Oman. The review of previous studies shows that despite much research on mobile learning, only a few of the studies have investigated students’ utilization level. Hence, the purpose of this study was to identify whether the predictive factors significantly influenced the utilization of mobile learning. Moreover, in determining the level of the utilization of mobile learning, the study also sought to investigate the role of behavioral intention as a mediator as well as gender and field of study as moderators, and finally, to develop a model for the utilization of mobile learning. This study not only tested the Unified Theory of Acceptance and Use of Technology (UTAUT) itself, but also combined some factors from Mobile Learning Acceptance Model (MLAM) and Liew’s et al. Model which are both specific models for mobile learning.
This study was based on a quantitative descriptive design with a sample size of 468 undergraduate students in the third-fourth years at Sultan Qaboos University (SQU). The sample was selected based on the proportional stratified and cluster sampling technique. The main instrument used was a questionnaire which was adapted from previous studies and whose content validity was checked by a panel of experts. A pilot study was conducted on 40 students to assist the reliability of the instrument which ranged in value from 0.82 to 0.94 on Cronbach’s alpha.
The data were analyzed descriptively using IBM SPSS statistics program and inferentially using the Analysis of Moment Structures (AMOS) program. The descriptive findings indicated that the utilization of mobile learning level was high. The perceived performance expectancy, effort expectancy, behavioural intention, facilitating conditions, and self-management factors level were found to be high, whereas social influence was at a moderate level. Among the 21 hypotheses tested, 11 were supported and 10 were not. The most salient factor influencing the utilization of mobile learning was performance expectancy (β=.27, P=.000), followed by self-management (β=.26, P=.000), behavioural intention (β=.25, P=.000) and facilitating conditions (β=.22, P=.000). Further, the influence of effort expectancy (β=.26, P=.001) and social influence (β=.36, P=.001) were found to be fully mediated by behavioral intention. Gender was a moderator and influenced effort expectancy and self-management significantly, while field of study also significantly moderated the influence of performance expectancy, facilitating conditions and self-management towards the utilization of mobile learning. The results attained from the analyses also produced a model that predicts the utilization of mobile learning among the undergraduates and which explained 50% of perceived the utilization of mobile learning and 26% of behavioral intention towards the utilization of mobile learning. Several implications were also drawn from the findings of this study. The proposed model is a definitive model that synthesizes what is known, and is likely to be a useful model that provides knowledge to guide future research in related fields. |
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