Factors influencing utilisation of ubiquitous technology among undergraduates in Malaysian Technical Universities

Ubiquitous technology such as laptops, smartphones and tablets have been widely used by many undergraduates in institutions of higher learning. However, not much is known of their utilisation level and the factors that influence its utilisation. Therefore, the main objectives of this study are to de...

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Bibliographic Details
Main Author: Sedek, Muliati
Format: Thesis
Language:English
Published: 2014
Online Access:http://psasir.upm.edu.my/id/eprint/39371/1/FPP%202014%2023%20IR.pdf
http://psasir.upm.edu.my/id/eprint/39371/
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Summary:Ubiquitous technology such as laptops, smartphones and tablets have been widely used by many undergraduates in institutions of higher learning. However, not much is known of their utilisation level and the factors that influence its utilisation. Therefore, the main objectives of this study are to determine: i) the level of ubiquitous technology utilisation; ii) the level of competency in using ubiquitous technology, iii) whether the selected factors (technology competency, performance expectancy, effort expectancy, facilitating conditions, social status and behavioural intention) significantly influence ubiquitous technology utilisation; iv) whether behavioural intention acts as a mediator; v) whether gender acts as a moderator and finally vi) to develop a model that can predict the utilisation of ubiquitous technology among the undergraduates. This study was based on a quantitative descriptive research using a set of questionnaire. The population of the study comprised of third-year undergraduates (N=4,247) from Malaysian Technical Universities (MTUN). Based on the Raosoft software, the minimum sample size for this study was 353 respondents. However, a total of 493 questionnaires were distributed among the undergraduates. The respondents were selected based on the proportional stratified and random sampling technique. The research instrument was adapted from previous studies and validated by a panel of experts from the field of Educational Technology. The research instrument was divided into three sections, namely, i) demographic data, ii) ubiquitous technology utilisation and iii) factors related to the use of ubiquitous technology. The reliability of the instrument ranged from 0.83 to 0.98. The data was analysed descriptively (frequency, mean and standard deviation) using the IBM SPSS Statistics (SPSS) version 20 and inferentially using the Analysis of Moment Structures (AMOS) version 20. The results of this study indicated that both the utilisation of ubiquitous technology and technology competency among the undergraduates were at a moderate level. The undergraduates’ perceived performance expectancy, effort expectancy, behavioural intention, facilitating conditions and social status factors level were found to be high. The performance expectancy (β=.485, p= .000) was found to be the most salient factor influencing the utilisation of ubiquitous technology, followed by technology competency (β=.306, p=.000), facilitating conditions (β=.216, p=.000) and behavioural intention (β=.156, p=.000). Finally, the influences of social status (β=.494, p=.000) and effort expectancy (β=.267, p=.000) towards the utilisation of ubiquitous technology were found to be mediated by behavioural intention. Gender factor was identified to influence effort expectancy significantly and was more significant amongst female undergraduates. The results attained from the analysis also produced a model that predicts the utilisation of ubiquitous technology among the undergraduates. The model was confirmed to account for 63% of the variance (adjusted R²) in ubiquitous technology utilisation. Several implications were also drawn from the results of the study. This study did not only test the Unified Theory of Acceptance and Use of Technology (UTAUT) model itself, but has been expanded by adding one variable; the technology competency from Theory of Acceptance Model (TAM). By encompassing UTAUT, one mediator and moderator, as well as technology competency; the proposed predictive model is a definitive model that synthesizes what is known and provides a foundation to guide future research in a related field of study.