Investigating the Determinants and Age and Gender Differences in the Acceptance of Mobile Learning

博士 === 國立彰化師範大學 === 商業教育學系 === 96 === With the proliferation of mobile computing technology, mobile learning (m-learning) will play a vital role in the rapidly growing electronic learning market. M-learning is the delivery of learning to students anytime and anywhere through the use of the wireless...

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Bibliographic Details
Main Authors: Hsiu-Yuan Wang, 王秀媛
Other Authors: Ming-Cheng Wu
Format: Others
Language:en_US
Published: 2008
Online Access:http://ndltd.ncl.edu.tw/handle/84518058202038348723
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Summary:博士 === 國立彰化師範大學 === 商業教育學系 === 96 === With the proliferation of mobile computing technology, mobile learning (m-learning) will play a vital role in the rapidly growing electronic learning market. M-learning is the delivery of learning to students anytime and anywhere through the use of the wireless Internet and mobile devices. However, acceptance of m-learning by individuals is critical to the successful implementation of m-learning systems. Thus, there is a need to research the factors that affect user intention to use m-learning. Based on the Unified Theory of Acceptance and Use of Technology (UTAUT) which integrates elements across eight models of IT use, the objective of this study was to investigate the determinants of m-learning acceptance and to discover if there exists either age or gender differences in the acceptance of m-learning, or both. Data collected from 330 respondents in Taiwan were tested against the research model using the structural equation modeling approach. The results indicate that that performance expectancy, effort expectancy, social influence, perceived playfulness, and self-management of learning were all significant determinants of behavioral intention to use m-learning. We also found that age differences moderate the effects of effort expectancy and social influence on m-learning use intention, and that gender differences moderate the effects of social influence and self-management of learning on m-learning use intention. These findings provide several important implications for m-learning acceptance, in terms of both research and practice.