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Investigating the determinants and age and gender differences in the acceptance of mobile learning
Author(s) -
Wang YiShun,
Wu MingCheng,
Wang HsiuYuan
Publication year - 2009
Publication title -
british journal of educational technology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.79
H-Index - 95
eISSN - 1467-8535
pISSN - 0007-1013
DOI - 10.1111/j.1467-8535.2007.00809.x
Subject(s) - expectancy theory , unified theory of acceptance and use of technology , psychology , educational technology , social influence , social learning , technology acceptance model , learning management , structural equation modeling , the internet , knowledge management , social psychology , computer science , mathematics education , usability , world wide web , pedagogy , machine learning , human–computer interaction
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 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 information technology use, this study was to investigate the determinants of m‐learning acceptance and to discover if there exist 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 modelling approach. The results indicate that performance expectancy, effort expectancy, social influence, perceived playfulness, and self‐management of learning were all significant determinants of behavioural 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.