Investigating the determinants and age and gender differences in the acceptance of mobile learning
Bibliographic Data
| ID | 23371997 |
|---|---|
| Authors | Yi‐Shun Wang (0000-0002-0161-5520, corresponding author), Ming‐Cheng Wu (0000-0003-1837-6826), Hsiu‐Yuan Wang (National Changhua University of Education) |
| Year | 2009 |
| Volume | 40 |
| Issue | 1 |
| Pages | 92-118 |
| Publication date | 2009-01-01 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | British Journal of Educational Technology (JOURNAL) |
| Journal identifiers | ISSN: 0007-1013 • E-ISSN: 1467-8535 |
| Publisher | Wiley (PUBLISHER • GB) |
| DOI | 10.1111/j.1467-8535.2007.00809.x |
| OpenAlex | W2157446202 |
| Language | EN |
| Citations received | 79 |
| References cited | 59 |
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.
Educational technology · Expectancy theory · Human–computer interaction · Knowledge management · Learning Management · Machine learning · Mathematics education · Pedagogy · Social influence · Social learning · Structural equation modeling · Technology Acceptance Model · The Internet · Unified theory of acceptance and use of technology · Usability · World Wide Web · Computer Science · Digital Marketing and Social Media · Impact of Technology on Adolescents · Psychology · Social Psychology · Technology Adoption and User Behaviour
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Withdrawn
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| Unique citing works | 79 |
|---|---|
| Citations per year | 4,65 |
| Citation span | 2009 - 2026 (18) |
| Citation velocity | current |
| Highly cited | No |
| Citation types | Neutral: 68 |