Factors Determining the Behavioral Intention to Use Mobile Learning: An Application and Extension of the UTAUT Model

• Published in: Frontiers in psychology Vol. 10; p. 1652
• Main Author: Chao, Cheng-Min
• Format: Journal Article
• Language: English
• Published: Switzerland Frontiers Media S.A 16-07-2019
• Subjects: mobile learning; mobile self-efficacy; perceived enjoyment; perceived risk; Psychology; trust; unified theory of acceptance and use of technology model; trust; perceived risk; mobile self-efficacy; unified theory of acceptance and use of technology model; perceived enjoyment; mobile learning
• ISSN: 1664-1078; 1664-1078
• DOI: 10.3389/fpsyg.2019.01652

This study developed and empirically tested a model to predict the factors affecting students' behavioral intentions toward using mobile learning (m-learning). This study explored the behavioral intention to use m-learning from the perspective of consumers by applying the extended unified theory of acceptance and use of technology (UTAUT) model with the addition of perceived enjoyment, mobile self-efficacy, satisfaction, trust, and perceived risk moderators. A cross-sectional study was conducted by employing a research model based on multiple technology acceptance theories. Data were derived from an online survey with 1,562 respondents and analyzed using structural equation modeling. Partial least squares (PLS) regression was used for model and hypothesis testing. The results revealed that (1) behavioral intention was significantly and positively influenced by satisfaction, trust, performance expectancy, and effort expectancy; (2) perceived enjoyment, performance expectancy, and effort expectancy had positive associations with behavioral intention; (3) mobile self-efficacy had a significantly positive effect on perceived enjoyment; and (4) perceived risk had a significantly negative moderating effect on the relationship between performance expectancy and behavioral intention. Our findings correspond with the UTAUT model and provide a practical reference for educational institutions and decision-makers involved in designing m-learning for implementation in universities.