Abstract
This study explored the factors that affect the intention of users to continue using mobile learning (m-learning) applications (apps). The influence of habit on user behavior toward information systems has been extensively discussed in the literature, but its role in the continuance of users when it comes to their usage of apps, especially m-learning apps, has rarely been reported. To obtain a comprehensive understanding of behaviors regarding the use of m-learning apps, this study constructed a theoretical research framework based on expectation confirmation theory and flow theory by considering habit as a moderating variable. Online questionnaires were administered to users of m-learning apps in Taiwan and data were analyzed through a structural equation modeling approach. The results indicated that the intention of users to continue using m-learning apps was influenced by satisfaction, perceived usefulness, and flow experience. Expectation confirmation affected user satisfaction and perceived usefulness. Differences existed in the intention to continue usage between users with strong and weak habits. In addition, perceived usefulness, expectation confirmation, and flow experience had direct and positive effects on satisfaction. The implications of these findings were discussed.
Highlights
The emergence of communication technology and mobile devices has contributed to rapid developments in mobile applications
Reliability was determined using Cronbach’s alpha and the composite reliability (CR) model to assess the internal consistency of the measurement model
This study explored the intention to continue using m-learning apps by using an integrated research model based on ECT, flow theory, and habit
Summary
The emergence of communication technology and mobile devices has contributed to rapid developments in mobile applications (apps). Advances in network communication and mobile technology have considerably changed the lives and learning methods of people (Nikou and Economides, 2017; Chao, 2019; Liu et al, 2021). Because of the portability of mobile devices such as smartphones and tablets, their usage by learners has increased considerably. A growing number of mobile learning (m-learning) apps have been developed (Chao, 2019; Alshurideh et al, 2020). Unlike computer-aided learning, m-learning allows users to learn without time and space limitations, which increases their learning intention and learning effectiveness (Chao, 2019; Quesada-Pallares et al, 2019; Wang et al, 2019; Liu et al, 2021)
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