Close links between students' conceptions of and approaches to learning were established in the past research. However, only a few quantitative studies investigated this relationship particularly with regard to mobile learning (m-learning). The correlation between learners' conceptions and approaches to m-learning was analysed using a partial least squares analysis applied to data obtained from a sample of 971 undergraduate students in China. The results indicated that students' conceptions of m-learning could be classified into reproductive, transitional, and constructive levels. Students may hold multiple m-learning applications than a predominant one; hence, examining m-learning as one monolithic entity may provide limited information. Latent profile analysis identified four learning profiles based on students' preferred m-learning applications: passive, mixed, surface-supportive, and high-engagement. Moreover, a general trend was observed, whereby students with reproductive and surface-supportive learning profiles showed a tendency to adopt surface approaches, whereas those expressing constructive and mixed learning profiles were more inclined to adopt deep approaches. Interestingly, students with transitional conceptions and high-engagement learning profiles tended to take both surface and deep approaches.
- approaches to m-learning
- conceptions of m-learning
- latent profile analysis
- mobile learning profiles
- partial least squares analysis
ASJC Scopus subject areas
- Computer Science Applications