TY - JOUR
T1 - Chinese undergraduate students' perceptions of mobile learning: Conceptions, learning profiles, and approaches
AU - Lin, Xiao-Fan
AU - Deng, Cailing
AU - Hu, Qintai
AU - Tsai, Chin-Chung
N1 - https://doi.org/10.1111/jcal.12333
PY - 2019
Y1 - 2019
N2 - 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.
AB - 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.
KW - approaches to m-learning
KW - conceptions of m-learning
KW - latent profile analysis
KW - mobile learning profiles
KW - partial least squares analysis
U2 - 10.1111/jcal.12333
DO - 10.1111/jcal.12333
M3 - Article
SN - 0266-4909
VL - 35
SP - 317
EP - 333
JO - Journal of Computer Assisted Learning
JF - Journal of Computer Assisted Learning
IS - 3
ER -