University students’ use of mobile technology in self-directed language learning: using the integrative model of behavior prediction

Lai, Y.; Saab, N.; Admiraal, W.F.

doi:doi:10.1016/j.compedu.2021.104413

Mobile technology offers great potential for university students’ language learning. Numerous
studies have been conducted on utilizing mobile technology in language learning classroom.
However, using it in self-initiated and self-directed learning outside class remains to be explored.
The present study employed the integrative model of behavior prediction to investigate the re-
lationships between attitude, subjective norm, self-efficacy and behavioral intention, as well as
the association between intention, facilitating conditions, self-regulation skills and actual use of
mobile technology in self-directed language learning. This study also examined whether self-
regulation skills moderated intention and actual use. Survey data from 676 language learners
in different disciplines from Chinese universities were collected and analyzed using structural
equation modeling approach. The results showed that 37.1 percent of respondents indicated that
they...Show moreMobile technology offers great potential for university students’ language learning. Numerous
studies have been conducted on utilizing mobile technology in language learning classroom.
However, using it in self-initiated and self-directed learning outside class remains to be explored.
The present study employed the integrative model of behavior prediction to investigate the re-
lationships between attitude, subjective norm, self-efficacy and behavioral intention, as well as
the association between intention, facilitating conditions, self-regulation skills and actual use of
mobile technology in self-directed language learning. This study also examined whether self-
regulation skills moderated intention and actual use. Survey data from 676 language learners
in different disciplines from Chinese universities were collected and analyzed using structural
equation modeling approach. The results showed that 37.1 percent of respondents indicated that
they never used mobile technology for self-directed language learning. Of the other 425 re-
spondents who did indicate that they used mobile technology for this purpose, the majority of
them seemed to be extrinsically motivated. Learning activities regarding vocabulary acquisition
and translation were far more reported than those in terms of listening, speaking, reading and
writing. In addition, attitude and subjective norm significantly explained students’ intention to
use mobile technology, but self-efficacy did not have a direct effect on students’ intention.
Moreover, students’ self-regulation skills and intention significantly predicted students’ actual use
of mobile technology. Through moderation analysis, the results indicated that the relationship
between intention and actual behavior would be stronger with any increase in self-regulation
skills. These findings are discussed and implications are formulated.
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University students’ use of mobile technology in self-directed language learning: using the integrative model of behavior prediction