University students seem primed for mobile learning (m-learning) given their affinity with technology and the ubiquity of mobile computing devices on campuses. However such conditions do not necessarily guarantee their readiness for m-learning. For m-learning to thrive in higher education, it is crucial to understand the factors propelling its adoption. Accordingly this study uncovers factors that drive the adoption of m-learning among university students. Using a mobile learning readiness model based on the Theory of Planned Behavior, data was collected from 900 undergraduates in a local, public university in Malaysia. Partial least squares analysis revealed that all three constructs of attitude, subjective norm and perceived behavioral control significantly influenced students’ intention to adopt m-learning. These three constructs were significantly predetermined by their respective external beliefs components. In fostering m-learning adoption among students, more emphasis should be expended to capitalize on subjective norm and improve perceived behavioral control.
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Attitude towards M-Learning.
I would like my coursework more if I used m-learning (ATT1).
Using m-learning in my coursework would be a pleasant experience (ATT2).
Using m-learning in my coursework would be a wise idea (ATT3).
Intention to Adopt M-Learning.
I predict I would use a mobile device for my courses (INT1).
I plan to use a mobile device if a course has mobile learning functions (INT2).
I intend to adopt a mobile device for university courses (INT3).
I think instructors (i.e. lecturers, tutors) would approve of utilizing m-learning for their courses (IR1).
I think instructors (i.e. lecturers, tutors) would believe that a mobile device could be a useful educational tool in their courses (IR2).
I think instructors (i.e. lecturers, tutors) would have adequate technical skills to use a mobile device in their teaching (IR3).
I would be able to actively access coursework material with a mobile device (LA1).
I would have more opportunities to create knowledge in my coursework with a mobile device (LA2).
I would be able to control the pace (speed) of learning in my classes with a mobile device (LA3).
Perceived Behavioral Control.
I have sufficient extent of knowledge to use m-learning (PBC1).
I have sufficient extent of control to make a decision to adopt m-learning (PBC2).
I have sufficient extent of self-confidence to make a decision to adopt m-learning (PBC3).
Perceived Ease of Use.
I believe that mobile devices would be easy to use (PEU1).
I believe it would be easy to access course material with my mobile device (PEU2).
I believe that mobile devices would be easy to operate (PEU3).
I am confident about using a mobile device for my courses (PSE1).
Using a mobile device for my courses would not be a challenge for me (PSE2).
I would feel comfortable using a mobile device in my courses (PSE3).
I believe that using mobile devices would improve my ability to learn (PU1).
I believe that mobile devices would allow me to get my work done more quickly (PU2).
I believe that mobile devices would be useful for my learning (PU3).
Most people who are important to me think that it would be fine to use a mobile device for university courses (SN1).
I think other students in my classes would be willing to adopt a mobile device for learning (SN2).
Most people who are important to me would approve of using a mobile device for university courses (SN3).
I think other students would approve of utilizing m-learning in their coursework (SR1).
I think other students would believe that a mobile device could be a useful educational tool in their coursework (SR2).
I think other students would have adequate technical skills to use a mobile device in their coursework (SR3).
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Yeap, J.A.L., Ramayah, T. & Soto-Acosta, P. Factors propelling the adoption of m-learning among students in higher education. Electron Markets 26, 323–338 (2016). https://doi.org/10.1007/s12525-015-0214-x
- Mobile learning readiness
- Mobile learning acceptance
- Mobile devices
- Theory of planned behavior