Abstract:
Research on technology adoption often profiles device usability (such as
perceived usefulness) and user dispositions (such as perceived ease of use) as the
prime determinants of effective technology adoption. Since any process of technology
adoption cannot be conceived out of its situated contexts, this paper argues
that any pre-occupation with technology acceptance from the perspective of device
usability and user dispositions potentially negates enabling contexts that make
successful adoption a reality. Contributing to contemporary debates on technology
adoption, this study presents flexible mobile learning contexts comprising cost
(device cost and communication cost), device capabilities (portability, collaborative
capabilities), and learner traits (learner control) as antecedents that enable the
sustainable uptake of emerging technologies. To explore the acceptance and
capacity of mobile instant messaging systems to improve student performance, the
study draws on these antecedents, develops a factor model and empirically tests it
on tertiary students at a South African University of Technology. The study
involved 223 national diploma and bachelor’s degree students and employed partial
least squares for statistical analysis. Overall, the proposed model displayed a good
fit with the data and rendered satisfactory explanatory power for students’ acceptance
of mobile learning. Findings suggest that device portability, communication
cost, collaborative capabilities of device and learner control are the main drivers of
flexible learning in mobile environments. Flexible learning context facilitated by learner control was found to have a positive influence on attitude towards mobile
learning and exhibited the highest path coefficient of the overall model. The study
implication is that educators need to create varied learning opportunities that
leverage learner control of learning in mobile learning systems to enhance flexible
mobile learning. The study also confirmed the statistical significance of the original
Technology Acceptance Model constructs.
