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Asia-Pacific Social Science Review

Abstract

The unexpected community quarantine period in the Philippines due to the COVID-19 pandemic has brought about a total switch from traditional classroom teaching to online teaching. The unprecedented challenges of whether teachers were prepared enough in terms of materials and their capability in delivering their lessons from traditional to online teaching prompted the researchers to conduct this study. Thus, this study attempted to investigate the robustness of UTAUT constructs and an aspect of IDT and explore the integration of trialability and compatibility to find out the preparedness of the teachers in using Canvas features during their lockdown days. Empirical data were collected through online surveys among university faculty (N=786) that used Canvas online features. Modeling and structuring approaches, such as a statistical tool called SmartPLS 3, were used. Results indicated that all the eight hypotheses tested, integrating trialability and compatibility with UTAUT constructs, were supported at p <0.000. Most particularly, the findings revealed the following: (a) Trialability of Canvas usage affects effort expectancy of users; (b) Social influence is directly related to facilitating conditions; (c) Compatibility on Canvas usage is directly related to facilitating conditions to use; (d) Effort expectancy influences usage of Canvas features; (e) Facilitating conditions affect the usage of Canvas features directly; (f) Performance expectancy is directly related to the usage of Canvas features; (g) Compatibility has a direct effect on performance expectancy; and (h) Trialability is directly related to compatibility in using the technology. Thus, the actual usage and acceptance of Canvas had been justified, giving evidence that the faculty were ready for online teaching during the quarantine period. It was recommended that educators continue with the online learning mode that meets learners’ needs. The models used in the study may be tried by future researchers using the same Canvas features.

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