Abstract
A proliferation of literature documented the correlation between the teachers’ use of technology and the factors of technostress, burnout as well as the peda-gogical content knowledge. Yet insufficient findings explored the impacting factors of demographic factors of individual teachers and school support on educational use of technology. Hierarchical regression employed in this study advanced the traditional regression analysis of individual demographic factors, added by the second-step of school support model. The statistical results sup-ported both hypotheses that Model 1 of individual factors and Model 2 of the combined factors of individual and school support significantly predicted teachers’ use of technology. In addition, the study results showed that R square value progressed from 0.26 in model 1 to 0.60 in Model 2, implying the additional 34% of the variance explained by the combined factors collectively. The findings shed lights on in robustness of the models in predicting teachers’ in-tention to use technology and the school administrative policy in advocating the persistent use of ICT in educational settings.
Highlights
Introduction and Literature ReviewTeachers’ intention to use technology refers to the degree that individual teachers are willing to accept and adopt the technological tools in purely online or blended context of teaching [1, 2]
Insufficient findings explored the demographic variables of individual teachers and school support on educational use of iJET ‒ Vol 16, No 12, 2021
The dependent variable in the model referred to teachers' intention to use technology in educational settings
Summary
Teachers’ intention to use technology refers to the degree that individual teachers are willing to accept and adopt the technological tools in purely online or blended context of teaching [1, 2]. Insufficient findings explored the demographic variables of individual teachers and school support on educational use of iJET ‒ Vol 16, No 12, 2021. Very few prior studies attempted to employ hierarchical regression in analyzing both factors of individual and school support. Preliminary studies have proved that school infrastructure had major impacts on teaching, which included the resource allocations, information technology and network equipment and hardware [7, 8]. Previous study revealed that school policy promoted the technology use in educational settings [9]. The study revealed the significant correlation between school support and teachers' willingness to use technology
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