What Drives College Teachers’ Behavioral Intention to Teach Online? A Structural Equation Modelling Approach

Tianjiao Chen, Gege Li, Qinna Feng, Jie Liu, Peiyu Wang, Heng Luo
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引用次数: 4

Abstract

Using technology acceptance model (TAM) as a theoretical framework, the study explored the potential factors that influence college teachers’ behavioral intention to teach online based on the results of a national survey (N=1090) administered during the Covid-19 pandemic. A structural equation modelling (SEM) was proposed by introducing new constructs such as subjective norm, facilitating conditions, affective and cognitive attitude into the TAM model. Meanwhile, the individual differences of college teachers were examined as moderating variables. The results suggested that cognitive attitude had much large impact on teachers’ behavioral intention to teach online, and perceived use- fulness of online learning platforms had greater influence on teachers’ online teaching attitude than perceived ease of use, particularly on cognitive attitude. Additionally, the moderating effect of teachers’ individual differences were also found to be insignificant. The study results supported the revised TAM as a theoretical model to understand college teachers’ online teaching behavioral intention, and can inform the policies to sustain teachers’ motivation for continual online teaching practice during the post-pandemic world.
大学教师在线教学行为意向的动因?结构方程建模方法
本研究以技术接受模型(TAM)为理论框架,基于新冠肺炎大流行期间进行的一项全国调查(N=1090)的结果,探讨了影响大学教师在线教学行为意愿的潜在因素。通过在TAM模型中引入主观规范、促进条件、情感态度和认知态度等新构式,提出了一种结构方程模型。同时,对高校教师的个体差异作为调节变量进行了检验。结果表明,认知态度对教师网络教学行为意向的影响较大,感知网络学习平台的可用性对教师网络教学态度的影响大于感知易用性,尤其是对认知态度的影响。此外,教师个体差异的调节作用也不显著。研究结果支持修订后的TAM作为理解大学教师在线教学行为意愿的理论模型,并为在疫情后世界维持教师持续在线教学实践动机的政策提供信息。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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