Kolil Vysakh Kani, Achuthan Krishnashree
Center for Cybersecurity Systems and Networks, Amrita Vishwa Vidyapeetham, Amritapuri, Kollam, 690525 Kerala India.
Amrita School of Engineering, Amrita Vishwa Vidyapeetham, Amritapuri, Kollam, 690525 Kerala India.
Educ Inf Technol (Dordr). 2022 Dec 12:1-34. doi: 10.1007/s10639-022-11499-2.
Synthesizing the advancements in technology with classroom practices depends considerably on teachers acceptance of such internet and communication technology (ICT) tools. Adequate teacher training and upgrading of their IT skills are not prioritized in developing economies leading to poor adoption of emerging technology assisted pedagogic interventions. This paper investigated the underlying characteristics of teachers acceptance of mobile friendly virtual laboratories (M-VLs) as part of a longitudinal study conducted over 5 years covering both pre-pandemic and pandemic periods. Systematic analysis of quantitative data from 650 chemistry teachers was carried out. Viewing through the theoretical lens of Unified Theory of Acceptance and Use of Technology (UTAUT2) theory, the effects of performance expectancy (PE), effort expectancy (EE), social influence (SI), facilitating conditions (FC), hedonic motivation (HM) and habit (HA) on the behavioral intention (BI) and use behavior (UB) were scrutinized. Structural Equation Modeling (SEM) analysis revealed that PE, SI, and HA are the considerable predictors of the BI to use M-VLs and HA is the predictor of UB. The present study found HM influencing teacher's BI and UB before COVID-19. However during COVID-19 the FC influenced usage. Moreover, we found that the technology training focused on enhancing knowledge, skill and, access leads to teachers' are critical to empowering teachers and causing wider adoption.
将技术进步与课堂实践相结合在很大程度上取决于教师对诸如互联网和通信技术（ICT）工具的接受程度。在发展中经济体中，教师培训和信息技术技能提升未被列为优先事项，导致新兴技术辅助教学干预措施的采用率较低。本文作为一项为期5年的纵向研究的一部分，调查了教师接受移动友好型虚拟实验室（M-VL）的潜在特征，该研究涵盖了疫情前和疫情期间。对650名化学教师的定量数据进行了系统分析。从技术接受与使用统一理论（UTAUT2）的理论视角出发，审视了绩效期望（PE）、努力期望（EE）、社会影响（SI）、促进条件（FC）、享乐动机（HM）和习惯（HA）对行为意向（BI）和使用行为（UB）的影响。结构方程模型（SEM）分析表明，PE、SI和HA是使用M-VL的BI的重要预测因素，而HA是UB的预测因素。本研究发现，在新冠疫情之前，HM影响教师的BI和UB。然而，在新冠疫情期间，FC影响了使用情况。此外，我们发现专注于增强知识、技能和获取途径的技术培训对增强教师能力和促使更广泛采用至关重要。
