ICT teachers’ adaptations to online instruction during Covid-19 pandemic

PurposeThe purpose of this study is to reveal both the adaptations of information computer technology (ICT) teachers teaching the information technologies and software (ITS) course online during the pandemic and the factors that affect this adaptation process. Teachers’ endeavours to conduct their courses online, the support they take during their endeavours, and their relationships with such basic components as the environment, content and students during this adaptation process will be revealed within the framework of unified theory of acceptance and use of technology (UTAUT).Design/methodology/approachIn this study, a sequential transformative mixed model was used in which firstly quantitative and then qualitative data were collected and analysed. The sample of this study consists of 307 ICT teachers employed and serving at public and private school in 2020–21. A proper sampling technique is used in the study. In this study, a sequential transformative mixed model was used in which firstly quantitative and then qualitative data were collected and analysed ( Creswell, 2009). The sample of this study consists of 307 ICT teachers employed and serving at public and private school in 2020–21. A proper sampling technique is used in the study.FindingsThe ICT teachers’ adaptations to the online courses have developed positively over the sub-dimensions of UTAUT, which are performance expectancy (PE), effort expectancy (EE), social influence (SE), facilitating conditions (FC) and behavioural intention (BI). The ICT teachers’ adaptations to the online instruction process have a significant effect on PE, FC and BI on the basis of gender, and on PE and EE on the basis of course content quality. In the process whereby the ICT teachers carry out the ITS course online, the sub-dimensions of PE, SE and FC are significantly predictive of the BI.Research limitations/implicationsUTAUT has been taken as a guiding framework in explaining and discussing the adaptations. Similarly, in other studies focussing on adaptation, this model could be employed in planning the research process. In addition, this study has followed a method in which qualitative data are mostly used to explain the quantitative data. Further studies may adopt a process whereby qualitative data are largely used to describe the way ITS course is conducted in online environments and this process may be used to develop a model.Practical implicationsExamining the students’ BIs in online courses overlaps with the sub-dimension of PE in this study, which stresses that PE, EE and motivation are significantly and directly effective on the students’ intentions of using the online courses, while there is a difference between these two studies in terms of the dimension of EE. The factors such learning outcome, curriculum, attendance to the course, use of materials and tools, interaction and technological substructure appear to be affected by this dimension, so they could be taken as important in that they reveal the importance of the study.Originality/valueThis study may provide clues for the online instruction practices that it reveals teachers’ adaptations to online learning environments at secondary schools. On the other hand, software, hardware, coding and robotics take place in the subjects like product designing, developing and programming that are within the content of ITS course for secondary schools. Even though there is a curriculum prepared for these subjects, a lot of different instruction techniques can be used for the teaching of these subjects. This can allow some inferences about the environments and methods suitable for the online instruction of the related subjects.