Dindar M, Suorsa A, Hermes J,Karppinen P, Näykki P. Comparing technology acceptance of K-12 teachers with and without prior experience of learning management systems: A Covid-19 pandemic study. J ComputAssist Learn. 2021;37:1553–1565.https://doi.org/10.1111/jcal.12552
Comparing technology acceptance of K-12 teachers with and without prior experience of learning management systems : a Covid-19 pandemic study
|Author:||Dindar, Muhterem1; Suorsa, Anna2; Hermes, Jan3,4;|
1Learning and Educational Technology Research Unit, Faculty of Education, University of Oulu, Oulu, Finland
2History, Culture and Communication Studies, Faculty of Humanities, University of Oulu, Oulu, Finland
3Department of Marketing, Management and International Studies, Oulu Business School, University of Oulu, Oulu, Finland
4Department of Organisational Behaviour and Marketing, Faculty of Economic Sciences and Management, Nicolaus Copernicus University, Toruń, Poland
5Oulu Advanced Research on Service and Information Systems, Faculty of Information Technology and Electrical Engineering, University of Oulu, Oulu, Finland
6Faculty of Education and Psychology, University of Jyväskylä, Jyväskylä, Finland
|Online Access:||PDF Full Text (PDF, 1.3 MB)|
|Persistent link:|| http://urn.fi/urn:nbn:fi-fe2022030722192
John Wiley & Sons,
|Publish Date:|| 2022-03-07
Covid-19 pandemic has caused a massive transformation in K-12 settings towards online education. It is important to explore the factors that facilitate online teaching technology adoption of teachers during the pandemic. The aim of this study was to compare Learning Management System (LMS) acceptance of Finnish K-12 teachers who have been using a specific LMS as part of their regular teaching before the Covid-19 pandemic (experienced group) and teachers who started using it for emergency remote teaching during the pandemic (inexperienced group). Based on the Unified Theory of Acceptance and Use of Technology framework, a self-report questionnaire was administered to 196 teachers (nexperienced = 127; ninexperienced = 69). Our findings showed no difference between the two groups of teachers in terms of performance expectancy, effort expectancy, LMS self-efficacy and satisfaction. However, the experienced group had higher behavioural intention to use LMS in the future, reported receiving higher online teaching support and displayed higher online teaching self-efficacy in terms of student engagement, classroom management, instructional strategies and ICT skills. For the experienced group, the most significant predictor of satisfaction with LMS was performance expectancy whereas for the inexperienced group, it was the effort expectancy. In terms of behavioural intention to use LMS in the future, the most significant predictor was the performance expectancy for both groups. Further, support was also a significant predictor of behavioural intention for the inexperienced group. Overall, our findings indicate that teachers should not be regarded as a unified profile when managing technology adoption in schools.
Journal of computer assisted learning
|Pages:||1553 - 1565|
|Type of Publication:||
A1 Journal article – refereed
|Field of Science:||
516 Educational sciences
This research is connected to the GenZ project, a strategic profiling project in human sciences at the University of Oulu. The project is supported by the Academy of Finland (project number: 318930) and the University of Oulu.
© 2021 The Authors. Journal of Computer Assisted Learning published by John Wiley & Sons Ltd. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.