Web-based videoconferencing systems have become very popular means of online teaching during the educational shift from face-to-face to online due to the COVID-19 pandemic. Students around the world have been attending online classes through different web-based videoconferencing platforms instead of face-to-face lectures and seminars. The current study aims to investigate University students’ intentions to continue use web-based videoconferencing systems for their learning, when social distancing render unnecessary and Universities re-open after the pandemic is over. This study is part of our wider investigation on the impact of the COVID-19 pandemic on students’ experiences about different e-learning technologies and related pedagogies. The current study proposes a model based on the Technology Acceptance Model (TAM) and the Expectancy Confirmation Model (ECM) in order to explain and predict continuance intention to use videoconferencing systems in the post-COVID-19 era. Sixty-one students from a School of Education in a UK University completed an online survey. Structural equation modelling was used to analyze the data. The model explains and predicts 53% of the total variance in continuance intention to use videoconferencing systems for learning online in terms of perceived usefulness, social influence, satisfaction and confirmation. Satisfaction and perceived usefulness were found to be the most significant predictors of continuance intention to use. Implications for the use of web-based videoconferencing systems for online teaching and learning in the post-COVID 19 landscape are discussed.
© 2021 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting /republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Nikou, S. 2021, 'Web-based videoconferencing in online teaching during the COVID-19 pandemic: university students' perspectives', Proceedings - IEEE 21st International Conference on Advanced Learning Technologies, ICALT 2021, pp. 431-435. https://doi.org/10.1109/ICALT52272.2021.00137