Video-based learning (VBL) is gaining increased attention as an educational means in settings such as the flipped classroom and massive open online courses. The value of VBL has been recognized in a range of contexts due to the ability to extend opportunities for life-long education for all socio-economic levels, removing geographical boundaries while at the same time alleviating time constraints. Yet, despite the advantages featured by VBL and some promising early outcomes regarding its effectiveness, little is known about what influences individuals to adopt VBL systems and technologies. The paper aims to discuss this issue.
Building on behavioral and adoption-acceptance theories as well as on past empirical studies on e-learning, a conceptual model of VBL adoption is proposed. By analyzing survey data from 260 VBL learners, the conceptual model is put to test by means of structural equation modeling.
Outcomes indicate that performance expectancy (PE) and computer self-efficacy (CSEF) have a positive direct effect on behavioral intention to adopt VBL. In addition, effort expectancy (EE) and social influence positively impact PE, while CSEF is found to enhance EE and perceived behavioral control.
This study integrates several theoretical perspectives that are applied to adoption of novel information technologies and in addition builds on findings of past empirical research on learning technologies. In effect, the conceptual model along with outcomes provide an integrative perspective of adoption determinants.
This project has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No. 704110. This work was carried out during the tenure of an ERCIM “Alain Bensoussan” Fellowship Programme. Our thanks to thank the Norwegian Research Council for its financial support under the projects FUTURE LEARNING (number: 255129/H20).
Mikalef, P., Pappas, I.O. and Giannakos, M. (2016), "An integrative adoption model of video-based learning", International Journal of Information and Learning Technology, Vol. 33 No. 4, pp. 219-235. https://doi.org/10.1108/IJILT-01-2016-0007
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