Factors Influencing the Adoption of E-Learning by University Students in Sri Lanka: Application of UTAUT-3 Model during Covid-19 Pandemic

Abstract

Universities around the world are entering 'emergency mode' during the COVID-19 pandemic, radically transforming education by switching towards online learning and other distance-based education methods. An unintended consequence of these emerging changes is that many students who are either not willing to use e-learning or have no adequate skills to learn through electronic devices or have no resources to access them are marginalized. Considering the timeliness and the relevance of the phenomenon, this study aims to identify the factors influencing the adoption of e-learning by Sri Lankan university students. The relevant data were collected through a self-administered questionnaire which was distributed among 191 university students based on the convenience sampling method. This study found out positive impacts of performance expectancy, facilitating conditions, habit, price-value, and personal innovativeness in IT on to use elearning. Moreover, the intention has a positive impact on the adoption of elearning platforms. This research fills the gap in the existing literature and provides valuable insights to the course administrators in universities in Sri Lanka to better manage e-learning systems.

Wearable Technologies Acceptance and Adoption by Elderly People in Masaka Uganda

“…This means that elderly people agreed to adopt to the wearable technology if they find that their friends are using it, so that they can also be recognized by others. People take image to be a crucial matter, therefore, they can easily adopt technology innovations, due to social influence because they want to uplift their status in their social groups (Kamalasena & Sirisena, 2021).…”

“…All the above mentioned influences can significantly influence end users acceptance and use of technology (Gonzalez-Garcia, Maltoni, Salvado, & Schwetz, 2012). The pressure from higher authorities can significantly shape an individual's behavior to accept the technology (Kamalasena, 2021). From this point of view, if for instance health workers adopt to technology, they are likely to influence the elderly people to adopt to the new technology if it happens to be effective.…”

“…The elderly compared the transport they inject in to reach the hospital in relation to the benefit of technology which will eliminate the unnecessary movement, and they concluded that they are willing to use technology if it is cost friendly. So when the advantage of using technology outweigh the initial cost of technology, then there is a likelihood that people's intention to use technology will be positive (Kamalasena, 2021). It is therefore believed that elderly people will adopt the wearable technology if they find out that it's cheaper to use technology, than visiting of the hospital regularly.…”

Factors affecting learners’ perception of e-learning during the COVID-19 pandemic

“…The first three are direct influences of usage intention, and the fourth is a direct determining factor of user behavior (Tan, 2013;Ain et al, 2016;Zuiderwijk et al, 2015). It can be seen that many researchers have investigated the UTAUT model in the context of intention to use e-learning (Kamalasena and Sirisena, 2021;Abbad, 2021;Jameel et al, 2021). As the present research is focused on usage intention, the aforementioned three factors of usage intention (PE, EE and SI) would assist to provide insights into the factors that may influence the adoption of e-learning during the Covid-19 pandemic.…”

“…, 2015). It can be seen that many researchers have investigated the UTAUT model in the context of intention to use e-learning (Kamalasena and Sirisena, 2021; Abbad, 2021; Jameel et al. , 2021).…”