Determining the Factors that Affect the Use of Virtual Classrooms: A Modification of the UTAUT Model

Abstract

Aim/Purpose: The aim of this study was to examine the factors that may influence the use of virtual classrooms. Background: The coronavirus (COVID-19) pandemic has affected and interrupted several aspects of our lives, including education. Most educational institutes and universities have changed their teaching mode from being face-to-face or fixable learning to ‘emergency remote education’. As a result, virtual classrooms were utilised in most of these universities to keep the continuity of teaching and delivering education to their students Methodology: Through an online survey, data was collected from 235 of the teaching staff at the University of Ha’il, Saudi Arabia. Structural equation modelling (SEM) using AMOS was applied to analyse the data and testing the hypothesis of the proposed model. Contribution: The study findings have a theoretical, methodological, and practical contribution in the area of virtual classrooms. In terms of its theoretical contribution, this research has enriched the literature on virtual classrooms. Most of previous studies used the basic UTAUT model or other models for different technology, such as LMS, Mobile Cloud Learning and social websites. Few studies have focused on virtual classrooms, and, based on the best knowledge of the researcher, this study is the first study that has extended and modified the UTAUT model by adding an external factor (mobility) with virtual classrooms technology. Thus, it contributes theoretically to IS acceptance literature in general, and to UTAUT models specifically. In terms of methodological contribution, this study assessed all latent constructs in the model in a different context (Saudi Arabia), and tested them through an advanced analysis technique, which some call a second-generation multivariate, by applying a two-step rule in AMOS (CFA and SEM). The CFA has shown solid results that can measure all constructs in the model after deleting a few items that show a low factor loading to the construct. According to Awang (2015), examining the construct, convergent and discriminant validities is essential during the CFA before moving on a step and analysing data using SEM. Thus, this study has validated all constructs and its items using CFA which can be further used in a different culture, specifically in an Arab culture, such as Saudi Arabia. Findings: The results showed that effort expectancy and performance expectancy are significant predictors of behaviour intention toward the use of virtual classrooms. However, in contrast of our expectation, social influence, facilitating condition and mobility were insignificant factors and had no influence on teaching staff’s behaviour intention toward the use of virtual classrooms. Recommendations for Practitioners: This research has made a practical contribution. The findings of this study showed which factors can determine the use of virtual classrooms. Decision makers and university organizations and administration can improve their virtual classrooms services based on the factors that determine their use. Taking care of that will lead to an increased use of virtual classrooms and lead to a successful use of virtual classrooms, which will result in huge benefits in applying virtual classrooms in the teaching process. Recommendation for Researchers: Researchers may develop different models and examine other factors to assess their influence on the usage of different technologies. Understanding the factors that may influence the usage of a technology leads to an increase in its usage and adoption. Impact on Society: This study may increase the usage of virtual classrooms among teaching staff by understanding and examining the factors that might determine the use of virtual classrooms. Future Research: Future studies could examine the moderation variables to establish their impact. This study relied on only a purely quantitative design study. Future research might employ a mixed method using both quantitative and qualitative designs to apply an interview after the quantitative study for a better insight and deeper knowledge as well as confirming the quantitative results.

Acceptance of the learning management system in the time of COVID-19 pandemic: An application and extension of the unified theory of acceptance and use of technology model

“…For SI, this study supports previous studies by ( Raman et al, 2014 ; Hsu, 2012 ; Alshehri et al, 2019 ), as they also found SI significant for LMSs uses and contradicts studies by ( Sultana, 2020 ; Alshammari, 2021 ; Zwain, 2019 ; Bouznif, 2018 ). The contradicts in the results indicate that the social impact differs from one context to another.…”

“…( Venkatesh et al, 2003 ) argued and confirmed that BI has a significant influence on the actual use of technology. Furthermore, previous studies have found a positive effect of BI on the actual use of technology ( Al-Adwan et al, 2018 ; Abu-Al-Aish and Love, 2013 ; Alshammari, 2021 ). Regarding LMS ( Hsu, 2012 ; Raza et al, 2021 ; Zwain, 2019 ; Alshehri et al, 2019 ; Sultana, 2020 ), they have found a positive effect of BI on the actual use of LMS.…”

“…PE implicitly denotes that learning and retrieving necessary information through LMSs occur anytime and anywhere, effectively and efficiently. Many studies have shown that PE is a significant determinant of BI when using an LMS ( Sultana, 2020 ; Alshammari, 2021 ; Alshehri et al, 2019 ; Raza et al., 2021 ; Hsu, 2012 ; Raman et al., 2014 ). As a result, this study hypothesizes, based on UTAUT: H1: PE significantly affects students’ BI to use an LMS.…”

An Extended Unified Theory of Acceptance and Use of Technology Model for Education Contexts

“…One variable that has been cited consistently as a possible impediment to the efficacy of such initiatives is that of end-user acceptance. For instance, user acceptance studies on online meeting platforms like Zoom and Microsoft has been on the rise (Alfadda & Mahdi, 2021;Alshammari, 2021;Bui et al, 2020;Mpungose, 2021;Olugbade & Olurinola, 2021;Pal & Vanijja, 2020).…”

Examining Gender Differences in Student Learning During the COVID-19 Pandemic: A Model from the Switching Costs and Quality-Related Perspectives

“…Chen & Roldan, 2021;Dunaway & Kumi, 2021;Johnson et al, 2020;Prentice et al, 2020). A few studies have been seen to develop research models to investigate student learning, but most of them applied existing models related to information systems acceptance and adoption (Alshammari, 2021;Rizun & Strzelecki, 2020;Shahzad et al, 2021;Tiwari, 2020). To the best of the authors' knowledge, the current study is the first to leverage the theoretical lenses of both switching costs and various types of qualities to assess student learning in this new context, and further examine gender differences based on it.…”