An Implementation of the UTAUT Model for Understanding Students' Perceptions of Learning Management Systems

Alshehri, Ahmed; Rutter, Malcolm; Smith, Sally

doi:10.4018/ijdet.2019070101

Cited by 67 publications

(64 citation statements)

References 59 publications

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“…Our findings have shown that behaviour intention has had a significant positive effect on the actual use of virtual classrooms. This finding is consistent with most previous studies which produced similar results (Alshehri et al, 2019;Lewis et al, 2013;Šumak et al, 2010;Sultana, 2020;Vankatesh et al, 2003). The findings have implied that when teaching staff have an intention to use virtual classrooms for teaching, this intention will lead to the actual use of virtual classrooms.…”

Section: Results Of Hypothesis Testingsupporting

confidence: 94%

“…Venkatesh et al (2003) anticipated that if the relationships of PE and EE with BI exist, then FC becomes insignificant in predicating the behaviour intention toward the use of technology. The findings of this study were also consistent with certain previous studies where they found insignificant influence of FC on BI (Alshehri et al, 2019;Sultana, 2020). A possible explanation for these findings is that nowadays teaching staff can deal with and access technology from anywhere, at any time, without a need for FC, and they pay more attention toward the performance (usefulness of technology) and effort expectancy (ease of use of technology).…”

Section: Results Of Hypothesis Testingsupporting

confidence: 91%

“…Thus, it could be argued that EE is considered as a crucial predictor on the behaviour intention toward the use of virtual classrooms. It should also be noted that there are previous studies that contradict the current finding as they revealed there was no relationship between EE and BI (Alshehri et al, 2019;Chen, 2011;Šumak et al, 2010;Taiwo & Downe, 2013). Nonetheless, in a study of the original study by Venkatesh et al (2003) who developed the UTAUT model, the finding of this study confirmed the same result of the original Venkatesh et al (2003) study, which showed that that EE was a significant predictor of BI toward the usage of technology.…”

Section: Results Of Hypothesis Testingcontrasting

confidence: 85%

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

Alshammari

2021

JITE:Research

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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.

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Section: Results Of Hypothesis Testingsupporting

confidence: 94%

Section: Results Of Hypothesis Testingsupporting

confidence: 91%

Section: Results Of Hypothesis Testingcontrasting

confidence: 85%

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

Alshammari

2021

JITE:Research

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“…Many studies have shown that PE is a significant determinant of behavioural intention (BI) to use an e-learning system (Alrawashdeh et al, 2012;Alshehri et al, 2019a;Bellaaj et al, 2015;Bouznif, 2018;Salloum & Shaalan, 2019;Usoro et al, 2013). Similarly, in the Saudi higher education context, the studies of Alshehri et al (2019a) and Bellaaj et al (2015) found that performance expectancy has a remarkably positive impact on the students' intention to use an LMS. Thus, these findings suggest that the students are driven to accept the e-learning system primarily on the basis of its usefulness.…”

Section: Performance Expectancy (Pe)mentioning

confidence: 99%

“…Furthermore, recent studies have examined the use of e-learning systems in a Saudi higher institution and found that more than half of university students only use LMS either rarely or occasionally (Binyamin et al, 2016(Binyamin et al, , 2017. Prior studies disclosed that there is a dearth of academic research on Saudi higher education to examine the effects of usability factors on students use of LMSs, so significant issues have not yet been examined (Al-Asmari & Khan, 2014;Al-Harbi, 2011a;Alshammari et al, 2016;Alshehri et al, 2019a;Salloum & Shaalan, 2019;Yamani, 2014). Issues associated with system technical support, self-efficacy and instructional design, perceived accessibility, perceived flexibility, and subjective norm have been examined in the acceptance and use of LMSs (Al-Harbi, 2011a;Alshammari et al, 2016).…”

Section: Introductionmentioning

confidence: 99%

The Effects of UTAUT and Usability Qualities on Students’ Use of Learning Management Systems in Saudi Tertiary Education

Alshehri

Smith

2020

JITE:Research

Self Cite

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Aim/Purpose: This study proposes a theoretical framework that amalgamates Unified Theory of Acceptance and Use of Technology (UTAUT) variables with usability metrics to investigate the impact on students’ intention and use of the Learning Management System (LMS) in Saudi higher education. Background: There is a dearth of academic research on Saudi higher education to examine the effects of usability factors on students use of LMSs, so significant issues have not yet been examined. Methodology: Based on survey data from 605 respondents, the Partial Least Squares Structural Equation Modelling (PLS-SEM) technique was employed to assess the model. Contribution: The findings of the study may help colleges and universities to gain insights into the best way to promote e-learning system perceived usefulness and acceptance among students. Findings: The results confirmed that the UTAUT parameters are valid and robust in the context of LMS in Saudi Arabia. The dimension of social influence emerged to significantly influence the students’ intention and usage behaviour. The performance expectancy was affected by information quality and the system interactivity whereas the effort expectancy was influenced by system navigation, system learnability, and instructional assessment. The usability feature of interactivity was also demonstrated to influence students’ willingness to use the system. Recommendations for Practitioners: University policymakers are expected to benefit from this research for e-learning system acceptance in an academic setting and eliminate any impediments to its implementation. University students will be able to identify the factors and motivations driving their adoption of the system. In particular, usability, social, and organisational factors that affect their use of an e-learning system would be better understood. Recommendation for Researchers: The study should aid the research community in technology acceptance and usability studies to determine the students’ perceptions and experiences towards e-learning usability, social, and organisational factors that influence their acceptance, specifically in a Saudi context where students have unique psychological and social characteristics. Administrators and designers could also better understand areas of improvement for usability issues and develop design solutions based on the findings of this study. Impact on Society: The suggestions have been offered in order to accelerate and increase the use of e-learning services in Saudi higher education. System designers and administrators should have a better insight into the user interface design, considering system-independent metrics that could enhance user acceptance of e-learning systems. Future Research: The study focused on the students’ perspective, a natural progression of this work is to involve other e-learning stakeholders (teachers and administrators). This could enrich the research by providing a better understanding of undisclosed issues, offering different views about the implementation and use of an e-learning system in Saudi Arabia.

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Consumer adoption of on‐demand digital platforms: An integrated model

Lim

Leong

et al. 2023

Glob Bus Org Exc

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On‐demand digital platforms are omnipresent in the contemporary marketplace of the digital era. The purpose of this study was to assess the factors influencing consumers’ intention to adopt on‐demand digital platforms in the context of a developing country. Based on a modified integration of the unified theory of acceptance and use of technology (UTAUT) and the social influence theory, this study contended that electronic word‐of‐mouth (eWOM) about on‐demand digital platforms shapes consumers' perceived risk and subjective norms, which, along with the other elements of UTAUT, influence their intention to use on‐demand digital platforms. A self‐administered questionnaire was developed and distributed online, yielding a total of 226 responses, which were analyzed using partial least squares structural equation modelling. The findings revealed that performance expectancy, effort expectancy, subjective norms, and perceived risk significantly affect consumers’ intention, wherein eWOM reduces perceived risk and shapes subjective norms to adopt on‐demand digital platforms. Therefore, this study contributes to the literature on consumer adoption of new‐age digital products, and in this case, on‐demand digital platforms, with implications for theory and practice in this space.

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An Implementation of the UTAUT Model for Understanding Students' Perceptions of Learning Management Systems

Cited by 67 publications

References 59 publications

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

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

The Effects of UTAUT and Usability Qualities on Students’ Use of Learning Management Systems in Saudi Tertiary Education

Consumer adoption of on‐demand digital platforms: An integrated model

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