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Journal ArticleDOI

Factors affecting students' intentions to undertake online learning: an empirical study in Vietnam.

04 Mar 2021-Education and Information Technologies (Springer US)-Vol. 26, Iss: 6, pp 1-21
TL;DR: In this paper, a study was conducted with 145 respondents and Structural Equation Model (SEM) was used for data analysis to understand what factors have an impact on students' intentions to study online.
Abstract: Educational institutions worldwide had to shift the teaching delivery mode from face to face to online teaching during COVID-19. Most of the universities in Vietnam were based on face to face learning until the sudden outbreak of COVID-19. This research study was conducted with 145 respondents and Structural Equation Model (SEM) was used for data analysis. The participants were undergraduate and post-graduate students in public and private universities who studied online during the pandemic in Vietnam. The purpose of this study was to understand what factors have an impact on students' intentions to study online. The results show that institutional support and perceived enjoyment (satisfaction) affects the students' intentions to study the course online in the future. Perceived enjoyment (PE) affects the online learning intentions (OLI) and PE is affected by ICT infrastructure and internet speed and access. Hence, this research adds new research variable defined as extrinsic factors (ICT infrastructure and access to the internet), which indirectly influences students' intentions to learn online. Given the increased use of smart phones with this generation, it is advisable to integrate mobile technology in online learning and QR codes can be one of the ways to integrate that in the course materials. It is further recommended that to increase the perceived enjoyment of the students with the online learning, the lecturers might be encouraged to use videos, audios and instant messaging to contact and provide the feedback to the students. It is important for universities to prepare for any such future crisis. This study results will provide a useful insight to design the online courses effectively by considering all the factors impacting students' intention and satisfaction.

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Citations
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Journal ArticleDOI
TL;DR: In this article, the authors examined the role of Information & Communication Technology (ICT), motivational variables, and virtual competence towards students' e-learning effectiveness, and found that perceived usefulness, perceived enjoyment, virtual self-efficacy and virtual social skills positively contribute towards elearning effectiveness of students which contribute to their knowledge acquisition and satisfaction.
Abstract: Current study is undertaken to examine the role of Information & Communication Technology (ICT), motivational variables, and virtual competence towards students' e-learning effectiveness. Structural Equation Modelling (SEM) with Partial Least Squares (PLS) was used for data analysis. Findings revealed that different components of ICT, except perception, have a positive impact on e-learning effectiveness. Also, perceived usefulness, perceived enjoyment, virtual self-efficacy, and virtual social skills positively contribute towards e-learning effectiveness of students which contribute to their knowledge acquisition and satisfaction. Findings of the study have unique implications for universities, faculty and students to create/use e-platforms for effective learning experiences.

20 citations

Journal ArticleDOI
TL;DR: In this paper, the authors reviewed the most common technologies used in the delivery of learning materials, with the experience of most infected countries being considered, and considered major challenges in online learning are discussed in this study.

13 citations

Journal ArticleDOI
TL;DR: In this paper , the authors investigate the perceptions of users about using digital detox applications and to display relationships among personality traits and technology-related variables, and find that behavioral intention predicted usage behavior significantly; performance expectancy, effort expectancy, and social influence positively affected behavioral intention; in turn, agreeableness and extroversion positively influenced performance expectancy and extrosversion affected effort expectancy; neuroticism had a statistically significant and negatively associated with effort expectancy of using social media detox apps.
Abstract: The purpose of this study was to investigate the perceptions of users about using digital detox applications and to display relationships among personality traits and technology-related variables. This study was designed using survey approach and employed Generalized Structured Component Analysis (GSCA). As such, 11 hypotheses were constructed and tested. The study recruited 263 participants who utilize detox applications to avoid social media distractions. Data were collected through Google Form and analyzed using GSCA Pro 1.1 to better understand whether the proposed conceptual model fits the data. The results of the study indicated that behavioral intention predicted usage behavior significantly; performance expectancy, effort expectancy, and social influence positively affected behavioral intention; in turn, agreeableness and extroversion positively influenced performance expectancy, and extroversion affected effort expectancy; finally, neuroticism had a statistically significant and negatively associated with effort expectancy of using social media detox apps. The significant exceptions were that facilitating conditions were not predictive of behavioral intention, openness to experience did not influence performance expectancy, and conscientiousness was not linked to effort expectancy. The proposed conceptual model explained 56.68% of the amount of variation, indicating that instructors, policy makers and software designers should consider personal factors for preparing practical intervention approaches to mitigate learning issues related to social media distraction.

12 citations

Journal ArticleDOI
12 May 2021
TL;DR: In this paper, the authors explore the post-acceptance of e-learning platforms based on a conceptual model that has various variables, such as perceived ease of use and usefulness, perceived daily routine, perceived critical mass and perceived self-efficiency.
Abstract: The fear of vaccines has led to population rejection due to various reasons. Students have had their own inquiries towards the effectiveness of the vaccination, which leads to vaccination hesitancy. Vaccination hesitancy can affect students’ perception, hence, acceptance of e-learning platforms. Therefore, this research attempts to explore the post-acceptance of e-learning platforms based on a conceptual model that has various variables. Each variable contributes differently to the post-acceptance of the e-learning platform. The research investigates the moderating role of vaccination fear on the post-acceptance of e-learning platforms among students. Thus, the study aims at exploring students’ perceptions about their post-acceptance of e-learning platforms where vaccination fear functions as a moderator. The current study depends on an online questionnaire that is composed of 29 items. The total number of respondents is 630. The collected data was implemented to test the study model and the proposed constructs and hypotheses depending on the Smart PLS Software. Fear of vaccination has a significant impact on the acceptance of e-learning platforms, and it is a strong mediator in the conceptual model. The findings indicate a positive effect of the fear of vaccination as a mediator in the variables: perceived ease of use and usefulness, perceived daily routine, perceived critical mass and perceived self-efficiency. The implication gives a deep insight to take effective steps in reducing the level of fear of vaccination, supporting the vaccination confidence among educators, teachers and students who will, in turn, affect the society as a whole.

12 citations

Journal ArticleDOI
TL;DR: In this article , the authors focused on the uses of digital technology during teaching and learning and inquired the preparedness, adoption, and use of virtual learning in higher and tertiary institutions.
Abstract: This study focuses on the uses of digital technology during teaching and learning. The preparedness, adoption, and use of virtual learning are inquired. Technology cannot enhance learning unless adopted, embraced, and effectively used. Three hundred and one (301) online questionnaires were administered to Higher and Tertiary institutions (HTEIs) students. The data were analyzed using the Structural Equation Model (SEM). Performance Expectancy (PE), Effort Expectancy (EE), and Social Influence (SI) were confirmed to be positive predictors of the Behavioural Intention (BI) to use technology. Facilitating Conditions (FC) is a non-significant construct to BI to use technology. Thus, irrespective of the availability of Information Communication Technologies (ICT) infrastructure and support needed to use virtual learning, students are forced to use virtual technology due to COVID-19. Pandemics such as COVID-19 force students and lecturers to use virtual learning irrespective of factors surrounding them. Pandemics are an anchor for the full embracement of virtual learning. Pandemic ‘like’ elements applied in the education system foster education. Google Classroom and its features prove to improve the teaching and learning processes. Chatbots and contextualized virtual Educational Humanoid robots enhance learning through interactivity. Pandemics need to be tested if they are a perfect fit as a new Unified Theory of Acceptance and Use of Technology (UTAUT) model construct. In addition, a model for effective blended learning during and post COVID-19 must be developed.

10 citations

References
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Journal ArticleDOI
TL;DR: In this article, the adequacy of the conventional cutoff criteria and several new alternatives for various fit indexes used to evaluate model fit in practice were examined, and the results suggest that, for the ML method, a cutoff value close to.95 for TLI, BL89, CFI, RNI, and G...
Abstract: This article examines the adequacy of the “rules of thumb” conventional cutoff criteria and several new alternatives for various fit indexes used to evaluate model fit in practice. Using a 2‐index presentation strategy, which includes using the maximum likelihood (ML)‐based standardized root mean squared residual (SRMR) and supplementing it with either Tucker‐Lewis Index (TLI), Bollen's (1989) Fit Index (BL89), Relative Noncentrality Index (RNI), Comparative Fit Index (CFI), Gamma Hat, McDonald's Centrality Index (Mc), or root mean squared error of approximation (RMSEA), various combinations of cutoff values from selected ranges of cutoff criteria for the ML‐based SRMR and a given supplemental fit index were used to calculate rejection rates for various types of true‐population and misspecified models; that is, models with misspecified factor covariance(s) and models with misspecified factor loading(s). The results suggest that, for the ML method, a cutoff value close to .95 for TLI, BL89, CFI, RNI, and G...

76,383 citations

Journal ArticleDOI
TL;DR: In this article, the authors developed and validated new scales for two specific variables, perceived usefulness and perceived ease of use, which are hypothesized to be fundamental determinants of user acceptance.
Abstract: Valid measurement scales for predicting user acceptance of computers are in short supply. Most subjective measures used in practice are unvalidated, and their relationship to system usage is unknown. The present research develops and validates new scales for two specific variables, perceived usefulness and perceived ease of use, which are hypothesized to be fundamental determinants of user acceptance. Definitions of these two variables were used to develop scale items that were pretested for content validity and then tested for reliability and construct validity in two studies involving a total of 152 users and four application programs. The measures were refined and streamlined, resulting in two six-item scales with reliabilities of .98 for usefulness and .94 for ease of use. The scales exhibited hgih convergent, discriminant, and factorial validity. Perceived usefulness was significnatly correlated with both self-reported current usage r = .63, Study 1) and self-predicted future usage r = .85, Study 2). Perceived ease of use was also significantly correlated with current usage r = .45, Study 1) and future usage r = .59, Study 2). In both studies, usefulness had a signficnatly greater correaltion with usage behavior than did ease of use. Regression analyses suggest that perceived ease of use may actually be a causal antecdent to perceived usefulness, as opposed to a parallel, direct determinant of system usage. Implications are drawn for future research on user acceptance.

40,720 citations

Journal ArticleDOI
TL;DR: In this article, the authors address the ability to predict peoples' computer acceptance from a measure of their intentions, and explain their intentions in terms of their attitudes, subjective norms, perceived usefulness, perceived ease of use, and related variables.
Abstract: Computer systems cannot improve organizational performance if they aren't used. Unfortunately, resistance to end-user systems by managers and professionals is a widespread problem. To better predict, explain, and increase user acceptance, we need to better understand why people accept or reject computers. This research addresses the ability to predict peoples' computer acceptance from a measure of their intentions, and the ability to explain their intentions in terms of their attitudes, subjective norms, perceived usefulness, perceived ease of use, and related variables. In a longitudinal study of 107 users, intentions to use a specific system, measured after a one-hour introduction to the system, were correlated 0.35 with system use 14 weeks later. The intention-usage correlation was 0.63 at the end of this time period. Perceived usefulness strongly influenced peoples' intentions, explaining more than half of the variance in intentions at the end of 14 weeks. Perceived ease of use had a small but significant effect on intentions as well, although this effect subsided over time. Attitudes only partially mediated the effects of these beliefs on intentions. Subjective norms had no effect on intentions. These results suggest the possibility of simple but powerful models of the determinants of user acceptance, with practical value for evaluating systems and guiding managerial interventions aimed at reducing the problem of underutilized computer technology.

21,880 citations

Journal ArticleDOI
TL;DR: In this article, a selection of fit indices that are widely regarded as the most informative indices available to researchers is presented, along with guidelines on their use and strategies for their use.
Abstract: The following paper presents current thinking and research on fit indices for structural equation modelling. The paper presents a selection of fit indices that are widely regarded as the most informative indices available to researchers. As well as outlining each of these indices, guidelines are presented on their use. The paper also provides reporting strategies of these indices and concludes with a discussion on the future of fit indices.

7,904 citations

Journal ArticleDOI
TL;DR: In this paper, the relative effects of usefulness and enjoyment on intentions to use, and usage of, computers in the workplace were reported concerning the relative benefits of using computers in work environments.
Abstract: Previous research indicates that perceived usefulness is a major determinant and predictor of intentions to use computers in the workplace. In contrast, the impact of enjoyment on usage intentions has not been examined. Two studies are reported concerning the relative effects of usefulness and enjoyment on intentions to use, and usage of, computers in the workplace. Usefulness had a strong effect on usage intentions in both Study 1, regarding word processing software (β=.68), and Study 2, regarding business graphics programs (β=.79). As hypothesized, enjoyment also had a significant effect on intentions in both studies, controlling for perceived usefulness (β=.16 and 0.15 for Studies 1 and 2, respectively). Study 1 found that intentions correlated 0.63 with system usage and that usefulness and enjoyment influenced usage behavior entirely indirectly through their effects on intentions. In both studies, a positive interaction between usefulness and enjoyment was observed. Together, usefulness and enjoyment explained 62% (Study 1) and 75% (Study 2) of the variance in usage intentions. Moreover, usefulness and enjoyment were found to mediate fully the effects on usage intentions of perceived output quality and perceived ease of use. As hypothesized, a measure of task importance moderated the effects of ease of use and output quality on usefulness but not on enjoyment. Several implications are drawn for how to design computer programs to be both more useful and more enjoyable in order to increase their acceptability among potential users.

5,367 citations