Improving the Behavioral Intention of Continuous Online Learning Among Learners in Higher Education During COVID-19

Wei, Xianfu; Shen, Zhi-Yi; Lin, Shijia; Chen, Jia-Chen

doi:10.3389/fpsyg.2022.857709

Cited by 13 publications

(16 citation statements)

References 26 publications

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“…Extant literature is still limited on the application of UTAUT to e-learning acceptance by students [44], particularly during the COVID-19 crisis. Experiences in the Middle East and East Asia [52,53,59,[59][60][61], as well as in several African countries [50,51,55], are particularly represented in literature. Experiences in other parts of the world, such as Europe or America, are comparatively less represented [49,57].…”

Section: The Utaut Framework and E-learning Acceptance During Covid-19mentioning

confidence: 99%

“…These hypotheses were elaborated based on the conclusions drawn in the extant literature on the application of UTAUT to e-learning acceptance, particularly during the COVID pandemic [35][36][37][38][43][44][45][46][47][48][49][50][51][52][53][54][55][56][57][58][59][60][61]. Indeed, most of the experiences represented in the literature validate the cause-effect relationships between the main constructs of the UTAUT model.…”

Section: Hypothesis 6 (H6) Behavioural Intention Has a Significant Ef...mentioning

confidence: 99%

“…The discriminant validity was tested using the classical methods of cross-load analysis and the Fornell-Larcker criterion. Cross-loads were calculated using the correlations between the construct scores and the standardised data [53]. To comply, no item should load more heavily on another construct than on the one it is meant to measure [46].…”

Section: Analysis Of the Measurement Systemmentioning

confidence: 99%

“…Although a number of recent studies have explored student technology acceptance of e-learning during the COVID-19 outbreak [9,[35][36][37][38][39][40][41][42], to the best of our knowledge, up to the current moment, no former study has been conducted in this particular regional context. Additionally, the number of works which have used the UTAUT model to study e-learning acceptance in this context is still limited [43][44][45][46][47][48][49][50][51][52][53][54][55][56][57][58][59][60][61]. Finally, no study to date has provided a comparison between public and private institutions.…”

Section: Introductionmentioning

confidence: 99%

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Student Acceptance of E-Learning during the COVID-19 Outbreak at Engineering Universities in Spain

2023

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This article analyses students’ intention to use a particular e-learning technology (MS Teams) at university during the COVID-19 outbreak in Spain using the Unified Theory of Acceptance and Use of Technology (UTAUT). The model was refined through a qualitative analysis based on six focus group discussions with students from different engineering faculties in Madrid, Spain. A survey involving 346 undergraduate students was subsequently fed into the model. Structural Equation Modelling (SEM) and SMART PLS software were applied for data analysis. The results shed light on theoretical and practical implications. The model was validated by the data and displayed a high predictive ability. Social influence was found to have the greatest influence over students’ acceptance, followed by the professor’s role in shaping the perception of improvement. Facilitating conditions were found to be the least relevant factor, probably due to the particular context in which this study was conducted. A significant difference was found between the public and private institutions in terms of the importance of the perceived usefulness for the professor (this factor was more important for students’ acceptance at the public university). In order to improve its acceptance and use under the current scenario, it is thus important for universities wishing to introduce e-learning to focus on creating a positive social environment around the e-learning platform, for example, by using social networks or relying on testimonies by professionals who could confirm the interest of such a platform in a future work environment. Understanding professors’ perspective on the implementation of the platform is also of paramount importance. More research is also needed regarding context-related differences when analysing students’ acceptance of e-learning.

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Section: The Utaut Framework and E-learning Acceptance During Covid-19mentioning

confidence: 99%

Section: Hypothesis 6 (H6) Behavioural Intention Has a Significant Ef...mentioning

confidence: 99%

Section: Analysis Of the Measurement Systemmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Student Acceptance of E-Learning during the COVID-19 Outbreak at Engineering Universities in Spain

2023

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“…However, UTAUT2 was chosen for this study because it focuses on end users' behavioural intentions toward new technology acceptance. According to Xu et al (2022) the effect of learning using technology tools is dependent on the learner behavioral intention in selflearning. Which is the construct for UTAUT2 model are contains (i) performance expectancy, (ii) effort expectancy, (iii) social influence, (iv) facilitating conditions, (v) hedonic motivation, (vi) price value, and (vii) habit are the independent construct while the behavioral intention is the dependent construct.…”

Section: Introductionmentioning

confidence: 99%

Acceptance of UTAUT2 Model for Professional Training via Mobile among Enforcement Officers at Malaysia

Sharuddin¹,

Ismail²,

Mohamad³

2023

IJARPED

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M -Learning is a new innovation in professional training for enforcement officers in Malaysia to achieve their key performance indicators in training attended. According to UTAUT2, there are seven components of acceptance that must be known in order to determine the level of acceptability among Enforcement Officers. This is a case study that includes a questionnaire with seven constructs and 35 questions was analyzed using mean and standard deviation. The construct for UTAUT2 model is (i) performance expectancy, (ii) effort expectancy, (iii) social influence, (iv) facilitating conditions, (v) hedonic motivation, (vi) price value, and (vii) habit are the independent construct while the behavioral intention is the dependent construct. In Malaysia, 30 respondents were chosen randomly selected from among Enforcement Officers. The reliability value of the questionnaire through the pilot study was 0.962 Cronbach's Alpha.The results obtained from this study found that five of the seven constructs had a high level of acceptability. While two constructs based on the UTAUT2 element show a moderate level of acceptance. It is related to the fact that enforcement officers do not have experience with mobile learning before and must be enhanced to reflect the seven UTAUT2 constructs in this M-Learning. The findings show that by integrating the constructs of facilitating condition and price value, the level of acceptance of mobile training Enforcement Officers can be strengthened. Because enforcement officers are willing to go through M-Learning to improve their job performance. The implications of this study, to improved acceptance of these two UTAUT2 model constructs along with existing constructs must be enhanced in order to produce mobile materials to contributed for professional training as a new medium to follow professional training continuously for government employees.

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Predictive analysis of Metaverse usage intention in the Spanish University

Castro-Lopez,

Cervero,

Alvarez-Blanco

2024

J. Comput. Educ.

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In technologically advanced societies, the Metaverse has become a three-dimensional digital space that merges the real and virtual worlds, creating new scenarios and possibilities for social interaction. Considering the early stage of its development, the goal of this research is to provide knowledge on the will and intention of university students to use the “Metaverse” for educational purposes, identifying the relevant influential factors on the matter. This would contribute to the assessment and possible action of higher education institutions regarding the integration of this technology in the design of teaching–learning activities. For this purpose, an ex post facto research methodology with a prospective design has been used, relying on a survey conducted with a specially designed questionnaire based on the extended version of the Unified Theory of Acceptance and Use of Technology, covering a sample of 480 university students. Descriptive analysis and structural equation modeling were performed using SPSS and SmartPLS. The influence intention to use the Metaverse were reduced to three dimensions: performance behavior, social influence, and perceived value. The obtained results consolidate, on a theoretical level, the robustness of the Technology Acceptance Model (UTAUT-2). From a practical point of view, they serve to inform tool developers about the aspects to be prioritized and strengthened for implementation of such technological instruments in a teaching–learning context. Therefore, the study provides relevant information about the integration of the Metaverse in educational institutions, especially at the university level, focusing attention on universities as necessary active protagonists of such process.

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Improving the Behavioral Intention of Continuous Online Learning Among Learners in Higher Education During COVID-19

Cited by 13 publications

References 26 publications

Student Acceptance of E-Learning during the COVID-19 Outbreak at Engineering Universities in Spain

Student Acceptance of E-Learning during the COVID-19 Outbreak at Engineering Universities in Spain

Acceptance of UTAUT2 Model for Professional Training via Mobile among Enforcement Officers at Malaysia

Predictive analysis of Metaverse usage intention in the Spanish University

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