Metaverse, which combines a number of information technologies, is the Internet of the future. A media for immersive learning, metaverse could set future educational trends and lead to significant reform in education. Although the metaverse has the potential to improve the effectiveness of online learning experiences, metaverse-based educational implementations are still in their infancy. Additionally, what factors impact higher education students’ adoption of the educational metaverse remains unclear. Consequently, the aim of this study is to explore the main factors that affect higher education students’ behavioral intentions to adopt metaverse technology for education. This study has proposed an extended Technology Acceptance Model (TAM) to achieve this aim. The novelty of this study resides in its conceptual model, which incorporates both technological, personal, and inhibiting/enabling factors. The empirical data were collected via online questionnaires from 574 students in both private and public universities in Jordan. Based on the PLS-SEM analysis, the study identifies perceived usefulness, personal innovativeness in IT, and perceived enjoyment as key enablers of students’ behavioral intentions to adopt the metaverse. Additionally, perceived cyber risk is found as the main inhibitor of students’ metaverse adoption intentions. Surprisingly, the effect of perceived ease of use on metaverse adoption intentions is found to be insignificant. Furthermore, it is found that self-efficacy, personal innovativeness, and perceived cyber risk are the main determinants of perceived usefulness and perceived ease of use. While the findings of this study contribute to the extension of the TAM model, the practical value of these findings is significant since they will help educational authorities understand each factor’s role and enable them to plan their future strategies.

In higher education learning, e-learning systems have become renowned tools worldwide. The evident importance of e-learning in higher education has resulted in a prenominal increase in the number of e-learning systems delivering various forms of services, especially when traditional education (face-to-face) was suddenly forced to move online due to the COVID-19 outbreak. Accordingly, assessing e-learning systems is pivotal in the interest of effective use and successful implementation. By relying on the related literature review, an extensive model is developed by integrating the information system success model (ISSM) and the technology acceptance model (TAM) to illustrate key factors that influence the success of e-learning systems. Based on the proposed model, theory-based hypotheses are tested through structural equation modeling employing empirical data gathered through a survey questionnaire of 537 students from three private universities in Jordan. The findings demonstrate that quality factors, including instructor, technical system, support service, educational systems, and course content quality, have a direct positive influence on students’ satisfaction, perceived usefulness, and system use. Moreover, self-regulated learning negatively affects students’ satisfaction, perceived usefulness, and system use. Students’ satisfaction, perceived usefulness, and system use are key predictors of their academic performance. These findings provide e-learning stakeholders with important implications that guarantee the effective, successful use of e-learning that positively affects students’ learning.

The importance of self-regulation in a MOOC has been extensively discussed in research studies that provide evidence about the significant relationship between self-regulated learning and success in an e-learning environment. Learners with high self-regulated learning are more independent in regulating their learning and have a greater probability of success in their online courses. This study identifies factors that influence self-regulated learning and determines relationships between these factors and self-regulated learning. A conceptual model is proposed for combining success factors for self-regulated learning in a MOOC environment. A research instrument based on the model was designed and administered to six hundred and twenty-two MOOC students enrolled in five universities. Relationships between relevant factors and self-regulated learning were examined using a Partial Least Squares Structural Equation Modeling (PLS-SEM) technique, and the statistical findings revealed that three factors - service quality, attitude, and course quality - influence self-regulated learning in a MOOC.

The main purpose of the current research was to explore the relationships between beliefs/knowledge and technology integration (TI) during teaching practice (i.e., placement or practicum) among Indonesian pre-service teachers. Five core variables of the theory of planned behavior or TPB (subjective norms, attitudes, perceived behavioral control, behavioral intention, and behavior) and one extended variable, technological pedagogical and content knowledge or TPACK, were included in the proposed model. Data from 1,181 respondents were analyzed through the systematic steps of partial least square structural equation modeling (PLS-SEM) and importance-performance analysis (IPMA). The main findings support all hypotheses; the strongest relationship emerges between behavioral intention and behavior, while the weakest correlation was between TPACK and behavioral intention. All variable performances were satisfactory. The highest performance was attitudes (71.734); the lowest was TPACK (65.027). Broadly, the results indicate the greater importance of beliefs as opposed to knowledge in influencing behavior in relation to TI.

Aim/Purpose: The main objective of this study is to explore students’ beliefs with regard to social media use (SMU) in higher education and the consequences of such use on the perception of their academic performance. Additionally, the study aims to determine the major influential factors with regard to SMU in student learning settings as a means of enhancing their performance. To achieve these objectives, drawing on the literature related to SMU in higher education settings, a research model has been developed. Background: Social media platforms have led to a significant transformation with regard to the communication landscape in higher education in terms of offering enhanced learning and improved teaching experience. Nevertheless, little is known, particularly in developing countries such as Jordan, as to whether or not the use of such platforms by students in higher education increases the perceptions of their academic performance. Therefore, this study has developed a model to examine the perceptions of higher education students with regard to social media use and its effect on their performance. Methodology: The Structural Equation Modelling approach is used to analyze data collected via an online survey in the form of a questionnaire to examine the use of such a model. The study sample is drawn from undergraduate and postgraduate students from three universities (one public and two private) in Jordan. Convenience sampling is used to collect data. Out of 730 sent questionnaire, 513 responses were received, of which 403 were deemed qualified to be part of the data analysis process. Contribution: This study contributes to the literature on social media in higher education by enhancing our understanding of the perceptions of higher education students on the use of social media in their learning. The tested model can be used as a benchmark for other studies that target the impact of social media on student performance in higher education. Findings: The results reveal that perceptions of (1) usefulness, collaborative learning, enhanced communication, enjoyment, and ease of use of social media have a positive effect on the use of such media in student learning; (2) resource sharing has an insignificant effect on social media use in student learning, and (3) social media use has a positive influence on students’ perceptions of their academic performance. Recommendations for Practitioners: Senior management and policy makers in higher education institutions will have to train faculty members on effective strategies and methods in order to effectively integrate social media into education. This would equip faculty members with the necessary digital skills needed to help them to be fully informed regarding the benefits of social media and its tools in learning and teaching activities and would also allow them to avoid any possible drawbacks. Furthermore, faculty members should reconsider their current techniques and strategies, and adopt new methods in their teaching that encourage students to use social media platforms as part of their learning. For example, they can regularly post discussions and assignments on social media platforms to inculcate the habit of using such platforms among students for educational purposes. Students, on the other hand, should be aware of the implications and potential advantageous aspects of SMU in their learning. This could be done by conducting regular workshops and seminars in the various faculties and schools at universities. Recommendation for Researchers: Researchers are encouraged to investigate additional factors that might influence the use of social media by students as well as faculty members. Specially, an emphasis should be given to identify any potential obstacles that might hinder the use of social media in higher education. Impact on Society: Social media is not only useful for socializing, but also it can be an effective educational tool that enhance students’ performance in higher education. Future Research: Although the collected data support the research model, this study is subjected to various limitations that need to be tackled by further studies. This study is based on the principles of quantitative research design. Data for this study was collected via survey questionnaires. Accordingly, future studies may consider a qualitative research design in order to uncover additional factors that may impact the use of social media on the part of higher education students. This would allow researchers to generate in-depth insights and a holistic understanding of SMU by higher education students. A convenience sampling method was employed to select respondents for this study. The respondents who participated in this study were from three universities (one public and two private) in Jordan. Accordingly, future research is deemed to be necessary to achieve a degree of generalizability regarding the findings of this study.