This study analyzes the perception of university students regarding the use of virtual reality (VR) in higher education, focusing on their level of knowledge, usage, perceived advantages and disadvantages, as well as their willingness to use this technology in the future. Using a mixed-methods approach that combines questionnaires and semi-structured interviews, both quantitative and qualitative data were collected to provide a comprehensive view of the subject. The results indicate that while students have a basic understanding of VR, its use in the educational context is limited. A considerable number of students recognize VR’s potential to enhance the learning experience, particularly in terms of immersion and engagement. However, significant barriers to adoption were identified, such as technical issues, the high cost of equipment, and inadequate access to technological infrastructure. Additionally, there is a need for broader training for both students and faculty to ensure the effective use of this technology in academic environments. The semi-structured interviews confirmed that perceptions of VR vary depending on prior exposure to the technology and access to resources. Despite the challenges, most students appreciate VR’s potential to enrich learning, although its effective adoption will depend on overcoming the identified barriers. The study concludes that strategies must be implemented to facilitate the integration of VR into higher education, thus optimizing its impact on the teaching-learning process.

The present research focuses on researching the impact of the diverse communication media that facilitate or develop Student Motivation and Engagement in the educational systems of the states in the Gulf, especially Oman. The main goal of this work is to determine which type of method is most effective in encouraging students in view of cultural and technological factors present in the region. Comparisons using hypothesis testing and structural models which provided higher T value for Technology-Based Communication Methods (TBCM) and Human Face-to-Face Communication Methods (HFtFCM). Next, the research hypothesis H2 that TBCM has a direct positive relationship with SMaE was supported by the following regression coefficients: β = 0.177, t = 4.493; p = 0.000. On the other hand, there was no effect of HFtFCM on SMaE as indicated by a regression coefficient of 0.056 (p < 0.124) for this hypothesis and therefore, this hypothesis was rejected. The analysis using the mediator of Student Perception of Communication Effectiveness (SPoCE) only partly mediates TBCM and SMaE (β = 0.047, t = 3.737, p = 0.000). However, SPoCE was found not to moderate the relationship between HFtFCM and SMaE (β = −0.01, t = 1.125, p = 0.005). The present study underlines the efficiency of TBCM in the area of student engagement, while face-to-face conversation does not play significant part in this process. The obtain results conclude that, the traditional and technological evolution in the Gulf region supports the adoption of TBCM in educational systems. Such approaches support with the technological learning and likings of students, offering greater flexibility and engagement. Educational systems must highlight TBCM to better meet the growing needs of their student, while identifying that face-to-face remains important, though secondary, in energetic motivation.

Since 1999, China’s higher education has experienced significant growth, with the government dramatically increasing college enrollment rates, thereby enhancing the overall quality of education. However, most existing studies have primarily focused on the quantity of education, with little attention having been given to the impact of higher education quality (HEQ) on economic growth. This study aims to explore how higher education quality (HEQ) contributes to regional economic growth through scientific and technological innovation (STI) and human capital accumulation. Using panel data from 31 Chinese provinces from the period 1999 to 2022, panel regression models and instrumental variable methods were employed to analyze both the direct and indirect impacts of higher education quality (HEQ) on economic growth. The results confirm that improving higher education quality (HEQ) is crucial for sustaining China’s economic growth. More specifically, higher education promotes regional economic expansion both directly, by enhancing labor productivity, and indirectly, by facilitating scientific and technological innovation. Furthermore, the study suggests that the balanced distribution of educational resources across regions should be prioritized to support coordinated regional development. This research provides insights for policymakers on how balanced regional economic development can be achieved through educational and technological policies. This work also lays a foundation for future studies.

Relational database models offer a pathway for the storage, standardization, and analysis of factors influencing national sports development. While existing research delves into the factors linked with sporting success, there remains an unexplored avenue for the design of databases that seamlessly integrate quantitative analyses of these factors. This study aims to design a relational database to store and analyse quantitative sport development data by employing information technology tools. The database design was carried out in three phases: (i) exploratory study for context analysis, identification, and delimitation of the data scope; (ii) data extraction from primary sources and cataloguing; (iii) database design to allow an integrated analysis of different dimensions and production of quantitative indicators. An entity-relationship diagram and an entity-relationship model were built to organize and store information relating to sports, organizations, people, investments, venues, facilities, materials, events, and sports results, enabling the sharing of data across tables and avoiding redundancies. This strategy demonstrated potential for future knowledge advancement by including the establishment of perpetual data updates through coding and web scraping. This, in turn, empowers the continuous evaluation and vigilance of organizational performance metrics and sports development policies, aligning seamlessly with the journal’s focus on cutting-edge methodologies in the realm of digital technology.

The effectiveness and efficiency of e-learning system in industry significantly depend on users’ acceptance and adoption. This is specifically determined by external and internal factors represented by subjective norms (SN) and experience (XP), both believed to affect users’ perceived usefulness (PU) and perceived ease of use (PEOU). Users’ acceptance of e-learning system is influenced by the immensity of region, often hampered by inadequate infrastructure support. Therefore, this study aimed to investigate behavioral intention to use e-learning in the Indonesian insurance industry by applying Technology Acceptance Model (TAM). To achieve this objective, Jabotabek and Non-Jabotabek regions were used as moderating variables in all related hypotheses. An online survey was conducted to obtain data from 800 respondents who were Indonesian insurance industry employees. Subsequently, Structural Equation Model (SEM) was used to evaluate the hypotheses, and Multi-Group Analysis (MGA) to examine the role of region. The results showed that out of the seven hypotheses tested, only one was rejected. Furthermore, XP had no significant effect on PU, and the most significant correlation was found between PEOU and PU. In each relationship path model, the role of region (Jabodetabek and Non Jabodetabek) had no significant differences. These results were expected to provide valuable insights into the components of e-learning acceptability for the development of a user-friendly system in the insurance industry.

The fifth-generation technology standard (5G) is the cellular technology standard of this decade and its adoption leaves room for research and disclosure of new insights. 5G demands specific skillsets for the workforce to cope with its unprecedented use cases. The rapid progress of technology in various industries necessitates a constant effort from workers to acquire the latest skills demanded by the tech sector. The successful implementation of 5G hinges on the presence of competent individuals who can propel its progress. Most of the existing works related to 5G explore this technology from a multitude of applied and industrial viewpoints, but very few of them take a rigorous look at the 5G competencies associated with talent development. A competency model will help shape the required educational and training activities for preparing the 5G workforce, thereby improving workforce planning and performance in industrial settings. This study has opted to utilize the Fuzzy Delphi Method (FDM) to investigate and evaluate the perspectives of a group of experts, with the aim of proposing a 5G competency model. Based on the findings of this study, a model consisting of 46 elements under three categories is presented for utilization by any contingent of 5G. This competency model identifies, assesses, and introduces the necessary competencies, knowledge, and attributes for effective performance in a 5G-related job role in an industrial environment, guiding hiring, training, and development. Companies and academic institutions may utilize the suggested competency model in the real world to create job descriptions for 5G positions and to develop curriculum based on competencies. Such a model can be extended beyond the scope of 5G and lay the foundation of future wireless cellular network competency models, such as 6G competency models, by being refined and revised.