Higher education (HE) consists of both conventional and non-conventional methods of learning. Open and Distance Learning (ODL) is a non-conventional system where teachers (often referred to as facilitators) are physically not present. The conduct of practical in engineering and science education using ODL remains a challenge due to inadequate technology and the dispersion of the students, which results in a graduate skills gap in ODL programs. There is a possibility of using a cloud computing set-up, as well as platforms for the creation of simulated virtual practical settings (virtual laboratories-VLs), which could be accessible by ODL engineering and science and education-based students notwithstanding their locations. This paper adds to existing knowledge on VLs and discusses these inadequacies in engineering and science education with emphasis on the enhancement of online and collaborative learning, as well as the possible laboratory (lab) requirements. In addition, the paper highlights contemporary trends and some issues in VLs and remote labs.

With the rapid development of artificial intelligence (AI) technology, its application in the field of auditing has gained increasing attention. This paper explores the application of AI technology in audit risk assessment and control (ARAC), aiming to improve audit efficiency and effectiveness. First, the paper introduces the basic concepts of AI technology and its application background in the auditing field. Then, it provides a detailed analysis of the specific applications of AI technology in audit risk assessment and control, including data analysis, risk prediction, automated auditing, continuous monitoring, intelligent decision support, and compliance checks. Finally, the paper discusses the challenges and opportunities of AI technology in audit risk assessment and control, as well as future research directions.

This study aims to explore the research on Chinese higher education policy from 2005 to 2024 through a bibliometric analysis. It is revealed that a continuous growth trend and sustained academic interest in this field. Mainland China leads in publication quantity, showcasing the active involvement of Chinese scholars in higher education policy research. Institutions like Peking University, the University of Hong Kong, and Beijing Normal University play significant roles in this research domain. The focus of research has shifted from student attitudes to international students, teachers, innovation models, changing demands, and urban education development, reflecting a growing emphasis on sustainability and internationalization. The study highlights the positive development trajectory of Chinese higher education policy research, with expanding research focuses and deepening concerns for sustainability and internationalization.

In order to assess the effects of e-learning integration on university performance and competitiveness, this study uses Oman as a model for the Gulf. Analyzing how e-learning impacts technology integration, diversity, community engagement, infrastructure, financial strength, institutional reputation, student outcomes, research and innovation, and academic quality can reveal whether universities are effectively incorporating digital tools to enhance teaching and learning. By offering a framework for comparable institutions in the Gulf area, this study provides insights into optimizing e-learning techniques to improve university performance and competitiveness. This study uses the Structural Equation Modeling (SEM) with a dataset comprising 424 participants and 55 indicators, analyzed using both measurement and structural models. The results of the hypothesis testing, which indicate that e-learning has a positive effect on factors like student outcomes (B = 0.080, t = 2.859, P = 0.004) and institutional reputation (B = 0.058, t = 2.770, P = 0.005), lend credence to these beliefs. Omani universities need culturally sensitive e-learning, stronger institutional support, and training to enhance diversity (B = 0.002, t = 0.456, P = 0.647) and technology integration (B = −0.009, t = 0.864, P = 0.387). These improvements increase the visibility of Gulf institutions abroad, attracting the best students from all around the world and fostering an inclusive learning atmosphere. Financially speaking, e-learning offers reasonably priced solutions such as digital libraries and virtual laboratories, which are especially beneficial in a region where education plays a major role in socioeconomic development.

The objectives of this qualitative research are to study problems and factors promoting success in the career path of government officials in the Ministry of Higher Education, Science, Research, and Innovation (MHESI) in Thailand. The study also finds out career path model to opinions between executives and government officials. This qualitative employed in-depth interview and focus group discussion with executives, academics, and civil servants. It found that the problem was the planning and management of career path due to lacking of standard pattern. Also, it found that the model of career path provides practitioners with career advancement opportunities and job titles from the very beginning to the very top where they can advance and can plan their career progression. The model also provides an opportunity to explore officers’ competencies, aptitudes, and interests that are appropriate for any type of work in the organization and able to prepare them to perform the job, which will affect the success of civil servants’ work and human resource management to create career path and develop oneself to be able to compete for academic and professional excellence, as well as prepare the government officers for appropriate positions in the future.

Mediating role of artificial intelligence in the relationship between higher education quality and scientific research ethics among faculty members: A Study in carrying out the study, specific research objectives were derived, and based on the derived objectives, null hypotheses were formulated and tested for the study. This study, thus, employed survey research design. This study’s population comprised postgraduate students from Middle Eastern University, Jordan, with 1200 students. Using the population, a sample size of 291 respondents was selected based on Krecie and Morgan The students in the sample completed Google Forms questionnaires. The data were statistically processed, and the analysis’s most significant level was 0.25. The research questions were analyzed using descriptive statistics, and the null hypothesis was tested using Pearson Product Moment Correlational Analysis (PPMC). Also, the study showed a significant relationship between artificial intelligence and the quality of higher education and the relationship of significance between artificial intelligence and ethics in scientific research. The researcher suggested a need for ongoing education, cross-discipline cooperation, and the development of solid ethical frameworks for the integration ethics of AI academia.