With the continuous development of social economy and science and technology, the world has entered the era of artificial intelligence. my country is also working hard on the cultivation of talents in the field of artificial intelligence, and paying more and more attention to technology research and development. This puts forward higher requirements for cultivating higher education talents. It is not only necessary to work hard on the cultivation of “people”, implement the concept of mass entrepreneurship and innovation, adapt to the development of the times, update educational concepts, and improve students’ thinking ability and logic ability. We must also work hard on “talent”, innovate teaching methods, integrate education with science and technology, and provide talent guarantee and intellectual support for social development.

This study assesses the implementation of socioformation in Public Higher Education Institutions (HEIs) in Mexico, exploring its impact on the quality of education in the knowledge society. With a sample of 150 educators, gender-balanced (44.7% female, 55.3% male), and an average age of 43.7 years, the research employed a validated socioformative rubric. Significant progress was observed in analytical and creative thinking, while areas related to living conditions and entrepreneurship education showed slower development. The findings highlight the advancements in socioformation but advocate for further research, including classroom observation and student evidence collection. Gender differences, communication, and leadership emerged as critical factors influencing socioformation implementation. Women demonstrated deeper comprehension of the educational model, willingness to adopt innovative strategies, and emphasis on socioformation axes. As educators gain experience, their adaptability to new pedagogical approaches increases. The study underscores the universal relevance of effective communication, leadership, and stakeholder involvement in successful educational model implementation. The research contributes valuable insights, emphasizing the importance of openness to new approaches and collaboration to prepare students for the challenges of the evolving knowledge society.

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.

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.