With the rapid development of modern AI painting, Chinese university fine arts education is facing numerous challenges and opportunities. This paper analyzes the impact of modern AI painting on traditional art creation and its implications for student skill development. Additionally, it explores the key areas where Chinese university fine arts education needs to transform, including curriculum, teaching methods, and teacher training, while proposing corresponding strategies.

Under the background of the continuous development of science and technology, the era of big data has come in an all-round way, and big data technology has also been widely used in the education industry. The course of financial management in applied colleges and universities is a highly applied course, which focuses on the substance of the course. Teachers need to create a good learning environment for students with the help of information technology, and constantly cultivate students' professional skills and professionalism. In order to improve the quality of financial management courses in colleges and universities, this paper mainly analyzes the management courses in application-oriented colleges and universities, expounds the factors affecting the practical teaching quality of management courses in colleges and universities, and analyzes the teaching methods of management courses in application-oriented colleges and universities. Finally, it is concluded that only when teachers constantly improve their teaching level, can students' learning level be improved by combining theory with practice.

In the era of rapid technological development, the integration of technology in education has become crucial (Hashim et al., 2022). The digital transformation of education requires universities to transform their traditional operational models, strategic directions, and teaching practices, re-examine their own value propositions, and promote high-quality innovative development in universities. Transformation and change bring challenges to organizational management, especially leadership. Can digital leadership positively influence the innovative behavior of university teachers? Can digital leadership improve organizational innovation performance by influencing innovation behavior? These questions urgently need to be answered through practical surveys of digital transformation in universities. From March 2024 to May 2022, we conducted a survey of 1142 participants from 12 universities in Kunming, southwestern China. Our research findings indicate that digital leadership has a positive impact on the innovation performance of university organizations; Innovation behavior plays a mediating role between digital leadership and organizational performance. These findings provide new insights into the potential mechanisms by which digital leadership influences organizational innovation in universities. The research findings emphasize that in the process of transforming traditional operational models, strategic directions, and teaching practices in higher education, in order to achieve high-quality innovative development, it is necessary to attach importance to digital leadership and continuously stimulate innovative behavior.

The construction and development of teachers has always been the focus of the construction and development of colleges and universities, and each school has also set up a lot of relevant departments or institutions such as the University Party Committee Teacher Work Department, Academic Affairs Office, Personnel Division, Teacher Development Center and so on. However, a lot of adaptation problems still exposed gradually after the entry of new full-time teachers. This paper takes Longyan University as an example to make some basic analysis and put forward relevant suggestions.

Purpose: This research aims to examine the influence of intellectual capital disclosure and the geographical location of universities on the sustainability of higher education institutions in Southeast Asia. Design/methodology/approach: This research is quantitative and uses secondary data obtained through the annual reports of universities that have the Universitas Indonesia Green Metric Rank. This research uses two stages of data analysis techniques, namely the content analysis stage to determine the number of Intellectual Capital disclosures and the hypothesis testing stage. The analysis tool uses the SPSS version 23 application. The population of this research includes all universities in Southeast Asia that are included in the UI Greenmetric World University Rankings. The sampling technique used was purposive sampling technique, which resulted in 86 analysis units of higher education institutions in Southeast Asia. Findings: The research results prove that the geographical location of universities has a negative and significant influence on Universitas Indonesia Green Metric’s performance in Southeast Asia and human capital has a positive influence on UIGM’s performance in Southeast Asia. However, the structural capital and relational capital components do not affect the UIGM performance of universities in Southeast Asia. Originality/value: The originality of the research is the use of higher education sustainability variables with UIGM proxies and modified IC indicators for universities and geographical areas that have not been widely used to see whether there are fundamental differences in the disclosure of intellectual capital for higher education institutions in Southeast Asia.