Universities play a key role in university-industry-government interactions and are important in innovation ecosystem studies. Universities are also expected to engage with industries and governments and contribute to economic development. In the age of artificial intelligence (AI), governments have introduced relevant policies regarding the AI-enabled innovation ecosystem in universities. Previous studies have not focused on the provision of a dynamic capabilities perspective on such an ecosystem based on policy analysis. This research work takes China as a case and provides a framework of AI-enabled dynamic capabilities to guide how universities should manage this based on China’s AI policy analysis. Drawing on two main concepts, which are the innovation ecosystem and dynamic capabilities, we analyzed the importance of the AI-enabled innovation ecosystem in universities with governance regulations, shedding light on the theoretical framework that is simultaneously analytical and normative, practical, and policy-relevant. We conducted a text analysis of policy instruments to illustrate the specificities of the AI innovation ecosystem in China’s universities. This allowed us to address the complexity of emerging environments of innovation and draw meaningful conclusions. The results show the broad adoption of AI in a favorable context, where talents and governance are boosting the advance of such an ecosystem in China’s universities.

The development of the times and the progress of society have put forward new requirements for the conduct of party building work. Only by adhering to innovative ideas, continuously adjusting and scientifically planning the mode of party building work, can a new and systematic guidance system for party building be constructed, so that the conduct of party building work in universities presents a new development state and mode. Based on the influence of the information technology environment and the guidance of the spirit of the 20th National Congress, this article explores and analyzes the innovative reform of party building work in universities in the new era. From different perspectives such as introducing advanced technology and innovative party building work concepts, it systematically explores the innovative planning measures for party building work, striving to build a new organizational system for party building in universities, and scientifically optimize the value and effectiveness of party building work in universities.

From the rich results generated by the combination of psychology and education in universities, it can be seen that the experimental education school that emerged in Europe and the United States in the late 19th century was a purely empirical spirit influenced experimental behavior in education and teaching; He pioneered a scientific educational experimental model, which is a milestone in the development history of education. It first introduces scientific experimental models into educational experiments through psychology, thereby promoting the development of educational experiments towards a scientific and standardized direction. This educational experiment of positivism paradigm, which evolved from the experimental research of psychology, is also the research paradigm advocated by psychological education in colleges and universities after the combination of college psychology and scientific education.

This study examines the effectiveness of Kazakhstan’s grant funding system in supporting research institutions and universities, focusing on the relationship between funding levels, expert evaluations, and research outputs. We analyzed 317 projects awarded grants in 2021, using parametric methods to assess publication outcomes in Scopus and Web of Science databases. Descriptive statistics for 1606 grants awarded between 2021 and 2023 provide additional insights into the broader funding landscape. The results highlight key correlations between funding, evaluation scores, and journal publication percentiles, with a notable negative correlation observed between international and national expert evaluations in specific scientific fields. A productivity analysis at the organizational level was conducted using non-parametric methods to evaluate institutional efficiency in converting funding into research output. Data were manually collected from the National Center of Science and Technology Evaluation and supplemented with publication data from Scopus and Web of Science, using unique grant numbers and principal investigators’ profiles. This comprehensive analysis contributes to the development of an analytical framework for improving research funding policies in Kazakhstan.