With the continuous deepening of education and teaching reform and the rapid development of information technology, more and more educators have paid attention to the effectiveness of computer teaching in universities, and university teachers have included it in the key topics of educational and teaching activity design. The cooperative teaching model stands out among numerous teaching models with its unique advantages, and has been applied by many teachers in the classroom teaching process, playing an important role in promoting the improvement of teaching efficiency. Teachers of computer science in universities should continue to explore effective teaching methods, accelerate the process of organic integration of cooperative teaching models and classroom teaching content, in order to deepen the understanding and cognition of computer knowledge among more students and promote their comprehensive development. This article will study the application strategies of cooperative teaching mode in computer teaching in universities.

To evaluate the efficiency of decision-making units, researchers continually develop models simulating the production process of organizations. This study formulates a network model integrating undesirable outputs to measure the efficiency of Vietnam’s banking industry. Employing methodologies from the data envelopment analysis (DEA) approach, the efficiency scores for these banks are subsequently computed and comparatively analyzed. The empirical results indicate that the incorporation of undesirable output variables in the efficiency evaluation model leads to significantly lower efficiency scores compared to the conventional DEA model. In practical terms, the study unveils a deterioration in the efficiency of banking operations in Vietnam during the post-Covid era, primarily attributed to deficiencies in credit risk management. These findings contribute to heightening awareness among bank managers regarding the pivotal importance of credit management activities.

The 2019 Social Enterprise Promotion Act in Thailand represents a pivotal step towards promoting social enterprises by fostering self-reliance and a fair and sustainable future for the country. Despite their significance, there is a noticeable research gap focusing on the factors that motivate Thai entrepreneurs to venture into social entrepreneurship. This study seeks to fill that gap by analyzing data from 2000 respondents in Thailand, utilizing linear regression to explore whether the awareness of the United Nations Sustainable Development Goals (SDGs), the adoption of digital technologies, extrinsic motivations, such as the overall societal view of entrepreneurs, social awareness, and perceptions of entrepreneurial capabilities influence the decision to start a social enterprise. In a gender comparison, our findings reveal that the societal context plays a crucial role for both genders, although in distinct ways: Male entrepreneurs are more influenced by individualistic extrinsic values, with motivations linked to power, respect, and societal recognition. In contrast, female entrepreneurs display a collectivistic orientation, being more likely to be inspired by intrinsic motivations, such as the success and visibility of other successful startups within their society. These findings underline the need for a gender-sensitive approach by government bodies, educational institutions, and other relevant organizations aiming to boost start-up rates of enterprises who “make a difference in the world”. Tailored support and educational programs to address the unique motivations and perspectives of male and female entrepreneurs could play a crucial role in enhancing the effectiveness of strategies designed to promote social entrepreneurship in Thailand and beyond.

The article addresses the issue of educational development policy in Ukraine: the main trends and ways, means, technologies of their implementation. It has been observed that educational policy is developing and changing under the influence of such factors as Russia’s military actions against our country, European integration and globalisation. It has been taken into account that globalisation trends in the world integration, according to which globalisation processes should be reflected not only in the foreign economic, political or technological spheres, but also, as a consequence, in the development of technologies for training future teachers. Integration of digital technologies in the educational process is one of the key tendencies in the modern educational policy in Ukraine. The characteristics of the most used technologies of augmented reality in the modern school of Ukraine have been outlined. The algorithm for displaying generalized information about a particular application was proposed, namely: payment, accessibility, language, system requirements; learning opportunities; practical value; website; video about the application. The model of the formation of future teachers’ skills to use augmented reality technologies in the process of natural sciences studying has been proposed. We consider it as a component of a holistic system of future teachers’ professional training. The conceptual basis for the development of the model is a multi-subject educational paradigm, which is considered to be open, self-developing and self-organizing, causing a fundamental change in the behavior and relationships of the educational process participants. The proposed model is implemented in the authors’ methodological system, which ensures the interconnected activities of all participants in the educational process. Its systemic factor is the goal of improving the quality of the future natural sciences teachers’ professional training by developing their skills in using AR technology. The end result is an increase in the level of future natural sciences teachers’ readiness to use AR technology in their professional activities.

Under the background of the development of the network information age, the current Internet industry has obtained more development opportunities, but it has also brought corresponding challenges in the process of wide application. In the development and construction of modernization, society pays more attention to the supervision and determination of the characteristics of online public opinion. From the perspective of the current characteristics of network public opinion, because social information is more extensive and involves many fields, network public opinion has a high degree of complexity and diffusion. Therefore, it is necessary to strengthen the analysis and application of relevant data mining systems in order to achieve efficient management of network public opinion. The key to the disadvantage of the traditional excavation of public opinion communication characteristics lies in the lag of the excavation process, and it is difficult to deal with malignant public opinion in a timely and effective manner. Therefore, in order to truly solve the lagging problem of public opinion data dissemination feature mining technology, it is necessary to strengthen the application of artificial intelligence technology in it.