This study evaluated the performance of several machine learning classifiers—Decision Tree, Random Forest, Logistic Regression, Gradient Boosting, SVM, KNN, and Naive Bayes—for adaptability classification in online and onsite learning environments. Decision Tree and Random Forest models achieved the highest accuracy of 0.833, with balanced precision, recall, and F1-scores, indicating strong, overall performance. In contrast, Naive Bayes, while having the lowest accuracy (0.625), exhibited high recall, making it potentially useful for identifying adaptable students despite lower precision. SHAP (SHapley Additive exPlanations) analysis further identified the most influential features on adaptability classification. IT Resources at the University emerged as the primary factor affecting adaptability, followed by Digital Tools Exposure and Class Scheduling Flexibility. Additionally, Psychological Readiness for Change and Technical Support Availability were impactful, underscoring their importance in engaging students in online learning. These findings illustrate the significance of IT infrastructure and flexible scheduling in fostering adaptability, with implications for enhancing online learning experiences.

The article presents the experience of formation and development of economic competences of non-economic specialty students. The modern world is quite complex, diverse, and multidimensional, in order to adapt to it, work effectively, it is necessary to have information about market relations, relations in the sphere of production, consumption, exchange, distribution, and also to be able to connect these areas, navigate the laws operating in these areas. It should be noted that the formation and development of a specialist’s economic competence occurs throughout his or her entire professional life. In our study, the process of forming economic competence is considered as its formation at the stage of mastering economic disciplines, relevant special courses and methodical support. Training in higher education should lead to the acquired knowledge being transferred into the activity of combining elements into an interconnected structure, into the skillful distribution of resources, into the activity that brings profit and has the form of capital investment, in other words, the individual, acquiring knowledge for himself, should be able to transform it into a socially significant value. This requires the search for and implementation of new approaches in the content and organization of the educational process at all levels of education. Research devoted to the role of education in the preparation of future non-economists for economic competence focuses on the preparation of an individual for the economic literacy of an entrepreneur. One of the main tasks of the education system should be preparation for successful socialization in the context of involvement in entrepreneurial relations. It is students and young specialists who have advantages in entrepreneurship in the current conditions: they have the opportunity to obtain specialized knowledge and skills in the field of economics; they can start their own business, relying on economic knowledge. Therefore, the role of higher education is increasing, since it helps to meet the needs of society and implement its socially significant goals. This poses new challenges for universities to transfer the necessary economic knowledge, skills and abilities to students, and to develop their economic competence. The development of basic economic competences in a student is a guarantee of his competitiveness in the labor market and the basis for making reasonable economic decisions in the daily life of every person.

To address gaps in practical skills among Public Health and Preventive Medicine graduates, an ‘open collaborative practice teaching model’ integrating medicine, teaching, and research was introduced. A cross-sectional study surveyed 312 Preventive Medicine undergraduates at a Yunnan medical university from 2020 to 2023, utilizing satisfaction scores and analyses (cluster, factor, SWOT) to assess the impact of the reform. Satisfaction scores from baseline, mid-term, and end-term assessments showed minor variations (4.30, 4.29, 4.36), with dissatisfaction primarily related to teaching content and methods. Key influences on satisfaction included teaching content, methods, and effectiveness. The SWOT analysis highlighted the importance of continuously updating teaching strategies to meet changing student expectations. This study suggests that the model has the potential for wider use in enhancing public health education, particularly in regions facing similar challenges.