In this article, digital transformation is examined as a key driver of structural and pedagogical change in higher education. This process is shown to expand access to learning, increase flexibility, support personalized educational trajectories, and enhance data-driven decision-making. At the same time, the effectiveness of digital transformation depends on institutional readiness, the quality of technological infrastructure, and the professional competencies of teaching staff. This research of this study is to assess the influence of digital transformation on the quality of higher education. This research employs a mixed-methods approach. Quantitative data from surveys of 4971 students and 483 instructors were analyzed using descriptive statistics, analysis of variance ANOVA, and multivariable regression, while qualitative focus group findings were examined through thematic analysis. The results indicate generally positive attitudes toward digitalization. The respondents emphasized flexibility and improved conditions for independent learning as key advantages of digital environments. However, this study also identifies several challenges, including infrastructural inequality, limited digital skills, and insufficient pedagogical adaptation. The article concludes that successful digital transformation requires a comprehensive strategic vision and sustained institutional support. For universities, strengthening digital competencies, modernizing infrastructure, and implementing management models focused on continuous improvement are essential conditions for ensuring sustainable development and enhancing the quality of education.

This paper describes a method and technology for processing natural language texts and extracting data from the text that correspond to the semantics of an ontological model. The proposed method is distinguished by the use of a Large Language Model algorithm for text analysis. The extracted data are stored in an intermediate format, after which individuals and properties that reflect the specified semantics are programmatically created in the ontology. The proposed technology is implemented using the example of an ontological model that describes the geographical configuration and administrative–territorial division of Kazakhstan. The proposed method and technology can be applied in any subject areas for which ontological models have been developed. The results of the study can significantly improve the efficiency of using knowledge bases based on semantic networks by converting texts in natural languages into semantically linked data.

This article is dedicated to the development of a model for competencies within an educational program and its implementation through the use of semantic technologies. The model proposed by the authors is distinctive in that competencies are organized into a hierarchical data structure with arbitrary levels of nesting. Furthermore, the article presents an original solution for modelling the input requirements for studying a course, which is defined in the form of dependencies between the competencies generated by the course and the competencies of other courses. The outcome of this work is an ontological model of a competency-based curriculum, for which the authors have developed and implemented algorithms for data addition and retrieval, as well as for analyzing the consistency of the curriculum in terms of the input requirements for studying a discipline and the learning outcomes from previous periods. The findings presented in the article will prove to be valuable in the development of educational process management information systems and educational program constructors. They will also be instrumental in aligning diverse educational programs within the context of academic mobility.

In this article, the development of in-service teachers’ digital competence is examined within an AI-supported learning environment designed to enhance professional modeling skills and the creation of interactive AR-based instructional content. The study investigates how such an environment supports teachers in developing contextual digital skills that enable not only the use of emerging technologies but also their meaningful adaptation to pedagogical goals and instructional needs. A training program involving 916 in-service teachers from Kazakhstani secondary schools was implemented, and survey data were collected to assess changes in digital competence and readiness to integrate AI and AR tools into teaching practices. The findings demonstrate high levels of interest and engagement: 96% of participants expressed readiness for further learning, 86% reported satisfaction with the course content, and 84% showed contextual maturity in applying newly acquired technologies in their instructional processes. These results highlight the potential of AI-supported professional development to strengthen teachers’ capacity to design interactive learning environments, promote equity and quality in digital education, and enhance student engagement.

The article presents the results of the application of an ontological approach to the description of the structure and content of the educational programme, and its subsequent analysis for the consistency of prerequisites and learning outcomes of courses. The practical result of the work is an ontology approach implemented in the Protégé 5.5.0 editor, which reflects the studied disciplines in terms of the skills they form and the entrance requirements (prerequisites) for the qualification of the student. The curriculum model includes sequences of semesters and courses of study (academic year) related by time relationships. The developed ontology approach is filled with data from the educational programme “Software Engineering”. The authors have earned queries in DL Query and SPARQL languages, which, using logical inference procedures, make it possible to analyse an educational programme for consistency of disciplines in terms of input requirements and the skills of the learner formed during the training period. The developed ontology and rules of logical inference can be used as a part of the educational process management information systems and educational programme designers, for the intellectual analysis of programme integrity and the consistency of learning prerequisites and outcomes in disciplines.