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TRAINING COMPUTER SCIENCE TEACHERS: THE ANALYSIS OF EDUCATIONAL PROGRAMMES FOCUSING ON DATABASES

Authors: Vladyslav Bespalyi; Artem Yurchenko; Olena Semenikhina;

TRAINING COMPUTER SCIENCE TEACHERS: THE ANALYSIS OF EDUCATIONAL PROGRAMMES FOCUSING ON DATABASES

Abstract

This article examines the current state of computer science teacher training in Ukraine, with a particular focus on the study of databases as a critical component of both digital and subject-specific competencies. The relevance of this topic is substantiated in the context of the digital transformation of education, the economy, and society, as well as the growing demand for professionals capable of effectively working with information systems, databases, and cloud-based services. The study emphasizes the importance of mastering not only the fundamentals of the relational data model and SQL but also modern technologies such as NoSQL, Big Data, and data analytics tools. The methodological framework of the research includes content analysis of educational and professional programs in Ukrainian higher education institutions, elements of comparative analysis, and the synthesis of regulatory requirements with contemporary pedagogical approaches. The article presents comparative data on course duration, technologies covered, instructional platforms used, and the starting point of database instruction across several universities. Strengths and weaknesses of the educational programs are identified, including the predominance of classical DBMSs, limited coverage of emerging technologies, insufficient interdisciplinary integration, and weak alignment with real-world IT industry cases. The article discusses opportunities for improving the content of academic disciplines through updated methodological support, a strengthened practice-oriented component, alignment with international standards, and the integration of artificial intelligence and Big Data analytics elements. Recommendations are provided for the development of flexible, relevant, and technologically updated educational programs. This article may be of interest to researchers, university instructors, educational program developers, and specialists involved in the digital transformation of education.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
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