Individual components of the methodology for developing digital competency of research and academic staff using scientometric databases

- Мінтій, І.С. (orcid.org/0000-0003-3586-4311), Вакалюк, Тетяна Анатоліївна (orcid.org/0000-0001-6825-4697) and Ткаченко, В.А. (orcid.org/0000-0003-4028-4522) (2025) Individual components of the methodology for developing digital competency of research and academic staff using scientometric databases Scientific Bulletin of South Ukrainian National Pedagogical University named after K. D. Ushynsky, 3 (152). ISSN 2414-5076 (In Press)

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Abstract

The research relevance is conditioned by the rapid growth of scientific information volumes and active implementation of AI technologies in research activities, necessitating a rethinking of traditional approaches to working with scientometric databases and forming new digital competencies among researchers and academic staff. The exponential increase in scientific publications, combined with revolutionary changes brought by AI technologies in research processes, requires developing innovative approaches to using scientometric tools and creating effective methodologies for developing digital competencies of scientific and academic personnel. The aim of the article is to describe individual components of the methodology for developing digital competency of researchers and academic staff using scientometric databases. Research methods are based on an integrated approach that combines the Scopus scientometric database, Claude AI assistant for query formulation and results analysis, VOSviewer platform for data visualization, and Scopus AI for results verification. Content and research results: individual components of the comprehensive methodology have been developed that include stages of query formulation using AI, data search and filtering in databases, results visualization, critical analysis and verification. The methodology has an iterative character and ensures the development of digital competency of researchers and academic staff. The novelty of the approach lies in the synergistic combination of traditional scientometric methods with AI technologies, allowing for improvement in search query accuracy compared to classical methods. The practical significance is determined by the ability to form researchers' skills in effective search, critical analysis, and visualization of scientific information, which is critically important in the context of digital transformation of education and science. The methodology testing demonstrated high efficiency in training competitive specialists capable of working with large arrays of scientific data and making informed decisions based on comprehensive information analysis. The approach provides systematic development of digital competencies essential for modern research activities.

Item Type:	Article
Keywords:	digital competency, scientometric databases, artificial intelligence, Scopus, VOSviewer, researchers, academic staff, bibliometric analysis, data visualization
Subjects:	Science and knowledge. Organization. Computer science. Information. Documentation. Librarianship. Institutions. Publications > 00 Prolegomena. Fundamentals of knowledge and culture. Propaedeutics > 001 Science and knowledge in general. Organization of intellectual work > 001.8 Methodology Science and knowledge. Organization. Computer science. Information. Documentation. Librarianship. Institutions. Publications > 00 Prolegomena. Fundamentals of knowledge and culture. Propaedeutics > 004 Computer science and technology. Computing. Data processing
Divisions:	Institute for Digitalisation of Education > Department of Open Education and Scientific Information Systems
Depositing User:	співробітн Ірина Мінтій
Date Deposited:	15 Oct 2025 16:57
Last Modified:	15 Oct 2025 16:57
URI:	https://lib.iitta.gov.ua/id/eprint/746771

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