EFFECTIVENESS OF THE DIGITAL COMPETENCE DEVELOPMENT METHODOLOGY FOR RESEARCHERS AND ACADEMIC STAFF USING OPEN EDUCATIONAL AND SCIENTIFIC INFORMATION SYSTEMS: FORMATIVE EXPERIMENT RESULTS

Abstract

The relevance of the study is determined by the intensive digital transformation of the scientific and educational space, which imposes new requirements on the professional competence of researchers and academic staff regarding the effective use of open educational-scientific information systems, scientometric databases and other digital tools in research, methodological, educational and organizational-communicative activities. The aim of the article is to present the results of a formative experiment evaluating the effectiveness of the developed methodological approach to developing digital competence of researchers and academic staff using open educational-scientific information systems. The research employs formative experiment methods and statistical analysis using Pearson's χ² criterion. The study content includes conducting an experiment involving 94 researchers and academic staff divided into experimental (49 people) and control (45 people) groups. A complex of methodologies was developed for using Canva web service, artificial intelligence systems (DeepThink, ScholarGPT), scientometric databases (Dimensions, ERIH PLUS, Scilit), cloud office solutions, social and academic networks, open journal systems (OJS) and other digital tools, integrated into a distance learning course on Google Classroom platform. The results demonstrate statistically significant differences between groups across all five components of digital competence: educational (χ²=6.54), research (χ²=10.83), methodological (χ²=7.82), organizational-communicative (χ²=7.37) and cross-activity (χ²=8.02). The most pronounced positive changes are observed in the experimental group for research competence, where the percentage of participants with high level (28.6%) exceeds the control group (13.3%) by 2.1 times, confirming the particular effectiveness of working with scientometric platforms and specialized artificial intelligence systems. The practical significance lies in the possibility of implementing the developed methodology in the continuing education system for researchers and academic staff.