PROSPECTS FOR DEVELOPING ACADEMIC STAFF’S DIGITAL COMPETENCE THROUGH GENERATIVE ARTIFICIAL INTELLIGENCE

Abstract

The article substantiates methodological recommendations and outlines prospects for developing academic staff’s digital competence through generative artificial intelligence. The empirical foundation of the study comprises survey results from Ukrainian academic staff (n = 567), which revealed a significant gap between declared awareness of generative artificial intelligence capabilities (89.1% rate their own knowledge at 3+ out of 5) and the level of its systematic use in professional practice (only 12.2% use it regularly). The methodological basis of the recommendations is formed by a five-component model for developing the digital competence of research and academic staff in the field of educational sciences (comprising learning, research, methodological, organisational-communicational, and cross-activity components) and the optimal toolset principle: for each type of professional task, a combination of specialised tools and generative artificial intelligence is determined based on requirements for accuracy, data security, and pedagogical accountability for outcomes. The recommendations and prospects for further digital competence development are differentiated across its five components and cover the main types of activity performed by academic staff. Special attention is given to Google NotebookLM as an environment capable of generating audio, video, structured diagrams, and presentations based on uploaded documents, as well as to Google Apps Script as a tool for the automated construction of diagnostic instruments. It is established that generative artificial intelligence demonstrates the highest effectiveness in formulating search queries, synthesising and structuring texts, generating code for data analysis, and stylistically refining academic texts, while specialised tools remain indispensable for tasks requiring high accuracy, data verification, and adherence to academic standards.