Svitlana Skvortsova, Tetiana Symonenko, Kira Hnezdilova AI-DRIVEN SYSTEMATIZATION OF EDUCATIONAL MATERIAL: EVIDENCE FROM UKRAINIAN EDUCATORS
(2026) Science and education, 2, 89-102. Odessa.
Svitlana Skvortsova,
Doctor of Pedagogical Sciences, Professor,
Professor at the Department of Mathematics and Methods of Teaching,
The state institution “South Ukrainian National Pedagogical University named after K. D. Ushynsky”,
26, Staroportofrankivska Str., Odesa, Ukraine,
ORCID ID: https://orcid.org/0000-0003-4047-1301
Tetiana Symonenko,
Doctor of Pedagogical Sciences, Professor,
Professor at the Department of Teaching Methods, Stylistics and Culture of the Ukrainian Language,
Bohdan Khmelnytsky National University of Cherkasy,
81, Shevchenko Boulevard, Cherkasy, Ukraine;
Center of Ukrainian Researchers in Austria,
Arbeitergasse 45, Vienna, Austria,
ORCID ID: https://orcid.org/0000-0001-5963-0451
Kira Hnezdilova,
Doctor of Pedagogical Sciences, Professor,
Professor at the Department of Primary and Special Education,
Bohdan Khmelnytsky National University of Cherkasy,
81, Shevchenko Boulevard, Cherkasy, Ukraine,
ORCID ID: https://orcid.org/0000-0002-5226-840X
AI-DRIVEN SYSTEMATIZATION OF EDUCATIONAL MATERIAL: EVIDENCE FROM UKRAINIAN EDUCATORS
SUMMARY:
In contemporary pedagogy, the rapidly increasing volume of information necessitates more effective systematisation of knowledge, as insufficient structuring often leads to fragmented understanding and the phenomenon known as “inert knowledge.” In this context, the emergence of generative artificial intelligence (AI) offers fundamentally new opportunities for automating the development of mind maps and concept maps, which are widely recognised as effective tools for organising and visualising learning content. However, the current state of adoption of these technologies in Ukrainian schools remains insufficiently explored. The aim of this study is to examine the extent, nature, and key factors influencing teachers’ use of AI tools for systematising learning materials, as well as to identify latent dimensions shaping their professional practices in this area. The research design integrates a systematic literature review and an analysis of existing AI services at the theoretical stage, followed by a largescale online survey of 1,949 teachers across Ukraine conducted using an original questionnaire. The data were processed using descriptive statistics and factor analysis (principal component method with Varimax rotation) in IBM SPSS Statistics 27. The findings demonstrate that AI tools, including ChatGPT, MindMeister, and Lucidchart, significantly reduce the time required to develop instructional materials and contribute to lowering students’ cognitive load. The study identifies the most widely used platforms and the primary tasks supported by AI-assisted mapping, including content decomposition, adaptive learning design, and information extraction. Furthermore, digital competence and prompt engineering skills emerge as key determinants of effective AI integration. The advantages of a hybrid “AI + human” approach are substantiated, particularly in ensuring contextual relevance, accuracy, and the development of critical knowledge construction skills.
KEYWORDS:
systematisation of learning content, artificial intelligence, mind maps, concept maps, generative language models, teacher digital competence
FULL TEXT:
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