- Іванова, С.М. (orcid.org/0000-0002-3613-9202) and Шиненко, М.А. (orcid.org/0000-0001-6697-747X) (2026) Areas of Application for Artificial Intelligence Tools in Educational Research In: Цифрова компетентність вчителя 2026: стратегії та практики навчання зі штучним інтелектом : збірник матеріалів . ІЦО НАПН України, м. Київ, Україна, pp. 130-134. ISBN 978-617-8330-68-2
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Abstract
This publication examines the conceptualization of shifts in the educational research paradigm under the influence of AI, as well as a comprehensive analysis of the ethical challenges and systemic risks associated with its integration into scientific and educational activities. The conducted research allows us to conclude that the integration of AI into the methodology of educational research is not merely a technological update, but a fundamental shift in the scientific paradigm. Summarizing the results of the analysis, the following key conclusions can be drawn. Artificial intelligence in modern educational science should be viewed not as an autonomous substitute for the researcher, but as a “cognitive partner.” Such human-machine interaction allows for combining the computational power of algorithms in big data processing with human critical thinking and ethical expertise. The main challenges remain the risks of academic misconduct, the occurrence of digital errors, and algorithmic bias. It has been established that overcoming these risks is possible only through the transparent disclosure of AI tool usage in scientific works and the implementation of strict protocols for verifying generated content. It has been demonstrated that despite high levels of automation, the researcher’s role remains indispensable at “critical junctures”: formulating research hypotheses, ethically evaluating data collection methods, and interpreting results within the specific sociocultural context of education. The POE model is identified as one of the effective mechanisms. The successful internationalization of Ukrainian educational research depends directly on the level of digital literacy among researchers. This requires not only technical proficiency with AI tools, but also an understanding of the FAIR principles to ensure the openness and reusability of research data in the global arena.for preserving the researcher’s cognitive autonomy.
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