DEVELOPMENT OF ARTIFICIAL INTELLIGENCE COMPETENCES FOR EDUCATORS IN THE DIGITAL SOCIETY
DOI:
https://doi.org/10.28925/2414-0325.2025.1813Keywords:
AI competencies, AI competencies for citizens, digital competencies, digital society, future AI competencies, cross-cutting AI competenciesAbstract
The article contains the latest research on the use of artificial intelligence (AI), analysis of approaches to determining AI competencies in a digital society. A comparative analysis of the frameworks of digital competencies and AI competencies for citizens and educators has been carried out. The relationship between digital competencies and AI competencies has been clarified. The components of the specified competencies for citizens in a digital society have been determined and the levels of development of the AI competency framework for citizens have been constructed. The article contains a detailed description of the specified competencies, namely examples of knowledge, skills, abilities and work experience of citizens in this field. The authors justify that some competencies in the constructed levels of development of AI competencies should not be placed in a horizontal direction, because some of them have a clear vertical direction. They will develop at all three levels of development of the AI competency framework for citizens and educators. The authors call such competencies cross-cutting AI competencies. The article also identifies a separate category of competencies, the formation and development of which will rapidly emerge with the development of AI and the digital society in particular. These are the future AI competencies that will emerge. The authors propose an updated model of development levels for AI competencies for citizens and separately for educators, taking into account cross-cutting and future competencies in the field of AI use.
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European Commission. JRC Publications Repository (2022). DigComp 2.2: The Digital Competence Framework for Citizens – With new examples of knowledge, skills and attitudes. March 17, 2022. https://publications.jrc.ec.europa.eu/repository/handle/JRC128415
European Commission. JRC Publications Repository (2017). European Framework for the Digital Competence of Educators: DigCompEdu. November 28, 2017. https://publications.jrc.ec.europa.eu/repository/handle/JRC107466
UNESCO (2024). AI Competency Framework for Teachers. August 8, 2024. https://www.unesco.org/en/articles/ai-competency-framework-teachers.
Ministry of Education and Science of Ukraine (2024, May 22). Project. Instructional and methodological recommendations for implementation and use of of artificial intelligence technologies in institutions of general secondary education. https://mon.gov.ua/static-objects/mon/sites/1/news/2024/05/21/Instruktyvno.metodychni.rekomendatsiyi.shchodo.SHI.v.ZZSO-22.05.2024.pdf
Sattelmaier, L., & Pawlowski, J. (2023). Towards a generative artificial intelligence competence framework for schools. In Proceedings of the 2023 International Conference on Enterprise and Industrial Systems (ICOEINS 2023), 4-5 October 2023, Bali, Indonesia.
Mikeladze, T., Meijer, P., & Verhoeff, R. (2024). A comprehensive exploration of artificial intelligence competence frameworks for educators: A critical review. European Journal of Education, 59 (e12663). https://doi.org/10.1111/ejed.12663
ERIC. P21 Framework Definitions (2009). Partnership for 21st Century Skills. December, 2009. https://eric.ed.gov/?id=ED519462
The OECD Learning Compass 2030 (2025). Future of Education and Skills 2030/2040 https://www.oecd.org/en/data/tools/oecd-learning-compass-2030.html
Baskara, F. (2025). Conceptualizing Digital Literacy for the AI Era: A Framework for Preparing Students in an AI-Driven World. Data and Metadata, 4, 530. https://doi.org/10.56294/dm2025530
Van Audenhove, L., Vermeire, L., Van den Broeck, W., & Demeulenaere, A. (2024). Data literacy in the new EU DigComp 2.2 framework: How DigComp defines competences on artificial intelligence, internet of things, and data. Information and Learning Sciences. https://doi.org/10.1108/ILS-06-2023-0072
Strutynska, O., Torbin, G., Umryk, M., & Vernydub, R. (2020). Digitalization of the educational process for the training of future teachers. In CTE 2020: 8th Workshop on Cloud Technologies in Education (pp. 179-199), December 18, 2020, Kryvyi Rih, Ukraine.
Morze, N., & Strutynska, O. (2021). Digital transformation in society: Key aspects for model development. Journal of Physics: Conference Series, 1946(1), 012021. https://doi.org/10.1088/1742-6596/1946/1/012021
Nuangchalerm, P., & Prachagool, V. (2023). AI-driven learning analytics in STEM education. International Journal on Research in STEM Education, 5(2), 77-84. https://doi.org/10.33830/ijrse.v5i2.1596
Digital skills & jobs platform. (2025). Have your say! Join the DigComp 3.0 Stakeholder Consultation. March 14, 2025. https://digital-skills-jobs.europa.eu/en/latest/news/have-your-say-join-digcomp-30-stakeholder-consultation
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Copyright (c) 2025 Umryk M., Morze N., Smirnova-Tribulskaya E.
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