DIGITAL READINESS FOR THE USE OF AI TOOLS IN THE PROFESSIONAL PRACTICE OF SPECIAL EDUCATION PROFESSIONALS
PDF (Ukrainian)

Keywords

special education
inclusive education
digital competence
generative artificial intelligence
AI tools
professional training

How to Cite

[1]
S. Levsha and N. Pakhomova, “DIGITAL READINESS FOR THE USE OF AI TOOLS IN THE PROFESSIONAL PRACTICE OF SPECIAL EDUCATION PROFESSIONALS”, ITLT, vol. 113, no. 3, pp. 70–89, Jun. 2026, doi: 10.33407/itlt.v113i3.6657.

Abstract

This article examines the digital readiness of students and professionals in the field of special education to use artificial intelligence (AI) tools in educational and professional activities. The relevance of the study stems from the growing use of generative AI and the need for its safe and methodologically grounded application in the preparation of materials, adaptation of tasks, and provision of correctional and developmental support.

The aim of the study is to systematize the terminology related to bots, AI assistants, agents, and agentic AI, as well as to assess the level of digital readiness to use such tools. The methodology combines a theoretical analysis of scholarly sources with an empirical survey of 138 respondents, including bachelor’s and master’s students and practicing professionals. Descriptive statistics and one-way analysis of variance (ANOVA) were used to analyze the results.

The findings indicate that generative AI tools are actively used in everyday, educational, and professional activities, although primarily for basic tasks, including information retrieval, text generation, and material preparation. Experience in creating and configuring specialized AI tools remains limited. No statistically significant differences were found in self-assessed levels of awareness among bachelor’s students, master’s students, and practicing professionals.

The theoretical analysis clarified the distinctions between bots, AI assistants, agents, and agentic systems and identified the main risks associated with their use in special and inclusive education. Key safeguards include professional verification of generated materials, minimization of personal data use, adherence to non-stigmatizing language, and preservation of the specialist’s decisive role. The findings confirm the need to develop methodological approaches to the responsible use of AI tools and highlight the prospects for developing specialized AI assistants to support the professional activities of special education specialists.

PDF (Ukrainian)

References

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REFERENCES (TRANSLATED AND TRANSLITERATED)

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[2] Organisation for Economic Co-operation and Development, OECD Digital Education Outlook 2026: Exploring Effective Uses of Generative AI in Education. Paris, France: OECD Publishing, 2026, doi: 10.1787/062a7394-en. (in English).

[3] H. Hobbs, D. Docherty, L. Aranda, K. Perset, K. Sugimoto, and R. Kierzenkowski, “Exploring possible AI trajectories through 2030,” OECD Artificial Intelligence Papers, no. 55. Paris, France: OECD Publishing, 2026, doi: 10.1787/cb41117a-en. (in English).

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[10] M. B. Hoy, “Alexa, Siri, Cortana, and more: An introduction to voice assistants,” Medical Reference Services Quarterly, vol. 37, no. 1, pp. 81–88, 2018, doi: 10.1080/02763869.2018.1404391. (in English).

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[12] F. Miao and W. Holmes, Guidance for Generative AI in Education and Research. Paris, France: UNESCO, 2023. [Online]. Available: https://unesdoc.unesco.org/ark:/48223/pf0000386693. Accessed: Jan. 27, 2026. (in English).

[13] N. Pakhomova, I. Baranets, I. Okhrimenko, L. Rudenko, L. Stakhova, and L. Moroz, “Utilizing specialized knowledge during correctional education with older preschool children with speech disorders,” Revista Conrado, vol. 19, no. 91, pp. 474–483, 2023. [Online]. Available: https://conrado.ucf.edu.cu/index.php/conrado/article/view/2977/2875. Accessed: Feb. 03, 2026. (in English).

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[21] P. Rizos et al., “Enhancing mathematics education for students with special educational needs through generative AI: A case study,” Contemporary Educational Technology, 2024, doi: 10.30935/cedtech/15487. (in English).

[22] U. Dello Iacono, L. Petti, and A. Vivarelli, “Story problems and artificial intelligence for inclusive design in mathematics: A study with Italian prospective special education teachers,” Research on Education and Media, 2025, doi: 10.2478/rem-2025-0012. (in English).

[23] C. Kotsi et al., “A review of artificial intelligence interventions for students with autism spectrum disorder,” Disabilities, vol. 5, no. 1, 2025, doi: 10.3390/disabilities5010007. (in English).

[24] A. Chalkiadakis et al., “Impact of artificial intelligence and virtual reality on educational inclusion: A systematic review of technologies supporting students with disabilities,” Education Sciences, vol. 14, no. 11, 2024, doi: 10.3390/educsci14111223. (in English).

[25] M. J. Wooldridge, An Introduction to Multi-Agent Systems, 2nd ed. Chichester, U.K.: John Wiley & Sons, 2009. (in English).

[26] C. Conati, K. Porayska-Pomsta, and M. Mavrikis, “AI in education needs interpretable machine learning: Lessons from open learner modelling,” in Proc. ICML Workshop Human Interpretability Mach. Learn. (WHI), Stockholm, Sweden, 2018, pp. 21–27, doi: 10.48550/arXiv.1807.00154. (in English).

[27] S. R. Goldman, A. Carreon, and S. J. Smith, “Exploring the integration of artificial intelligence into special education teacher preparation through the TPACK framework,” Journal of Special Education Preparation, vol. 4, no. 2, pp. 52–64, 2024, doi: 10.33043/6zx26bb2. (in English).

[28] A. S. Drigas, “Artificial intelligence in special education,” in Artificial Intelligence Applications and Innovations. Berlin, Germany: Springer, 2011, pp. 385–391. (in English).

[29] Z. Xi et al., “The rise and potential of large language model based agents: A survey,” arXiv preprint arXiv:2309.07864, 2023. (in English).

[30] Z. P. Alivia, J. Kustija, L. S. Riza, A. Hafina, A. G. Abdullah, and I. Widiaty, “Artificial intelligence for autism spectrum disorder,” Lex Localis – Journal of Local Self-Government, vol. 23, no. 10, pp. 290–321, 2025. (in English).

[31] C. Spulber, “Trends and emerging topics in the use of artificial intelligence in inclusive education,” Geopolitical, Social Security and Freedom Journal, vol. 7, no. 1, pp. 85–99, 2024, doi: 10.2478/gssfj-2024-0007. (in English).

[32] P. Creati and A. Cuccaro, “Special pedagogy and artificial intelligence: A digital humanism for inclusive education,” Italian Journal of Special Education for Inclusion, vol. 13, no. 1, pp. 202–213, 2025, doi: 10.7346/sipes-01-2025-17. (in English).

[33] L. Carling, A. R. Harkins-Brown, and D. C. Peloff, “Application of artificial intelligence to improve the quality of individualized education programs (IEPs) for students with disabilities,” in Proc. Soc. Inf. Technol. Teacher Educ. Int. Conf. (SITE), Orlando, FL, USA, 2024, pp. 1917–1919. (in English).

[34] S. Garg and S. Sharma, “Impact of artificial intelligence in special need education to promote inclusive pedagogy,” International Journal of Information and Education Technology, vol. 10, no. 7, pp. 523–528, 2020, doi: 10.18178/ijiet.2020.10.7.1418. (in English).

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Copyright (c) 2026 Serhii Levsha, Natalііa Pakhomova

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